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Journal articles on the topic 'Projects selection automation'
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1
Axmann, Bernhard, Harmoko Harmoko, and Malhotra Rahul. "The Assessment of Robotic Process Automation Projects with a Portfolio Analysis." Tehnički glasnik 17, no. 2 (2023): 207–14. http://dx.doi.org/10.31803/tg-20230416193006.
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RPA’s (Robotic Process Automation) usage in organizations has rapidly increased in recent years; as a result, companies have developed high expectations from this technology. However, according to Ernst & Young (E&Y), 30-50% of observed RPA projects initially fail and reveal several risks, which lead to investment losses. Consequently, the RPA project is prematurely retired, and the company is back to the manual process. This premature retirement is mainly because of wrong process selection and the not sufficient company automation (RPA) maturity. Therefore, this paper will introduce the concept of an RPA Portfolio, which will assess the complexity of business processes with a company’s automation (RPA) maturity. The RPA Portfolio is a new innovative concept to simplify and visualize the business process selection for RPA projects, and will help to introduce successfully the right RPA projects.
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Hansen, Seng, Alethea Suryadibrata, and Seng Hansun. "Infrastructure project selection automation using non-structural fuzzy decision support system II." Eastern-European Journal of Enterprise Technologies 1, no. 3 (121) (2023): 46–56. http://dx.doi.org/10.15587/1729-4061.2023.271822.
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In this study, we develop a web-based Decision-Making Tool (DMT) based on a four-year research project in building the proper multiple criteria Decision-Making Framework (DMF) for infrastructure project selection automation. Several challenges in selecting and prioritizing infrastructure projects include poor front-end planning, lack of project funding, improper investment, unsustainable development, regulatory barriers, and poor coordination among stakeholders. The Non-Structural Fuzzy Decision Support System II (NSFDSS-II) is chosen as the main method applied in the proposed DMF since it could resolve complex multi-criteria problems, even without sufficient information provided. When developing the DMT, Agile software development method is used since the development cycle can be run in a light and fast manner with iterative and incremental processes. The DMT is successfully developed by using PHP, HTML, and JavaScript which implement the proposed NSFDSS-II method. We further tested the decision results from the DMT by using eight real past infrastructure projects from relevant infrastructure agencies in Indonesia, such as the Ministry of Public Works and Housing (MPWH), the Ministry of Transportation, and the Local Government. The DMT outcomes were compared with the actual implementation status and evaluated by an independent expert. It was found that the decision results from the developed DMT are in accordance with the real implementation status of evaluated projects. The DMT is recommended to be used for infrastructure project selection automation. However, despite of its fast and accurate result, the DMT should be tested on larger number of infrastructure projects in the future
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Seng, Hansen, Suryadibrata Alethea, and Hansun Seng. "Infrastructure project selection automation using non-structural fuzzy decision support system II." Eastern-European Journal of Enterprise Technologies 1, no. 3 (121) (2023): 46–56. https://doi.org/10.15587/1729-4061.2023.271822.
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In this study, we develop a web-based Decision-Making Tool (DMT) based on a four-year research project in building the proper multiple criteria Decision-Making Framework (DMF) for infrastructure project selection automation. Several challenges in selecting and prioritizing infrastructure projects include poor front-end planning, lack of project funding, improper investment, unsustainable development, regulatory barriers, and poor coordination among stakeholders. The Non-Structural Fuzzy Decision Support System II (NSFDSS-II) is chosen as the main method applied in the proposed DMF since it could resolve complex multi-criteria problems, even without sufficient information provided. When developing the DMT, Agile software development method is used since the development cycle can be run in a light and fast manner with iterative and incremental processes. The DMT is successfully developed by using PHP, HTML, and JavaScript which implement the proposed NSFDSS-II method. We further tested the decision results from the DMT by using eight real past infrastructure projects from relevant infrastructure agencies in Indonesia, such as the Ministry of Public Works and Housing (MPWH), the Ministry of Transportation, and the Local Government. The DMT outcomes were compared with the actual implementation status and evaluated by an independent expert. It was found that the decision results from the developed DMT are in accordance with the real implementation status of evaluated projects. The DMT is recommended to be used for infrastructure project selection automation. However, despite of its fast and accurate result, the DMT should be tested on larger number of infrastructure projects in the future
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Bhargavi, S. M. Bindu, V. Suma, and R. Vijaya Arjunan. "Impact of Critical Success Factors on Productivity Gain during Automation Testing." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 15, no. 3 (2024): 92–108. http://dx.doi.org/10.58346/jowua.2024.i3.007.
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Software testing, a linchpin of quality assurance in software development, encompasses both manual and automation approaches. While manual testing ensures meticulous scrutiny, automation accelerates efficiency, reducing time and costs in dynamic landscape of software development. This research investigates the impact of critical success factors on productivity gain in software testing, with a focus on automation, within CMMI Level 5 companies. Drawing from a dataset comprising thirty real-time projects spanning banking, retail, and industrial applications, study explores dynamics of software development under agile and waterfall models. Interviews with developers and testers reveal insights into key aspects influencing productivity, including skills, experiences, and training. Emphasizing the need for strategic automation in projects subject to changes and maintenance, the research analyzes over thirty projects, scrutinizing variables such as manually designed test cases, execution time, and subsequent automation of test cases. Strategic selection of test cases for automation emerges as a cost-efficient practice. Results highlight a correlation between manual and automated test cases, indicating productivity gains. Research introduces a productivity gain metric, showcasing a break-even point where automation significantly reduces testing time. Overall, the findings offer a comprehensive understanding of software testing within CMMI Level 5, guiding organizations toward efficient automation practices and improved productivity.
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Yadav, Neelam, and Supriya P. Panda. "Developing standard criteria for robotic process automation candidate process selection." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 4 (2024): 4291. http://dx.doi.org/10.11591/ijai.v13.i4.pp4291-4300.
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<p>Robotic process automation (RPA) is a cutting-edge technology that provides software robots to repeat and mimic the repeatable tasks that a human user earlier performed. The use of software robots is encouraging because of their cost efficiency and easy implementation. Selecting and prioritizing a candidate process for automation is always challenging as all the business processes in an organization are not equally suitable for RPA implementation. Various studies have highlighted several criteria found in the literature for determining, prioritising, and selecting a business process for RPA. Nevertheless, there are no set standards for evaluating and analyzing a certain process or its tasks to determine whether they may be automated to use RPA. This paper aims to develop standard criteria and propose a consistent model to select and prioritize candidate process for RPA projects. To assess these criteria's applicability in the context of RPA, surveys among subject matter experts (SMEs) are used to validate them. Principal component analysis (PCA) and correlation are used to identify the top 20 criteria. Naïve Bayes algorithm is applied on the collected data for decision-making. The developed multi-criteria model exhibits strong precision and recall measures, with training and validation accuracy of 96% and 90%, respectively.</p>
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Neelam, Yadav, and P. Panda Supriya. "Developing standard criteria for robotic process automation candidate process selection." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 4 (2024): 4291–300. https://doi.org/10.11591/ijai.v13.i4.pp4291-4300.
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Robotic process automation (RPA) is a cutting-edge technology that provides software robots to repeat and mimic the repeatable tasks that a human user earlier performed. The use of software robots is encouraging because of their cost efficiency and easy implementation. Selecting and prioritizing a candidate process for automation is always challenging as all the business processes in an organization are not equally suitable for RPA implementation. Various studies have highlighted several criteria found in the literature for determining, prioritising, and selecting a business process for RPA. Nevertheless, there are no set standards for evaluating and analyzing a certain process or its tasks to determine whether they may be automated to use RPA. This paper aims to develop standard criteria and propose a consistent model to select and prioritize candidate process for RPA projects. To assess these criteria's applicability in the context of RPA, surveys among subject matter experts (SMEs) are used to validate them. Principal component analysis (PCA) and correlation are used to identify the top 20 criteria. Naïve Bayes algorithm is applied on the collected data for decision-making. The developed multi-criteria model exhibits strong precision and recall measures, with training and validation accuracy of 96% and 90%, respectively.
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Khattar, Kriti. "Docker Like a Pro: Essential Practices for Secure and Scalable Containers." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41900.
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Adopting best practices in project development is crucial for ensuring security, efficiency, and sustainability. Key practices include minimizing security risks by limiting access permissions, optimizing container images for faster deployments, and automating processes to reduce manual intervention. Additionally, effective configuration management, container health checks, and seamless integration of security tools within CI/CD pipelines help maintain system reliability and code quality. By leveraging cross-account access, choosing secure base images, and automating container restarts, projects can maintain operational stability while minimizing downtime. Overall, these practices foster a secure, scalable, and well-maintained environment for application development and deployment. Keywords: Docker Security Practices, Principle of Least Privilege, Multi-Stage Docker file, Docker Image Optimization, Configuration Management, Docker Tagging, Container Health Check, Base Image Selection, Cross-Account Access, CI/CD Pipeline Security, SonarQube, Prisma Cloud, Container Automation
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Rulon, Peter W. "Selection criteria for laboratory robotic application personnel." Journal of Automatic Chemistry 14, no. 2 (1992): 51–53. http://dx.doi.org/10.1155/s1463924692000129.
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Norwich Eaton Pharmaceutical recognized the benefits of using automation systems in the laboratory over seven years ago and created a robotic development area within the analytical method development group. They now have eight complete robotic systems and a large number of semi-automated systems in routine operation.This level of activity has provided many challenges for the automation group. The success of this group has been very dependent on the talents of people working these assignments. You can have the best equipment and the vendor's promises of success, but it is the people who understand the products and the requirements that get systems on line.Assembling an effective robotics organization requires prework on the part of management. There must be a clear vision of the specific types of activities the group will perform. This vision can be used to establish a skills profile for the members of the team. It appears that at least four people are required to provide the variety of skills and keep the group going.Each member's personality is an important component of establishing a new team. In robotics, one of the most critical talents is the ability to work on long term projects that constantly present new challenges. The group members need to balance consistency of purpose with the ability to creatively solve a variety of problems. The group will not be effective in delivering new technologies unless they have the talent to train the novice in a highly technical environment.People who are successful in automation development are unique. They should have the ability to work comfortably in a logic-based environment, to become very creative on demand, and to communicate highly technical information effectively. People do not usually possess all these skills, providing their manager with challenging coaching opportunities.
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Zu, Xian Feng, Yu Qin Han, and Gong Liu. "Selection of Optimal Measure Project for Automatic Test System." Applied Mechanics and Materials 128-129 (October 2011): 994–97. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.994.
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An optimal solution of multi-objective optimization has been proposed for the measure project of automatic test system (ATS) because of the formation complexity and the factors diversity. The method is used to select the optimal measure project for ATS. First a quasi-ideal solution is defined using maximum subjection principle from fuzzy theory. Then calculate the subjection of the existing projects and get their maximum subjection under specific weight set. Finally the optimal measure project has been obtained. The signal integrity, data throughput, cost, degree of automation, volume scale and expansion capabilities are regarded as integrated key factors according to bus forms and system architecture. The optimal measure project of ATS is determined by finding maximum subjection. Therefore the selection method enhances the cost-effectiveness of ATS formation.
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Baratov, Dilshod, and Elmurod Astanaliev. "Methodology for selection and efficiency of graphic software packages for technical documents." E3S Web of Conferences 402 (2023): 03018. http://dx.doi.org/10.1051/e3sconf/202340203018.
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The article describes the results of technical documentation automation projects. The effects of graphical representations of technical documentation are presented on the several levels. Performance indicators have been applied to other systems accordingly. The significant achievements of the program increase the efficiency of this system and automated technical documentation is convenient for all users. This system is more reliable, efficient, convenient and faster than others. Software indicators indicate the interdependence of numerous processes and the formation of these systems. Level coefficients are calculated using a calculation formula that generalizes system performance. Software capabilities are created through an improved method.
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Sureshkumar R, Sanjai Rohith M, Santhosh Kumar S, Somasankar S, and Sripathi S. "Web Implementation of the Smart Project Allocation." International Research Journal on Advanced Science Hub 7, no. 05 (2025): 498–506. https://doi.org/10.47392/irjash.2025.056.
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Final year projects are integral to graduation, showcasing students' depth of knowledge and essential soft skills like creativity and problem-solving. Recognizing the challenges of managing these projects manually, our project introduces a web-based Student Project Allocation and Tracking system. This system recommends project titles, prioritizes teams, matches projects and teams, manages project progress, and generates reports. Notably, it includes unique project title functionality to eliminate redundancy in project proposals, streamlining selection. The system aids Project Internal Guides, facilitating project selection and allocation, while empowering students to submit preferences. Heads of Departments (HODs) can utilize it to track project progress with involvement from Project Coordinators, supervisors, HODs, and students. The system also offers administrative tools such as project status reports, supervisor workload analysis, and automated reminders for upcoming submissions .By leveraging automation and intelligent allocation, the platform reduces administrative workload, enhances transparency, and fosters seamless collaboration ultimately improving the overall project management experience for students, supervisors, and academic coordinators, this application enhances collaboration, making the supervision process more formal and professional, thereby improving overall efficiency and quality.
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Grande, Vinicius Augusto, Renato de Campos, Ana Lúcia Figueredo Facin, and Gislaine Cristina Batistela. "An analysis of the benefits, challenges and methods of process selection to adopt robotic process automation." Revista Gestão da Produção Operações e Sistemas 17, no. 3 (2022): 89. http://dx.doi.org/10.15675/gepros.v17i3.2934.
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Purpose - Robotic Process Automation (RPA) is an emerging business tool that has gained the attention of organizations aiming to improve and transform their processes. However, RPA is not a solution that fits all existing scenarios and thus carefully-considered analysis is required before its implementation. This study aimed to carry out an analysis of the benefits, challenges and methods of selecting the most appropriate processes to be prioritized in RPA implementation projects.Theoretical framework - In addition to the basic concepts, the article was based on research in the literature that specifically deals with characteristics and methods for selecting processes to be automated with RPA.Design/methodology/approach - This is an applied, qualitative and exploratory research study that has adopted the literature review method to identify characteristics related to RPA technology. Articles were searched for from three academic sources: Science Direct, Scopus, and Web of Science.Findings - In addition to cost savings, the benefits identified were accuracy, productivity, and consistency. Benefits obtained in several areas of the industry were also synthesized. As challenges, common mistakes in projects where automation implementation failed and problems multiplied, such as a lack of training and support, were identified and listed. Finally, methods considering different characteristics and criteria were described in order to define organizational processes most compatible with RPA.Research, Practical & Social implications - Thus, the study seeks to contribute to the decision-making of those wishing to understand and introduce this technology into their organizations, enabling them to appropriately select processes to be automated with RPA.Originality/value - Despite the rapid development of the market in relation to process automation, no single model or guide for the proper selection of processes to be automated with RPA was identified, and each method found in the literature has specific characteristics.Keywords - RPA; Robotic Process Automation; Benefits; Challenges; Methods.
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Morin, Xavier, Nils O. E. Olsson, and Albert Lau. "Managerial Challenges in Implementing European Rail Traffic Management System, Remote Train Control, and Automatic Train Operation: A Literature Review." Future Transportation 4, no. 4 (2024): 1350–69. http://dx.doi.org/10.3390/futuretransp4040065.
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This paper explores the management of digitalization projects within the railway industry. It aims to increase and understand the opportunities presented by digitalization and automation in rail operations. Employing a scoping review methodology, this research investigates the execution of European Rail Traffic Management System (ERTMS), remote train control (RTC), and automatic train operation (ATO) projects spanning from 2005 to 2023, with a particular emphasis on metro automation, the remote control of freight and passenger trains, fully automated trains, and highly assisted driving. The refined selection process yielded 30 papers. The analysis of the retrieved papers identified managerial issues, with stakeholder management, change management, and organizational management emerging as recurring themes. Despite the increasing trend in publications, the limited representation managerial issues in ERTMS, RTC, and ATO projects in scientific research persists, with implications for the industry’s advancement. This research sheds light on the critical intersection of change management and digitalization within the railway industry by showing the impact of ERTMS, RTC, and ATO on organizational and scope dynamics. The need for human-centered systems is highlighted, showing the necessity of involving every echelon of the organization in the change management process. These findings provide insights for practitioners, researchers, and policymakers, emphasizing the need for understanding and addressing managerial aspects for successful and sustainable digitalization implementations.
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Thejas, Prasad. "Automate the Reconciliation Process of Open Payables Invoices and Migration Extract During Data Conversion." European Journal of Advances in Engineering and Technology 7, no. 8 (2020): 90–95. https://doi.org/10.5281/zenodo.13919094.
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Data migration of Accounts Payables (AP) invoices from Oracle E-Business Suite (EBS) to Oracle Fusion Cloud ERP is a complex and critical process, with the accuracy of the migration hinging on the selection of all eligible open payables invoices. Ensuring that these invoices are correctly extracted for migration requires meticulous reconciliation with the Oracle E-Business Suite Payables Trial Balance. Traditionally, this reconciliation process is performed manually, demanding significant time and effort while being prone to human error. The manual approach often results in discrepancies that can lead to incomplete or incorrect data migration, affecting the integrity of financial records in the new system. This article explores a solution approach to automating the reconciliation process, aiming to streamline and enhance the accuracy of the data conversion. By automating the comparison of open invoices in the migration extract with the Oracle E-Business Suite Payables Trial Balance, organizations can significantly reduce the risks associated with manual reconciliation. The proposed automation solution leverages advanced data extraction, transformation, and validation techniques to ensure that all relevant invoices are accurately captured and prepared for migration. The automation process not only increases efficiency but also improves data integrity by minimizing human intervention and errors. Furthermore, the article discusses the practical implementation of this automated reconciliation solution within the broader context of data migration projects. It delves into the technical aspects of setting up the automation framework, including the use of specific tools and technologies compatible with Oracle EBS ERP. By automating this critical reconciliation task, organizations can achieve a smoother transition to Oracle Fusion Cloud ERP, ensuring that financial data remains accurate and reliable throughout the migration process. This approach ultimately supports better decision-making and financial reporting in the post-migration environment.
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Del Blanco García, Federico Luis, and Laura Perez Lupi. "Parametric methods for virtual reconstruction. The hyperbolic paraboloids designed by Félix Candela." EGE-Expresión Gráfica en la Edificación, no. 10 (December 1, 2018): 18. http://dx.doi.org/10.4995/ege.2018.12437.
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<p>The paper explains the process used in a research project whose objective was the reconstruction of the hyperbolic-parabolic surfaces of a selection of non-built projects designed by Félix Candela.</p><p>The workflow was based on an automation process. After setting up the variables and define a procedural design, it has been possible to obtain the variation of the projects designed by Candela.</p><p>The virtual reconstruction was done using models parameterized with Grasshopper and experimentally with Houdini FX.</p><p>The results are valid not only for their scientific debate but also can have an educational role in the fields of geometry and architectural communication.</p>
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Weatherl, Michael H. "Technology Focus: Drilling Automation and Innovation (February 2021)." Journal of Petroleum Technology 73, no. 02 (2021): 44. http://dx.doi.org/10.2118/0221-0044-jpt.
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Drilling automation and innovation continue as dominant trends despite market downturns and unprecedented challenges in the past year. In many ways, the drive toward new efficiencies and step changes in well-construction performance has taken on an even greater sense of urgency. Further advancements in automation and innovation in well construction are recognized globally as keys to unlocking new opportunities in the ever-changing world in which we live. OTC Live sessions in late 2020 included a fascinating session titled “Opportunities and Challenges in Frontier Basins and Emerging Offshore Areas.” Despite pandemic-induced uncertainty, a significant number of high-impact exploration efforts, including projects in deepwater Gulf of Mexico, Brazil, west Africa, the Mediterranean, and Asia were ongoing. Panelists agreed, given world population and energy consumption being forecast to grow 20% by 2040, that increased hydrocarbon supplies, in addition to renewables, are essential to meeting future demand. The discussion also highlighted increased emphasis on carbon footprint reduction. Leaders from Shell, Expro, Wood Mackenzie, and others spoke to a CO2-intensity/barrel of oil equivalent chart comparing relative values for deep water, unconventionals, oil sands, and liquefied natural gas. It is noteworthy that deepwater production represents the lowest carbon footprint of all hydrocarbon sources by a significant margin. This advantage, combined with the potential for large resource size, high flow rates, and low well count, suggest that deepwater assets will compete in long-term portfolios for many operators. Referring to the current selection of SPE drilling-related manuscripts, automation of land rigs within onshore unconventional basins remains a widely published subject. More specifically, automation of the directional drilling process continues to yield improvements in performance and efficiency. It is often noted that well costs have been reduced by more than 50% with advancements related to horizontal technology, digitalization of well construction, and rig automation. These technologies were largely initiated within onshore, unconventional projects, but application is now wide-spread for offshore, complex wells. Selected papers in this feature are chosen to highlight the latest achievements and near-term opportunities across the full spectrum of upstream projects. A consistent message from paper SPE 203251 regarding drilling automation in the digital age reads, “industry has yet to benefit on a large scale from these advancements and…significant value remains untapped.” This reoccurring theme appears across operator and geographical boundaries, revealing significant opportunity and the need for ongoing emphasis. Software and hardware evolution progresses along with more- comprehensive integration of rig equipment and functionality. Industry now is more focused on moving from automation of individual tasks toward automation of the full well-construction process from plan to completed borehole. This idea is presented in paper SPE 201763. Change management remains a key issue within the process to ensure adequate control, early buy-in from stakeholders, and strong leadership. In summary, impressive examples of ongoing innovation span domestic unconventional plays, remote/international locations, geologically complex thrustbelt fields, and deep water with managed-pressure drilling in narrow pore pressure/fracture gradient environments. The few selections that appear here are a reflection of many more published by SPE in the past year and are a powerful testament to the ingenuity and perseverance of those involved.
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Fyedorova, Natalya Vasilevna, and Imran Gurruevich Akperov. "Formalizing choice of priority investment strategy." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2022, no. 4 (2022): 66–77. http://dx.doi.org/10.24143/2072-9502-2022-4-66-77.
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The paper considers the development of a method of forming and evaluating the priority of investment strategies aimed at creating technological (production) objects. A formalized approach to the formation and ranking 
 of investment projects is presented: the statement of the investment problem is formalized; a formalized analytical expression of the investment project is given. Possible factors and components of investment as components of an investment project are considered. Factors and criteria for evaluating the projects, ranking options, the role of the investor, a regulatory body and a decision maker in the formation of the project evaluation are considered. The role and directions of forming the components of the descriptive factor, financial and non-financial restrictions are shown. Methods of developing and ranking strategies for investing in technical and technological projects have been developed and presented in the form of a flowchart and of analytical constructions. Formalization of the processes of development and evaluation of investment projects will provide a systematic approach to the investment design, create the conditions for algorithmization and automation of priority investment strategies formation and selection.
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Shen, Yutong, Yuelong Wu, and Baozhen Yao. "Research on Heterogeneous Traveler Travel Mode Choices with Differences under a Mixed Traffic Environment." Sensors 23, no. 13 (2023): 6091. http://dx.doi.org/10.3390/s23136091.
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Autonomous vehicles (AVs) have been made possible by advances in sensing and computing technologies. However, the high cost of AVs makes privatization take longer. Therefore, companies with autonomous vehicles can develop shared autonomous vehicle (SAV) projects. AVs with a high level of automation require high upgrade and use costs. In order to meet the needs of more customers and reduce the investment cost of the company, SAVs with different levels of automation may coexist for a long time. Faced with multiple travel modes (autonomous cars with different levels of automation, private cars, and buses), travelers’ travel mode choices are worth studying. To further differentiate the types of travelers, this paper defines high-income travelers and low-income travelers. The difference between these two types of travelers is whether they have a private car. The differences in time value and willingness to pay of the two types of travelers are considered. Based on the above considerations, this paper establishes a multi-modal selection model with the goal of maximizing the total utility of all travelers and uses the imperial competition algorithm to solve it. The results show that low-income travelers are more likely to choose buses and autonomous vehicles with lower levels of automation, while high-income travelers tend to choose higher levels of automation due to their high value of travel time.
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Zolotukha, Roman, and Olena Glazunova. "DEVELOPMENT AND TESTING OF ALGORITHM FOR AUTOMATING TEAM FORMATION IN IT PROJECTS." Scientific Journal of Polonia University 61, no. 6 (2024): 203–10. http://dx.doi.org/10.23856/6125.
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The research aims to investigate the automation of recruiting and the formation of adaptive teams for IT projects using a proposed mathematical model. Additionally, the proposed algorithm needs to be tested in practice. The algorithm is based on weighting coefficients formed on the basis of expert assessments of key characteristics of candidates which are obtained by testing candidates for soft and hard skills. The research compares the results of two approaches: arbitrary team formation and a method based on a proposed mathematical algorithm. The authors conducted a practical study of both approaches during a hackathon whose task was to develop a web page for a future HR platform. The research methodology involved dividing the participants into two groups. The participants are divided into two groups. The first group forms teams independently during the hackathon, while the second group undergoes soft and hard skills tests during registration to determine team formation using a mathematical algorithm. The study’s authors present the effectiveness results of both groups and describe the advantages and possibilities for improving the algorithm. The conclusions drawn identify the achievements of the study and prospects for further development of the algorithm for automating team selection in the IT industry. This work contributes significantly to the understanding of effective strategies for forming IT teams, which is crucial in the face of constant technological changes.
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Wontorski, Paweł, and Andrzej Kochan. "Some aspects of project management in terms of design automation for railway traffic control devices." WUT Journal of Transportation Engineering 121 (June 1, 2018): 411–21. http://dx.doi.org/10.5604/01.3001.0014.4630.
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The article presents the concept of integration system of design automation and system of project management. A model was developed cooperation between the two systems on several levels, based on continuous monitoring of the design process and comparing the assumed values of the selected parameters from the actual values. The selection of variables transmitted based on the assumption of cooperation project management system with the system of design automation for railway traffic control devices, designed to support of designers. Due to the nature of projects for railway traffic control devices drew attention to the quality control of the project in the context of the safety and reliability of railway traffic control system, the impact of deviations from the schedule to the railway timetable, version compatibility, and changes in the chamfering work on objects with continuous rail traffic. The structure of the model is presented in graphical form.
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Wen, Pan, Iturralde Kepa, Bock Thomas, Garay Martinez Roberto, Macias Juez Olga, and Finocchiaro Pietro. "A Conceptual Design of an Integrated Façade System to Reduce Embodied Energy in Residential Buildings." Sustainability 2020 12 (14), Toward Smart Cities: Zero Energy Buildings (2020): 5730. https://doi.org/10.3390/su12145730.
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The overall energy requirement of a building may be impacted by the building design, the selection of materials, the construction methods, and lifecycle management. To achieve an optimum energy-efficiency level when dealing with a new building or renovation project, it is important to improve the entire construction process as it is not enough to merely focus on the operational phase. If conventional construction practices do not evolve, compromise, or adapt to necessary changes, then it becomes challenging to deliver an ultimate low energy building. This paper demonstrates the trend of off-site prefabrication and its production principles and the notions of open-building design and Design for X, as well as offering an overview of the development of automation in construction, which provides both insights and evaluations based on the context of the research. Three European Union Horizon 2020 research projects were evaluated, and the outcome of the projects served as the backbone for the research and inspired the design of the proposed integrated façade system. Two design scenarios were proposed to demonstrate the potential improvements that could be achieved in a new build as well as in renovation projects. The research lays a foundation for establishing a larger cross-disciplinary collaboration in the future.
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Sotnyk, Iryna, Kostiantyn Zavrazhnyi, Volodymyr Kasianenko, Hynek Roubík, and Oleksandr Sidorov. "Investment Management of Business Digital Innovations." Marketing and Management of Innovations, no. 1 (2020): 95–109. http://dx.doi.org/10.21272/mmi.2020.1-07.
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This paper considers the issue of investment management of digital innovations in modern business. The main purpose of the research is the development of approaches to the investment management of the innovative digitalisation processes of the enterprises and justification of the economic efficiency of investment projects on innovative information technologies use in the context of their relationship with existing information solutions for enterprise management. The relevance of the research is the necessity to change the methods of doing and managing the modern business, taking into account the achievements of the Third and Fourth Industrial Revolutions, which form innovative business philosophy based on informatisation and digitalisation of manufacturing and delivery processes. The implementation of innovative digital technology in business processes requires significant costs and it raises the issue on their minimization. Systematization of literary sources and approaches for the investment management of industrial digitalisation indicates the absence of complex solutions for this problem. In this regard, based on a comparative analysis, the authors have revealed the features of business development in the conditions of the Fourth Industrial Revolution and justified the need for modern information systems integration for enterprise management on the platform of business processes digitalisation. In order to create the road map of business digital innovations, it is suggested that the Theory of Constraints should be used to determine which of the operating information systems of the enterprise (Business intelligence – BI; Enterprise Resource Planning – ERP; Manufacturing Execution System – MES; Industrial Internet of Things – IIoT) is to begin the digital transformation with. The stages of the project development for the digital transformation of an enterprise are designed based on the structural approach. The economic justification for the selection of alternative digitalisation projects is based on an assessment of the labour costs for implementing two variants of digital innovation of a business entity: a complex automation project with up-front modelling and an integration automation project with the gradual implementation of a new information system. The assessment results have shown the economic benefits of implementing the integration project as it provides 1.58 times fewer labour costs and can be realized by use of universal package solutions such as Business Automaton Software (BAS). The analysis of the results of the implemented business digitalisation projects in Ukraine and the world as well as the potential of planned ones has allowed generalising the effects of their implementation and confirmed the need for further development of the mechanisms for the investment management of business digital innovations. Keywords automation, business, digitalisation, efficiency, greening, ERP, information technology, innovation, investment management, project.
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Rabia, Rahla, and Sathish Kumar. "BIM and GIS integrated utility supply station location optimization and possibilities." Journal of Applied Engineering Science 20, no. 4 (2022): 1384–94. http://dx.doi.org/10.5937/jaes0-40600.
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Optimal planning of utility supply station location is an integral part of infrastructural projects. In general, this is a multi-objective optimization process by considering engineering, financial and geographical constraints. A shift from conventional 2D-CAD, manual quantification and design application-based approach to Building Information Modelling (BIM)-Geographic Information System (GIS) integrated approach is found to be suitable for minimizing optimal planning time, cost and increasing automation. In this paper, an Autodesk Revit add-in tool is proposed aimed at integrating BIM and GIS for Genetic Algorithm (GA) based utility supply station location optimization and to assess the possibilities of this integration. From the case study it is observed that up to 90% of cost saving can be accomplished by this proposed approach. It is found that compared to the traditional multi-software approach with manual data transfer, this integration can be utilized for multi-stage optimization and is suitable for automating heterogenous data integration with increased accuracy. The platform in which the add-in tool is developed for the utility network can be at either BIM or GIS and this selection is influenced by the availability and ease of data retrieval from the respective semantic information system and the level of automation that is to be accomplished. Standardised BIM-based modelling combined with concepts like artificial intelligence and image processing techniques can be promising for attaining desired results in industrial applications.
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Udaipurwala, Asad, and Alan D. Russell. "Computer-assisted construction methods knowledge management and selection." Canadian Journal of Civil Engineering 29, no. 3 (2002): 499–516. http://dx.doi.org/10.1139/l02-030.
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The construction industry's information environment is undergoing rapid changes. Construction professionals now expect fast and reliable access to rich data sources. Significant advances have been made in streamlining the creation and dissemination of computer-aided design drawings and construction documents through incorporation of information technology in the workflow. However, there is a need to go beyond just the automation of existing paper flows and provide the construction knowledge worker with tools that can be easily used to document previous project experience, track new technological developments, and then incorporate these in the formulation of construction strategies for future projects. This paper describes work aimed at creating such tools in the context of a comprehensive decision-support system, by developing intelligent representation structures for storing and accessing construction domain knowledge and coupling them with advanced planning tools so as to enable the quick formulation and assessment of initial project plans. The information requirements and features needed for such a system are first examined, followed by a demonstration of how some of these requirements have been addressed in the system design and implementation. Aspects of a hypothetical high-rise building project are used throughout to illustrate application of the concepts developed.Key words: construction methods, integrated project management systems, methods feasibility reasoning, hierarchical scheduling, project views.
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Credle, Sydni, Nor Farida Harun, Grant Johnson, et al. "Blockchain Research and Development Activities Sponsored by the U.S. Department of Energy and Utility Sector." Energies 18, no. 3 (2025): 611. https://doi.org/10.3390/en18030611.
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This article provides an in-depth analysis of blockchain research in the energy sector, focusing on projects funded by the U.S. Department of Energy (DOE) and comparing them with industry-funded initiatives. A total of 110 funded activities within the U.S. power industry were successfully tracked and mapped into a newly developed categorization framework. This framework is designed to help research agencies to systematically understand their funded portfolio. Such characterization is expected to help them make effective investments, identify research gaps, measure impact, and advance technological progress to meet national goals. In line with this need, the proposed framework proposes a 2-D categorization matrix to systematically classify blockchain efforts within the energy sector.Under the proposed framework, the Energy System Domain serves as the primary classification dimension, categorizing use cases into 30 distinct applications. The second dimension, Blockchain Properties, captures the specific needs and functionalities provided by Blockchain technology. The aim was to capture blockchain’s applicability and functionality: where and why blockchain? Principles behind the selection of the viewpoint dimensions were carefully defined based on consensus obtained through the Blockchain for Optimized Security and Energy Management (BLOSEM) project. The mapped results show that activities within the Grid Automation, Coordination, and Control (31.8%), Marketplaces and Trading (25.5%), Foundational Blockchain Research (19.1%), and Supply Chain Management (17.3%) domains have been actively pursued to date. The three leading specific use case applications were identified as Transactive Energy Management for Marketplaces and Trading, Asset Management for Supply Chain Management, and Fundamental Blockchain for Foundational Blockchain Research. The Marketplaces and Trading and Retail Services Enablement domains stood out as being favored by industry by a factor greater than 2 (2.3 and 2.6, respectively), yet there seemed to be little to zero investment from DOE. Approximately 76% of the total projects prioritized Immutability, Identity Management, and Decentralization and/or Disintermediation compared to Asset Digitization and/or Tokenization, Automation, and Privacy and/or Anonymity. The greatest discrepancies between DOE and industry were in Asset Digitization and/or Tokenization and Automation. The industry efforts (36% in Asset Digitization/Tokenization and 22% in Automation) was 14 times and 2.4 times, respectively, more intensive than the DOE-sponsored efforts, indicating a significant discrepancy in industry versus government priorities. Overall, quantifying DOE-sponsored projects and industry activities through mapping provides clarity on portfolio investments and opportunities for future research.
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Wibowo, Andi Prasetiyo. "Unveiling the Potential of AI Assistants: A Review of AI in Building Materials Selection." Journal of Artificial Intelligence in Architecture 3, no. 2 (2024): 105–21. http://dx.doi.org/10.24002/jarina.v3i2.9293.
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Fast-advancing Artificial Intelligence (AI) has transformed many industries, including construction. AI offers innovative solutions to increase efficiency and effectiveness in various aspects of construction, one of which is selecting building materials. By reading relevant literature, this study aims to determine how much AI can help choose building materials so that projects go more easily and quickly. Using SCOPUS as its principal database, this study conducted a literature review. The method of this study begins with the process of filtering articles using the key string: ("artificial intelligence" OR AI) AND ("building materials" OR "construction materials") AND ("efficiency" OR "time" OR "cost") to find relevant articles. The research results show that AI can help improve time and cost efficiency in selecting building materials through various means, such as data analysis, material recommendations, cost optimisation, and performance estimation. In conclusion, this study shows that AI has much potential to make choosing building materials more efficient and effective, thus reducing building time, costs, and environmental damage. Still, it also dramatically impacts building monitoring and maintenance and task automation.
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Schofield, Alexandra, Siqi Wu, Theo Bayard de Volo, Tatsuki Kuze, Alfredo Gomez, and Sharifa Sultana. ""My Very Subjective Human Interpretation": Domain Expert Perspectives on Navigating the Text Analysis Loop for Topic Models." Proceedings of the ACM on Human-Computer Interaction 9, GROUP (2025): 1–30. https://doi.org/10.1145/3701201.
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Practitioners dealing with large text collections frequently use topic models such as Latent Dirichlet Allocation (LDA) and Non-negative Matrix Factorization (NMF) in their projects to explore trends. Despite twenty years of accrued advancement in natural language processing tools, these models are found to be slow and challenging to apply to text exploration projects. In our work, we engaged with practitioners (n=15) who use topic modeling to explore trends in large text collections to understand their project workflows and investigate which factors often slow down the processes and how they deal with such errors and interruptions in automated topic modeling. Our findings show that practitioners are required to diagnose and resolve context-specific problems with preparing data and models and need control for these steps, especially for data cleaning and parameter selection. Our major findings resonate with existing work across CSCW, computational social science, machine learning, data science, and digital humanities. They also leave us questioning whether automation is actually a useful goal for tools designed for topic models and text exploration.
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Chenzhong, Ren, Kan Wenliang, Zhou Taihua, Su Dongdong, Geng YongLi, and Wu Wenzheng. "Intelligent Generation and Analysis of the Municipal Road Construction Scheme Based on the KNN Algorithm." Mathematical Problems in Engineering 2022 (September 27, 2022): 1–15. http://dx.doi.org/10.1155/2022/8752870.
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The construction of municipal road engineering is a complex system engineering, and its internal components are interconnected and mutually restricted, and the relationship is intricate. The quality of its construction plan directly affects the realization of the project's quality, safety, environment, progress, cost, and other goals, and the project construction plan occupies an important position in the construction of the project. The selection of construction plans for municipal road projects involves a wide range of areas. According to the characteristics of specific municipal road engineering projects, it is very important to establish a scientific construction scheme intelligent generation model and select the optimal construction scheme suitable for the project from many feasible construction schemes, which has very important theoretical research value and practical application value. After analyzing the knowledge characteristics of road construction technology and the content of road construction schemes, this study decomposes the knowledge of road construction schemes into two parts: case characteristics and solutions. Then, according to the needs of case retrieval technology, the data storage form of each subdivision index is proposed and the value range is explained, and a complete structure form of the road construction scheme case database is formed. Combined with actual engineering cases, the feasibility and applicability of the intelligent generation method of the road construction scheme based on the KNN algorithm is confirmed, which provides a new idea for the automation of road construction scheme preparation and the improvement of the scheme application effect.
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Pan, Wen, Kepa Iturralde, Thomas Bock, Roberto Garay Martinez, Olga Macias Juez, and Pietro Finocchiaro. "A Conceptual Design of an Integrated Façade System to Reduce Embodied Energy in Residential Buildings." Sustainability 12, no. 14 (2020): 5730. http://dx.doi.org/10.3390/su12145730.
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(1) The overall energy requirement of a building may be impacted by the building design, the selection of materials, the construction methods, and lifecycle management. To achieve an optimum energy-efficiency level when dealing with a new building or renovation project, it is important to improve the entire construction process as it is not enough to merely focus on the operational phase. If conventional construction practices do not evolve, compromise, or adapt to necessary changes, then it becomes challenging to deliver an ultimate low energy building. (2) This paper demonstrates the trend of off-site prefabrication and its production principles and the notions of open-building design and Design for X, as well as offering an overview of the development of automation in construction, which provides both insights and evaluations based on the context of the research. (3) Three European Union Horizon 2020 research projects were evaluated, and the outcome of the projects served as the backbone for the research and inspired the design of the proposed integrated façade system. Two design scenarios were proposed to demonstrate the potential improvements that could be achieved in a new build as well as in renovation projects. (4) The research lays a foundation for establishing a larger cross-disciplinary collaboration in the future.
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PRAVORSKA, NATALYA. "METHOD OF APPLYING MACHINE LEARNING TO ENHANCE THE EFFICIENCY OF DEVOPS PROCESSES." Herald of Khmelnytskyi National University. Technical sciences 343, no. 6(1) (2024): 454–63. https://doi.org/10.31891/2307-5732-2024-343-6-68.
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Context. The speed and quality of software development determine the competitiveness of products, therefore integrating DevOps and machine learning through MLOps approaches opens new opportunities for optimization. The implementation of MLOps promises enhancements in automation, efficiency, and the quality of development, however, realizing these promises requires the development of practical tools and methods. Objective. The goal of this study is to develop and evaluate a prototype framework based on MLOps to optimize DevOps processes. This prototype is designed to demonstrate how the integration of machine learning can enhance key aspects of DevOps, such as: testing automation, system monitoring, and deployment processes. Method. The research methodology includes the development of a prototype that involves the selection and adaptation of machine learning tools for integration into DevOps. The prototype was experimentally tested on several projects to assess its impact on development speed and product quality. Results. The results confirm that the application of the MLOps framework prototype contributes to significant improvements in the automation of DevOps processes, especially in the areas of testing and monitoring. This, in turn, leads to a reduction in development time and an increase in the quality of the final product. The study demonstrates that implementing an MLOps-based framework prototype into DevOps processes can effectively enhance their productivity and quality. Conclusions. The conclusions from this study provide a valuable foundation for further development of MLOps tools and their application in the software development industry.
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Alekseev, M. V., V. S. Kudryashov, A. V. Ivanov, I. A. Kozenko, and M. O. Ovsenev. "Development of a geographic information system for monitoring work with customers for the supply, maintenance and automation of elevator equipment for LLC «Expert-Agro»." Proceedings of the Voronezh State University of Engineering Technologies 85, no. 2 (2023): 17–22. http://dx.doi.org/10.20914/2310-1202-2023-2-17-22.
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As part of the production practice in LLC «Expert-Agro» developed a geographic information system (GIS) for the supply and maintenance of the produced elevator equipment. In the MS Access system, a database of customers has been formed that contains the names of enterprises, addresses and coordinates of their location, contact information, information on orders (purchase, delivery and installation of equipment, maintenance of existing equipment, repair work, etc.). At the same time, a message is automatically generated when the day of completion of the order approaches, which allows you to control the efficiency of working with customers and, if necessary, extend the lead time of the order. In the MS Visual Studio integrated environment, using the gmap.Net library, geolocation was implemented to display customers on the map, which makes it possible to assess the geography of LLC «Expert-Agro» and plan further expansion of interaction. Controlling the location of customers also provides a solution to logistical problems for the supply of equipment. The system additionally provides for the selection of process parameters sensors, actuators, control controllers with input / output modules and other devices for automating the supplied equipment. At present, the GIS database is being filled with information on manufactured equipment and devices that are used in standard automation projects.
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Ochoa, Danny. "Technology Focus: Drilling Automation and Innovation (February 2024)." Journal of Petroleum Technology 76, no. 02 (2024): 50–51. http://dx.doi.org/10.2118/0224-0050-jpt.
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In recent years, operators and service companies have optimized drilling activities and reduced operational costs by accelerating the deployment of digital solutions. Among other applications, predictive data analytics are commonly used to estimate rock properties, reduce operational uncertainty, improve equipment maintenance processes, and optimize scarce human resources on specific tasks. Not surprising, then, is the number of initiatives to maximize the value of data and new machine-learning models to understand complex operations and the different levels of drilling automation around the world. The selection of technical papers for this month highlights some interesting examples implemented in diverse geographies. Sustainability appears today as a key driver for innovation. The complex process of decarbonization of our industry can be accelerated with the potential larger-scale application of emerging solutions with proven tangible impact. For instance, rig and equipment automation are a reality, with the capacity to lower emissions in drilling operations and help obtain improved and more-consistent results. Papers SPE 216249 and IPTC 22975 illustrate examples of actual benefits in different projects. The task of collecting, processing, organizing, and making sense of drilling information from multiple sources with minimum time requirements remains an opportunity for improved decision-making in project management. Paper OTC 32978 describes one case with the use of artificial intelligence for automatic classification of daily drilling reports as an enabler for better planning and accurate risk analysis. Worth emphasizing is the importance of extended reality as a growing and promising alternative with untapped potential in well construction, mainly as a resource for active learning and a collaboration tool among multidisciplinary teams. Paper SPE 212532, included in the additional recommended reading, gives an interesting overview of current applications associated with drilling operations and challenges ahead. Recommended additional reading at OnePetro: www.onepetro.org. SPE 217113 Machine-Learning Techniques for Real-Time Prediction of Essential Rock Properties While Drilling by K.W. Amadi, Australian University, et al. SPE 212532 Extended Reality and Gamification for Drilling by Crispin Chatar, SLB, et al. SPE 213043 Ensemble Machine Learning for Data-Driven Predictive Analytics of Drilling Rate of Penetration Modeling: A Case Study in a Southern Iraqi Oil Field by Dhuha T. Al-Sahlanee, BP, et al.
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Rybak, V. A., A. D. Grib, and Sh Ahmad. "Application of information technologies for automation management of environmental activity." «System analysis and applied information science», no. 3 (December 12, 2019): 36–45. http://dx.doi.org/10.21122/2309-4923-2019-3-36-45.
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The article deals with the problem of assessing the conformity of various resource-intensive industries and enterprises with the principles of environmental management. On the basis of existing systems, a new model of monitoring the implementation of innovative projects within the framework of the State Innovative Development Program of the Republic of Belarus is proposed, which includes five main levels: implementing organizations, Government customers, GU BelISA, State Committee on Science and Technology of the Republic of Belarus, Council of Ministers of the Republic Belarus, Administration of the President of the Republic of Belarus. This model is programmatically implemented using the latest information technologies and is presented in the form of a web portal for collecting, storing, processing and displaying relevant subject data.Generally developed approaches and automated tools have been tested and modified for the dairy industry, since this sector of the national economy is one of the most significant for the Republic of Belarus in terms of production. In this direction, indicators of waste-free, resource-intensive, energy-intensive and earth-intensiveness were proposed, which were reduced to a single integral index by the method of logarithmic averaging, which made it possible to increase the sensitivity to changes in terms compared with the arithmetic and geometric averages. To automate the process of collecting, storing, processing and displaying this information, a software tool has also been developed that allows to automate environmental management. The ultimate goal of this tool is to support decision making when choosing a project that is more environmentally friendly. For industries and technologies that do not fall into the category of rational from the point of view of environmental management, a mathematical model of their optimization has been developed with the selection of specific environmental protection measures. The economic efficiency of the developed automation tools was calculated using the methodology for determining the prevented environmental damage and summed up 28303 rubles per year for the company under study.
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Alsaif, Omar, and Amer Mohamed Shhatha. "A comprehensive Analysis of Approaches and Difficulties for Cybersecurity Threats- Article Review." Mustansiriyah Journal of Pure and Applied Sciences 2, no. 4 (2024): 126–39. http://dx.doi.org/10.47831/mjpas.2024.2.4.126-139.
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This study explores a broad range of cybersecurity research projects, including emerging fields like IoT and linked auto security as well as more established threats like malware and Distributed Denial of Service (DDoS) assaults. Scholars utilize a range of approaches, such as deep learning and machine learning, while paying close attention to clear dataset descriptions and the consequences of false positives and negatives. Accuracy and contextual awareness are critical, especially for Internet of Things security. Rapid threat identification relies on automation and effectiveness, and a commitment to progress is demonstrated by the incorporation of cutting-edge methods like Genetic, Wolf Optimization and new models. Finding a balance between feature selection, precision, and execution time presents a significant challenge. Similar examinations are made simpler by the accessibility of shared benchmark datasets. The final goal represented by reinforce bunch guards and advance computerized trust. This review gives data and courses to explore the continuously changing network protection scene.
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Alsaif, Omar, and Amer Mohamed Shhatha. "A comprehensive Analysis of Approaches and Difficulties for Cybersecurity Threats- Article Review." Mustansiriyah Journal of Pure and Applied Sciences 2, no. 4 (2024): 126–39. http://dx.doi.org/10.47831/mjpas.v2i4.164.
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This study explores a broad range of cybersecurity research projects, including emerging fields like IoT and linked auto security as well as more established threats like malware and Distributed Denial of Service (DDoS) assaults. Scholars utilize a range of approaches, such as deep learning and machine learning, while paying close attention to clear dataset descriptions and the consequences of false positives and negatives. Accuracy and contextual awareness are critical, especially for Internet of Things security. Rapid threat identification relies on automation and effectiveness, and a commitment to progress is demonstrated by the incorporation of cutting-edge methods like Genetic, Wolf Optimization and new models. Finding a balance between feature selection, precision, and execution time presents a significant challenge. Similar examinations are made simpler by the accessibility of shared benchmark datasets. The final goal represented by reinforce bunch guards and advance computerized trust. This review gives data and courses to explore the continuously changing network protection scene.
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Bondarenko, A. A. "The development of the system of accounting, control, analytical support, management tactics and development strategy of a large company оf holding type". Voprosy regionalnoj ekonomiki 40, № 3 (2019): 164–69. http://dx.doi.org/10.21499/2078-4023-2019-40-3-164-169.
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This article is based on the definition of key positions proposed by the author of vertical-horizontal operation of the Department coordinating JSC «RZD», combining the functions of accounting, control, analytical support, management tactics and development strategy of a large company of holding type. This article discusses the controversial aspects of the selection system of accounting and control and analytical support of management strategy and tactics of development of railway transport by all information flows in one using the automation of accounting, control, management processes, implementation of electronic document management, electronic financial and management reporting. The conclusions drawn are that the decision is strategically important and essential tasks of innovative development of JSC «RZD», requires improvement of their accounting information support, which in turn is impossible without development of methods of management costs, taking into account branch specificity of formation of the cost of rail transportation. The author offers methodicalsecurity projects (Development of KPI; financial Management and assurance Strategy development; Business planning; Operation of the Treasury; Cost management, etc.) that can greatly increase the informational efficiency of calculation.
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Shestakov, K. I., I. M. Sokolov, M. A. Pirogov, and S. G. Soloview. "Experience in Development, Implementation and Standardization of BIM Design in the Mining Industry." Mining Industry Journal (Gornay Promishlennost), no. 5/2021 (November 12, 2021): 40–50. http://dx.doi.org/10.30686/1609-9192-2021-5-40-50.
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The paper describes the experience of the RIVS Company in using the Building Information Model technologies as the key element, from software selection and training of the company's specialists to practical examples of applying these technologies in pilot projects and information models being developed under existing contracts. The process of interacting with the customer regarding coordination of the design solutions and visual presentation of the facility is also addressed. A performance assessment has been carried out based on the implementation and subsequent use of the BIM technology. Taking into account the research data, global and Russian trends in BIM-design, the RIVS Company continues to use and develop Building Information Model technologies, as well as to set challenging goals - from automation of modelling processes to the creation of a digital twin. This article and the data presented in it can help the companies that are implementing the Building Information Model technologies to making a decision in their favor of one or another software product. A real case illustrated in the article will give an insight into the use of the BIM technologies.
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Studdiford, Larry. "Looking at the bigger picture: Total cost of ownership considerations for baggage handling systems." Journal of Airport Management 19, no. 2 (2025): 173. https://doi.org/10.69554/qosd2216.
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There is ever-increasing pressure on airlines and airports to provide a positive customer experience for travellers. Coupled with the imposition of fees for baggage, the expectation of efficient and effective service is high. Yet, airport baggage handling systems (BHS) are often overlooked in large terminal projects. BHS design and procurement decisions are frequently based solely on capital investment considerations, without a holistic analysis of the life cycle cost of the system. Encouraging stakeholders to look at the project through a total cost of ownership (TCO) lens involves diving into design decisions, equipment selection, construction planning, operations and maintenance strategies, as well as the impact of various procurement methods. This paper offers a framework for engaging in a broader analysis of the considerations and trade-offs across the BHS project life cycle. Engaging all stakeholders from the beginning and helping them understand the impact of their choices during each phase of a BHS project can not only reduce costs, but uncover opportunities for innovation, energy efficiency and automation.
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Woo, HoSung, and Ja-Mee Kim. "Impacts of Learning Orientation on the Modeling of Programming Using Feature Selection and XGBOOST: A Gender-Focused Analysis." Applied Sciences 12, no. 10 (2022): 4922. http://dx.doi.org/10.3390/app12104922.
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In programming, modeling is a generalized explanatory system that organizes key characteristics of a specific matter or object of interest using computer science concepts. Modeling is integral for both automation design in programming education and communication in the collaborative process. This study investigates the effect of learning orientation on the modeling stage based on gender. The study includes 756 male and 688 female elementary-school students. We analyzed the results of XGBOOST by extracting the influential characteristics from feature selection along with the basic statistics. As a result of the study, it was confirmed that learners, regardless of gender, had the largest gap in modeling and that this was the stage at which differences occurred in programming education. For male students, the process of collecting data for modeling or devising a solution was found to be an important learning method. This shows that it is necessary to create an environment to focus on activities that derive solutions from the collected data along with strengthening information retrieval education. Although female students showed a similar tendency to male students, the process of cooperating with friends as a differentiating factor was found to be an important learning method. It seems necessary to apply teaching and learning methods that can strengthen team projects that can collaborate with friends. The findings could serve as a reference for teaching and learning design and operation for effective programming education.
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Sebbeh-Newton, Sylvanus, Prosper E. A. Ayawah, Jessica W. A. Azure, et al. "Towards TBM Automation: On-The-Fly Characterization and Classification of Ground Conditions Ahead of a TBM Using Data-Driven Approach." Applied Sciences 11, no. 3 (2021): 1060. http://dx.doi.org/10.3390/app11031060.
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Pre-tunneling exploration for rock mass classification is a common practice in tunneling projects. This study proposes a data-driven approach that allows for rock mass classification. Two machine learning (ML) classification models, namely random forest (RF) and extremely randomized tree (ERT), are employed to classify the rock mass conditions encountered in the Pahang-Selangor Raw Water Tunnel in Malaysia using tunnel boring machine (TBM) operating parameters. Due to imbalance of rock classes distribution, an oversampling technique was used to obtain a balanced training dataset for unbiased learning of the ML models. A five-fold cross-validation approach was used to tune the model hyperparameters and validation-set approach was used for the model evaluation. ERT achieved an overall accuracy of 95%, while RF achieved 94% accuracy, in rightly classifying rock mass conditions. The result shows that the proposed approach has the potential to identify and correctly classify ground conditions of a TBM, which allows for early problem detection and on-the-fly support system selection based on the identified ground condition. This study, which is part of an ongoing effort towards developing reliable models that could be incorporated into TBMs, shows the potential of data-driven approaches for on-the-fly classification of ground conditions ahead of a TBM and could allow for the early detection of potential construction problems.
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Chupin, Alexander, Svetlana Makar, Natalia Fomenko, Natalia Nikiforova, and Olga Orusova. "Analysis of the modern scientific and methodological apparatus for the development of the information infrastructure of the UTP of truck transportation on the territory of the EAEU." OOO "Zhurnal "Voprosy Istorii" 2022, no. 3-1 (2022): 233–40. http://dx.doi.org/10.31166/voprosyistorii202203statyi24.
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The development of the information infrastructure of the UTP of road freight transportation on the territory of the EAEU should be based on the appropriate scientific and methodological apparatus. The urgent need for its development determined the general scientific task. It consists in improving the theoretical provisions and scientific substantiation of recommendations for the development of the information infrastructure of the UTP of road freight transportation on the territory of the EAEU. At the same time, as the analysis showed, its solution can be achieved by solving a number of particular problems. These include, first of all: development of methodological provisions for improving the information infrastructure of the UTP of road freight transportation on the territory of the EAEU; development of a methodological approach to the selection of a set of automation tools for the information infrastructure of automobile checkpoints across the customs border of the EAEU; development of a methodological approach to assessing the cost of projects to improve the information infrastructure of the UTP of road freight transportation on the territory of the EAEU; scientific substantiation of recommendations for improving the information infrastructure of the UTP of road freight transportation on the territory of the EAEU.
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Schmidt, Daniel, Luis Fernando Casagranda, Maria Angela Butturi, and Miguel Afonso Sellitto. "Digital Technologies, Sustainability, and Efficiency in Grain Post-Harvest Activities: A Bibliometric Analysis." Sustainability 16, no. 3 (2024): 1244. http://dx.doi.org/10.3390/su16031244.
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Post-harvest grain processes play a crucial role in food supply chains. Recent research focuses on how digital technologies can minimize grain losses, enhance food safety, and reduce their environmental impacts. The relationship between technologies and efficiency and sustainability needs more clarity, particularly concerning critical control points in post-harvest activities. The purpose of this article is to establish a connection between digital technologies used in food supply chains and critical control points within post-harvest systems. The research method is a bibliometric analysis. A literature survey identified thirteen digital technologies. The most published technologies are simulation, automation, and artificial intelligence. The least is augmented reality. Previous research identified nine critical control points in post-harvest engineering solutions, responsible for most losses in efficiency and environmental impacts. A framework using a sample of recent case studies was constructed to relate digital technologies and critical control points. The primary contribution of the study is a categorized list of the most influential technologies corresponding to each control point. The significance and novelty lie in providing managers and practitioners in engineering solutions for post-harvest systems with a practical guide for decision-making in the selection of technologies for future projects. Ultimately, this aids in reducing losses and environmental impact.
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Feder, Judy. "Implementation of an Intelligent Drilling Automation System in the Middle East." Journal of Petroleum Technology 73, no. 02 (2021): 45–46. http://dx.doi.org/10.2118/0221-0045-jpt.
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This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 203251, “Drilling in the Digital Age: Harnessing Intelligent Automation To Deliver Superior Well-Construction Performance in a Major Middle Eastern Gas Field,” by Brennan Goodkey, Gerardo Hernandez, and Andres Nunez, Schlumberger, et al., prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually from 9-12 November. The paper has not been peer reviewed. While breakthroughs in digital technology have rewarded many industries with a step change in productivity and efficiency during the past decade, the drilling industry has yet to benefit on a large scale from these advances. The complete paper details the introduction of a drilling automation system (DAS) to deliver superior well-construction performance in a major gas field in the Middle East. The DAS was deployed on two onshore gas drilling rigs. The paper discusses the technology itself, the deployment process, implementation challenges, the agile development model, and the results achieved. Introduction In 2018, Schlumberger partnered with a major Middle Eastern national oil company on one of the world’s largest lump-sum, turnkey gas-well-delivery projects, where drilling operations had already been optimized by targeting high-impact, low-effort areas of opportunity. Drilling automation was pursued to achieve an improvement in performance, specifically to shift the technical limit and to minimize the frequency of service incidents that could cost days of nonproductive time (NPT). An in-house solution under development for some time was designed to take control of the rig’s surface equipment to automate and optimize most drilling tasks and to generate value in the following areas: Automation of drilling actions to perform exactly as planned, within the safe limits of operation, by eliminating the inconsistency of manual operation and its susceptibility to human factors Identification and mitigation of drilling dysfunctions that could lead to costly tool failures and incidents by using intelligence engines that would adapt drilling parameters continuously for best performance Technology Overview The DAS was developed as the execution component of a well-construction platform designed to link planning and execution. The planning component allowed for all well-design stakeholders to collaborate online and create the well plan simultaneously. Once prepared, the plan would be exported to the rig as a machine-interpretable digital drilling plan that the DAS could digest. With the validation of rig personnel, the DAS would then take control of a selection of drilling actions and execute exactly as instructed in the well plan. While drilling, extensive information would be collected to serve as a vehicle to drive performance when planning future wells. In the deployment summarized in the complete paper, a pilot version of the drilling automation module was deployed as a standalone product. The key objectives of design included three categories - dynamic planning, safety and resilience, and interoperability.
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Voronova, A. G. "Typification of Projects for the Transition to Cloud Services." Advanced Engineering Research (Rostov-on-Don) 24, no. 3 (2024): 274–82. http://dx.doi.org/10.23947/2687-1653-2024-24-3-274-282.
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Introduction. Digital solutions make the operation of the company clearer, reduce staff costs, and provide data security. Various aspects of automation, digitalization and cloud technologies are described in the literature. The question is raised about the quality of the methodological basis for such transformations. Global and narrow technical approaches are presented. As a rule, materials are presented from the perspective of experts in the implementation of digital technologies. In this paper, for the first time, the author's scheme is proposed that can allow not only providers, but also their customers to navigate the upcoming transition to the cloud. The latter will receive systematic information on how to select a contractor and the most economically feasible option of cooperation.Materials and Methods. The information model was based on the semantic network as a system of nodes, their characteristics and connections. Management of the cloud migration project and the migration itself were visualized. The contraction practice between providers and their customers was summarized. The specifics of the tasks of such projects were taken into account. The part of the subject area related to the implementation of a cloud service is algorithmic — a step-by-step transition to the cloud, a generalized scheme of the process taking into account the hierarchy of elements are presented.Results. For the first time, a method of self-preparation of a company for the implementation of cloud solutions is proposed. The algorithm systematizes the cloud migration processes. The activities related to goal setting, audit, selection of cloud environment and services, calculation of the economic efficiency of the project, planning and implementation of migration, technical support and scaling of processes are described. The possibilities of determining the economic feasibility of measures for the transition to the cloud are shown. The costs of equipment, data storage and processing, software licenses, salaries, information security, etc., are taken into account. The amount received is compared to the providers' offers. For the final decision, the costs of infrastructure support are taken into account — by the customer or the outsourcer. The best option is selected. As a result, the customer gets the opportunity to work with better profitability and scale the project. Feedback is provided, and processes are adjusted, starting with IT reaudit.Discussion and Conclusion. The proposed solution will give the customer's management a system view of the execution sequence when migrating to the cloud, the issues and tasks to discuss with a potential outsourcer. Providers can use the algorithm to typify and unify projects, which can eventually simplify the coordination of the list of services and the migration procedure with customers. In this way, the parties can free up significant resources in terms of time, labor and other costs. In addition, customers and providers can partially use the described semantic network to develop not only the organizational, but also the technical aspect of the project.
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Olorunshogo Benjamin Ogundipe, Azubuike Chukwudi Okwandu, and Sanni Ayinde Abdulwaheed. "Optimizing construction supply chains through AI: Streamlining material procurement and logistics for project success." GSC Advanced Research and Reviews 20, no. 1 (2024): 147–58. http://dx.doi.org/10.30574/gscarr.2024.20.1.0258.
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The construction industry faces numerous challenges in achieving efficient supply chains, particularly in material procurement and logistics. This paper explores the transformative potential of Artificial Intelligence (AI) in addressing these challenges and enhancing project success. The discussion covers current issues in construction supply chains, the pivotal role of AI in revolutionizing material procurement and logistics, and practical strategies for implementation. The paper delves into the fragmented communication, inefficient procurement processes, and limited logistics visibility that hinder construction supply chains. AI's application is examined in real-time data analytics, automation of procurement workflows, and the integration of intelligent logistics management systems. The implementation of AI in material procurement includes demand forecasting, automated vendor selection, and order tracking, while logistics streamlining encompasses real-time tracking, route optimization, and proactive delay management. Benefits of AI implementation are highlighted, including cost reduction through waste minimization and optimized logistics, increased efficiency in procurement processes, and improved project timelines. The paper incorporates case studies illustrating successful AI implementation in construction supply chains, showcasing tangible improvements in material procurement and logistics. Despite the evident benefits, the paper acknowledges challenges and considerations in AI adoption within the construction industry. Barriers to implementation are discussed, along with strategies to overcome resistance and ensure successful integration. By streamlining material procurement and logistics through AI, construction projects can achieve heightened efficiency, reduced costs, and improved collaboration among stakeholders, ultimately contributing to overall project success.
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Olorunshogo, Benjamin Ogundipe, Chukwudi Okwandu Azubuike, and Ayinde Abdulwaheed Sanni. "Optimizing construction supply chains through AI: Streamlining material procurement and logistics for project success." GSC Biological and Pharmaceutical Sciences 20, no. 1 (2024): 147–58. https://doi.org/10.5281/zenodo.13641489.
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The construction industry faces numerous challenges in achieving efficient supply chains, particularly in material procurement and logistics. This paper explores the transformative potential of Artificial Intelligence (AI) in addressing these challenges and enhancing project success. The discussion covers current issues in construction supply chains, the pivotal role of AI in revolutionizing material procurement and logistics, and practical strategies for implementation. The paper delves into the fragmented communication, inefficient procurement processes, and limited logistics visibility that hinder construction supply chains. AI's application is examined in real-time data analytics, automation of procurement workflows, and the integration of intelligent logistics management systems. The implementation of AI in material procurement includes demand forecasting, automated vendor selection, and order tracking, while logistics streamlining encompasses real-time tracking, route optimization, and proactive delay management. Benefits of AI implementation are highlighted, including cost reduction through waste minimization and optimized logistics, increased efficiency in procurement processes, and improved project timelines. The paper incorporates case studies illustrating successful AI implementation in construction supply chains, showcasing tangible improvements in material procurement and logistics. Despite the evident benefits, the paper acknowledges challenges and considerations in AI adoption within the construction industry. Barriers to implementation are discussed, along with strategies to overcome resistance and ensure successful integration. By streamlining material procurement and logistics through AI, construction projects can achieve heightened efficiency, reduced costs, and improved collaboration among stakeholders, ultimately contributing to overall project success.
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Macedo de Morais, Rinaldo, Samir Kazan, Silvia Inês Dallavalle de Pádua, and André Lucirton Costa. "An analysis of BPM lifecycles: from a literature review to a framework proposal." Business Process Management Journal 20, no. 3 (2014): 412–32. http://dx.doi.org/10.1108/bpmj-03-2013-0035.
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Purpose – Business process management (BPM) is an emerging research theme in management. BPM lifecycles are models that systematize the steps and activities that should be followed for conducting BPM projects. The theoretical and empirical studies present differences regarding the number of steps and activities that should be carried out for promoting BPM. Using the BPM lifecycle model of the Association of Business Process Management Professionals (ABPMP) – an entity that proposes a common body of knowledge on BPM, as a parameter, this paper conducts a literature review to investigate lifecycle models within the academic-scientific ambit, identify convergences and variations and analyze the alignment between business strategy and processes in BPM activities in these models. The purpose of this paper is to propose a framework that deals with alignment between strategy and business processes in an explicit manner. Design/methodology/approach – A literature review was conducted aimed at prospecting papers about the BPM lifecycle. For such, the Scopus, Google Schoolar and Science Direct databases were accessed. The selection process was structured in two steps: the first filtered studies based on a reading of the title, abstract and key words; the second step consisted of selecting papers based on a complete reading of those papers resulting from the first step and from the references they contained. Findings – Seven BPM lifecycle models were selected and analyzed. A comparison was presented between the model steps and the model proposed by ABPMP. The particularities of each model were identified and the study suggests an alignment of these models with the BPM lifecycle proposed by ABPMP, in particular with the analysis, design and modeling, implementation and monitoring and control steps. Four models do not include the planning step, whereas four others do not incorporate refining. The majority of models studied projects the automation of business processes. This study reinforces that ABPMP's BPM lifecycle is a reference model, observing that the activities in the other models studied are projected in it. However, it was observed that in the ABPMP model as well as the models studied, there is little emphasis on organization strategy and on defining process architecture. Thus, this study suggests the incorporation of activities proposed by Burlton (2010) as an additional instrument for the ABPMP BPM lifecycle model to align strategy to processes in BPM projects. For such, a framework was proposed that deals with alignment between strategy and business process in an explicit manner. Originality/value – This study presents a typology of BPM lifecycle models, with common characteristics and peculiarities, and it analyzes the alignment between processes and strategy in the models’ activities. This study can assist professionals in the adoption of a model for implementing BPM projects and for continuous improvement.
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Alshboul, Odey, Ali Shehadeh, Ghassan Almasabha, and Ali Saeed Almuflih. "Extreme Gradient Boosting-Based Machine Learning Approach for Green Building Cost Prediction." Sustainability 14, no. 11 (2022): 6651. http://dx.doi.org/10.3390/su14116651.
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Accurate building construction cost prediction is critical, especially for sustainable projects (i.e., green buildings). Green building construction contracts are relatively new to the construction industry, where stakeholders have limited experience in contract cost estimation. Unlike conventional building construction, green buildings are designed to utilize new technologies to reduce their operations’ environmental and societal impacts. Consequently, green buildings’ construction bidding and awarding processes have become more complicated due to difficulties forecasting the initial construction costs and setting integrated selection criteria for the winning bidders. Thus, robust green building cost prediction modeling is essential to provide stakeholders with an initial construction cost benchmark to enhance decision-making. The current study presents machine learning-based algorithms, including extreme gradient boosting (XGBOOST), deep neural network (DNN), and random forest (RF), to predict green building costs. The proposed models are designed to consider the influence of soft and hard cost-related attributes. Evaluation metrics (i.e., MAE, MSE, MAPE, and R2) are applied to evaluate and compare the developed algorithms’ accuracy. XGBOOST provided the highest accuracy of 0.96 compared to 0.91 for the DNN, followed by RF with an accuracy of 0.87. The proposed machine learning models can be utilized as a decision support tool for construction project managers and practitioners to advance automation as a coherent field of research within the green construction industry.
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Anwar, Nur Effendi, and Helga Ferdilla. "Pengaturan Kecepatan Dan Pengendalian Motor DC 5 V-110 V Menggunakan IC Tipe NE 555." Jurnal Teknologi Riset Terapan 1, no. 2 (2024): 113–23. https://doi.org/10.35912/jatra.v1i2.3157.
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Purpose: To determine the regulation of the rotation speed of a DC motor using an NE 555 type IC and by providing a stable voltage with the same working frequency but varying DC motor speed control pulse cycles. Methodology: This research method includes several stages, the stages in the research are as follows: The data required is the specifications of each component and the specifications of the hardware design to be made. The selection of tools and materials used must be in accordance with what is expected for setting and controlling the speed of a DC motor Result: The effect of the armature current (Ia) on the rotation speed of the motor is directly proportional; that is, the greater the rotation speed of the series self-amplifying DC motor. Contribution: This study can provide practical insight into how to implement DC motor speed adjustment in various applications, such as in the fields of automation, robotics, and other small control systems. This may help readers who wish to apply the techniques taught in their projects. Limitations: Dependence on specific ICs: Focusing on the use of the NE 555 IC may limit the understanding of other alternatives that may be more suitable or efficient for certain applications. This article could be better if it includes a comparison with other available methods or ICs.
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Desconsi, Rafael, and Fernanda Lazzari. "The Use of CRM in the Management of Micro and Small Businesses: A Qualitative Analysis." Revista de Gestão Social e Ambiental 19, no. 4 (2025): e012046. https://doi.org/10.24857/rgsa.v19n4-128.
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Objective: To analyze the use of Customer Relationship Management (CRM) in the management of Brazilian micro and small businesses (MSEs), highlighting benefits, challenges and managerial implications. Method: The research adopted a qualitative and exploratory approach, with semi-structured interviews conducted with managers and employees of six MSEs from different sectors that implemented CRM solutions in the last two years. Content analysis guided the identification of patterns, difficulties and gains. Results: The main benefits observed were: centralization and organization of customer data, automation of operational routines, integration between sectors and greater personalization in service. Among the barriers, cultural resistance, budgetary limitations, training gaps and inadequacy of some platforms to the realities of smaller companies stand out. Theoretical contributions: The study reinforces the literature on CRM by highlighting its implications in the digital transformation of MSEs, showing how leadership involvement and a data-driven culture positively impact results. Practical contributions: Good practices for adopting CRM are suggested: ongoing training, pilot projects, use of performance indicators, and selection of scalable and integrable solutions. The recommendations serve as a guide for managers seeking to modernize their customer relationship processes. Originality/value: The originality lies in the empirical approach applied to multiple real cases of Brazilian companies, offering practical and academic support to foster the strategic adoption of CRM in the context of micro and small companies.