Academic literature on the topic 'PLM (production or plant lifecycle management)'
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Journal articles on the topic "PLM (production or plant lifecycle management)"
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Carrizosa, I. Pablo, M. Oliver Rubio, O. Julián Mora, and G. Álvaro Guarín. "Keys for Redesign Industrial Facilities in a Current Productive Environment." Applied Mechanics and Materials 752-753 (April 2015): 1312–19. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1312.
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Today companies don’t have time and resources availability to stop their production to evaluate new layout and strategies, unless the results are guaranteed. Developing or redesigning products, gathering them in a product family and creating product platforms can be expensive tasks that represent a meaningful outlay for companies if they don’t have the adequate tools in order to facilitate the work. Thus, it is important to define the most appropriate manufacturing system as well as the performance of the chain value and the equipment layout in order to achieve an optimal production with the best quality and the shortest times and production costs. Therefore, computational tools, validated by working strategies and philosophies as Lean Manufacturing (LM) and Product Lifecycle Management (PLM) become necessary. After the evaluation of products, the value chain and the layout, these tools allow the construction of models and simulations as dynamic Value Stream Map (dynamic VSM), to analyze the actual process functioning or future process plans and PLM software, to estimate production flows, equipment and human labor requirements without stopping the normal production activities and providing competitive advantages to the company.
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Takahashi, Keita, Masahiko Onosato, and Fumiki Tanaka. "A comprehensive approach for managing feasible solutions in production planning by an interacting network of Zero-Suppressed Binary Decision Diagrams." Journal of Computational Design and Engineering 2, no. 2 (January 7, 2015): 105–12. http://dx.doi.org/10.1016/j.jcde.2014.12.005.
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Abstract Product Lifecycle Management (PLM) ranges from design concepts of products to disposal. In this paper, we focus on the production planning phase in PLM, which is related to process planning and production scheduling and so on. In this study, key decisions for the creation of production plans are defined as production-planning attributes. Production-planning attributes correlate complexly in production-planning problems. Traditionally, the production-planning problem splits sub-problems based on experiences, because of the complexity. In addition, the orders in which to solve each sub-problem are determined by priorities between sub-problems. However, such approaches make solution space over-restricted and make it difficult to find a better solution. We have proposed a representation of combinations of alternatives in production-planning attributes by using Zero-Suppressed Binary Decision Diagrams. The ZDD represents only feasible combinations of alternatives that satisfy constraints in the production planning. Moreover, we have developed a solution search method that solves production-planning problems with ZDDs. In this paper, we propose an approach for managing solution candidates by ZDDs' network for addressing larger production-planning problems. The network can be created by linkages of ZDDs that express constraints in individual sub-problems and between sub-problems. The benefit of this approach is that it represents solution space, satisfying whole constraints in the production planning. This case study shows that the validity of the proposed approach.
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Rangan, Ravi M., Steve M. Rohde, Russell Peak, Bipin Chadha, and Plamen Bliznakov. "Streamlining Product Lifecycle Processes: A Survey of Product Lifecycle Management Implementations, Directions, and Challenges." Journal of Computing and Information Science in Engineering 5, no. 3 (September 1, 2005): 227–37. http://dx.doi.org/10.1115/1.2031270.
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The past three decades have seen phenomenal growth in investments in the area of product lifecycle management (PLM) as companies exploit opportunities in streamlining product lifecycle processes, and fully harnessing their data assets. These processes span all product lifecycle phases from requirements definition, systems design/ analysis, and simulation, detailed design, manufacturing planning, production planning, quality management, customer support, in-service management, and end-of-life recycling. Initiatives ranging from process re-engineering, enterprise-level change management, standardization, globalization and the like have moved PLM processes to mission-critical enterprise systems. Product data representations that encapsulate semantics to support product data exchange and PLM collaboration processes have driven several standards organizations, vendor product development efforts, real-world PLM implementations, and research initiatives. However, the process and deployment dimensions have attracted little attention: The need to optimize organization processes rather than individual benefits poses challenging “culture change management” issues and have derailed many enterprise-scale PLM efforts. Drawn from the authors’ field experiences as PLM system integrators, business process consultants, corporate executives, vendors, and academicians, this paper explores the broad scope of PLM, with an added focus on the implementation and deployment of PLM beyond the development of technology. We review the historical evolution of engineering information management/PLM systems and processes, characterize PLM implementations and solution contexts, and discuss case studies from multiple industries. We conclude with a discussion of research issues motivated by improving PLM adoption in industry.
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Deuter, Andreas, and Sebastian Imort. "Product Lifecycle Management with the Asset Administration Shell." Computers 10, no. 7 (June 23, 2021): 84. http://dx.doi.org/10.3390/computers10070084.
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Product lifecycle management (PLM) as a holistic process encompasses the idea generation for a product, its conception, and its production, as well as its operating phase. Numerous tools and data models are used throughout this process. In recent years, industry and academia have developed integration concepts to realize efficient PLM across all domains and phases. However, the solutions available in practice need specific interfaces and tend to be vendor dependent. The Asset Administration Shell (AAS) aims to be a standardized digital representation of an asset (e.g., a product). In accordance with its objective, it has the potential to integrate all data generated during the PLM process into one data model and to provide a universally valid interface for all PLM phases. However, to date, there is no holistic concept that demonstrates this potential. The goal of this research work is to develop and validate such an AAS-based concept. This article demonstrates the application of the AAS in an order-controlled production process, including the semi-automatic generation of PLM-related AAS data. Furthermore, it discusses the potential of the AAS as a standard interface providing a smooth data integration throughout the PLM process.
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Camacho, Ana María, and Eva María Rubio. "Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020)." Applied Sciences 11, no. 13 (June 27, 2021): 5975. http://dx.doi.org/10.3390/app11135975.
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The Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020) has been launched as a joint issue of the journals “Materials” and “Applied Sciences”. The 14 contributions published in this Special Issue of Applied Sciences present cutting-edge advances in the field of Manufacturing Engineering focusing on advances and innovations in manufacturing processes; additive manufacturing and 3D printing; manufacturing of new materials; Product Lifecycle Management (PLM) technologies; robotics, mechatronics and manufacturing automation; Industry 4.0; design, modeling and simulation in manufacturing engineering; manufacturing engineering and society; and production planning. Among them, the topic “Manufacturing engineering and society” collected the highest number of contributions (representing 22%), followed by the topics “Product Lifecycle Management (PLM) technologies”, “Industry 4.0”, and “Design, modeling and simulation in manufacturing engineering” (each at 14%). The rest of the topics represent the remaining 35% of the contributions.
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Myung, Sehyun. "Innovation Strategy for Engineering Plant Product Lifecycle Management based on Master Data Management, Project Management and Quality Management." Korean Journal of Computational Design and Engineering 21, no. 2 (June 1, 2016): 170–76. http://dx.doi.org/10.7315/cadcam.2016.170.
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Winters, Jeffrey. "Punching Above their Weight." Mechanical Engineering 128, no. 02 (February 1, 2006): 22–24. http://dx.doi.org/10.1115/1.2006-feb-1.
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Smaller Companies are discovering that product management tools can help their small staffs get a global reach. The Product Lifecycle Management (PLM) software has become an important tool for managing people and resources at enterprises of any size. At Sonnax, the adoption of a PLM solution has led to some clear changes in information management. Instead of relying on a single point-person to do the project management for the whole company, each product line sales manager has become more deeply involved in the designs of specific lines. Indeed, many startups are incorporating PLM solutions before they even have products to manage. One factor that may be pushing small- and medium-size enterprises to adopt PLM solutions is the new globalized business model. Experts see PLM as way to help the far-flung pieces of the production chain mesh together. The system can be set up to enable suppliers of components anywhere in the world to look at the documentation they need, and to determine the most relevant information: what the history was, the nature of the changes, who approved it, and so forth.
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Thilmany, Jean. "Engineering Meets Manufacturing." Mechanical Engineering 129, no. 12 (December 1, 2007): 20–23. http://dx.doi.org/10.1115/1.2007-dec-1.
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This article discusses the future of software that links engineering and manufacturing. Companies are seeking a natural link between engineering and manufacturing, even if some aspects of it may be restricted. According to experts, giving manufacturers direct access to that design information would help them isolate potential manufacturing problems earlier in the cycle, cut product development time by stepping up design-manufacturing communication, and ensure that products will comply with government regulations. The article also describes that by allowing for quick communication and updates to an already existing computer-aided design model, product lifecycle management (PLM) can help speed these products to market. Engineers are putting efforts to bring PLM information to the factory floor to cut production time. Though the day of easy integration has yet to arrive, many companies are using PLM to reduce cycle time. Pushing PLM to the factory floor would help, according to an engineer. However, that's not an option for many until integration software comes to the fore.
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Camarillo, Alvaro, José Ríos, and Klaus-Dieter Althoff. "Product Lifecycle Management as Data Repository for Manufacturing Problem Solving." Materials 11, no. 8 (August 18, 2018): 1469. http://dx.doi.org/10.3390/ma11081469.
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Fault diagnosis presents a considerable difficulty to human operators in supervisory control of manufacturing systems. Implementing Internet of Things (IoT) technologies in existing manufacturing facilities implies an investment, since it requires upgrading them with sensors, connectivity capabilities, and IoT software platforms. Aligned with the technological vision of Industry 4.0 and based on currently existing information databases in the industry, this work proposes a lower-investment alternative solution for fault diagnosis and problem solving. This paper presents the details of the information and communication models of an application prototype oriented to production. It aims at assisting shop-floor actors during a Manufacturing Problem Solving (MPS) process. It captures and shares knowledge, taking existing Process Failure Mode and Effect Analysis (PFMEA) documents as an initial source of information related to potential manufacturing problems. It uses a Product Lifecycle Management (PLM) system as source of manufacturing context information related to the problems under investigation and integrates Case-Based Reasoning (CBR) technology to provide information about similar manufacturing problems.
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Kokareva, Victoria V., Andrey N. Malyhin, and V. G. Smelov. "Production Processes Management by Simulation in Tecnomatix Plant Simulation." Applied Mechanics and Materials 756 (April 2015): 604–9. http://dx.doi.org/10.4028/www.scientific.net/amm.756.604.
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This paper describes the process of simulation and modeling in the context of production engineering. In order to organize the smart and lean manufacturing, moreover flexible and efficient production processes we should use the digital manufacturing solution such as Tecnomatix Plant Simulation by optimizing and validating process performance, eliminating inefficiencies, shortening set up times and increasing quality before production. Manufacturing process management is an essential part of any PLM strategy. It enables you to connect your product design activities to your manufacturing planning activities.
Dissertations / Theses on the topic "PLM (production or plant lifecycle management)"
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Kipper, Marcelo Mondadori. "Proposta de metodogia de engenharia de domínio para o desenvolvimento de sistemas de automação industrial." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2010. http://hdl.handle.net/10183/31391.
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Engenharia de domínio (do inglês: DE - Domain Engineering) é uma proposta surgida no âmbito da Engenharia de Software e que visa o aumento do reuso no desenvolvimento de sistemas, buscando uma redução dos custos e do tempo de desenvolvimento. A aplicação desta técnica em sistemas de automação industrial (produtos e plantas industriais) – os quais incluem múltiplas disciplinas (sistemas mecânicos, elétricos, pneumáticos, entre outros), diferentemente da engenharia de Software que trata basicamente do reuso de artefatos de Software – vem despertando o interesse de algumas instituições de pesquisa, como o IAS (Instituto de Automação Industrial e Engenharia de Software da Universidade de Stuttgart), e será abordada neste trabalho. A engenharia de plantas industriais é crescentemente realizada nas chamadas ferramentas de gerenciamento de ciclo de vida de plantas PLM (Plant ou "Production Lifecycle Management"), que se originou do conceito de "Product Lifecycle Management", cuja sigla também é PLM. A idéia destas ferramentas é o gerenciamento de ativos não somente durante o processo de engenharia, mas também durante a operação e manutenção até o descomissionamento das plantas. Muitas destas ferramentas PLM englobam o paradigma de orientação a objetos da Engenharia de Software, e baseadas neste paradigma, abordam a integração de dados entre os artefatos das várias disciplinas. Este trabalho apresenta o conceito de um artefato técnico reutilizável multidisciplinar, que foi a base para a elaboração de uma metodologia de engenharia de Domínio adaptada a ferramentas PLM, que se baseiam no paradigma de orientação a objetos. A metodologia proposta foi validada experimentalmente em um estudo de caso de uma Planta Modular de Produção (MPS – Modular Production System) em conjunto com a ferramenta PLM Comos da Siemens. Os resultados obtidos indicam a viabilidade da implementação da metodologia proposta em projetos na indústria, visando a redução de custo e tempo de desenvolvimento através do reuso de artefatos técnicos multidisciplinares em domínios com aplicações semelhantes.Domain Engineering comes from the Software field and aims the increase of reuse to allow reduction of cost and time in the development of systems. The deployment of this methodology in automation systems (products and industrial plants) – in which more disciplines (mechanical, electrical, pneumatic, among others) are present and therefore differs from the Software engineering, that deals basically with the reuse of Software artifacts – has awakened the interest of some research institutes, like the IAS (Institute of Industrial Automation and Software Engineering of the University of Stuttgart), and will be analyzed during this work. The engineering of industrial plants is increasingly executed using the so called PLM Tools ("Plant or Production Lifecycle Management"), whose concept was originated from "Product Lifecycle Management", also abbreviated as PLM. The idea of these tools is to manage the assets not only in the engineering process, but also through operation and maintenance until the decommissioning of the industrial plants. Many of these PLM Tools support the object orientation principle from the Software engineering, and based upon this principle they address the integration of data from artifacts of the various disciplines. This work presents a concept for a multidisciplinary reusable technical artifact that was the base for the elaboration of an adapted DE Methodology for PLM Tools, in which the object oriented principle, is present. The presented ideas have been experimentally validated using as a case study a Modular Production System (MPS) together with the PLM Tool Comos from the company Siemens. The obtained results indicate a feasible implementation of the proposed methodology in the industry, aiming cost and time reduction through the reuse of multidisciplinary technical artifacts in domains with similar applications.
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Fife, Nathaniel Luke. "Developing a Design Space Model Using a Multidisciplinary Design Optimization Schema in a Product Lifecycle Management System to Capture Knowledge for Reuse." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd742.pdf.
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Kochan, Detlef. "Die TU Dresden als eine Keimzelle der Digitalisierung im Maschinenbau: Aktivitäten und Erfahrungen in der deutsch-deutschen und internationalen Zusammenarbeit von 1960 bis 2020." Prof. Dr. Detlef Kochan, 2021. https://slub.qucosa.de/id/qucosa%3A74429.
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Von Beginn der flexiblen Automatisierung mit numerisch gesteuerten Werkzeugmaschinen und der zugehörigen Programmier-Software bis zum gegenwärtigen Entwicklungsstand (Industrie 4.0) wird die historische Entwicklung von 1960 bis 2020 aus der Position eines aktiven Mitgestalters dargestellt. Interessanterweise vollzogen sich die wesentlichen Entwicklungsetappen für die ersten dreißig Jahre parallel in beiden deutschen Staaten. Aus den Lehren des Zweiten Weltkrieges wurden im Rahmen der UNESCO zum friedlichen Informationsaustausch geeignete wissenschaftliche Organisationen gegründet:
• IFIP (Internationale Föderation für Informationsprozesse, speziell Arbeitsgrupp CAM
• CIRP (Internationale Akademie der Fertigungstechniker)
Mit der Berufung und aktiven Mitarbeit in diesen Organisationen war eine Plattform für die deutsch-deutsche und darüber hinaus internationale Kooperation gegeben. Ein besonderer Schwerpunkt für den geordneten Informationsaustausch im Rahmen der gesamten dynamischen Entwicklung im Gebiet der Produktionsautomatisierung war dabei die im 3-Jahres-Rhythmus durchgeführte Konferenzserie PROLAMAT (Programming Languages for Machine Tools), gestartet 1969 in Rom. Im weiteren Verlauf wurde dieser Begriff viel breiter für das gesamte Gebiet der automatisierten Informationsverarbeitung und Fertigung erweitert. Ein besonderer Höhepunkt war dabei die erfolgreichste PROLAMAT-Konferenz 1988 in Dresden.
Parallel dazu erfolgten an der TU Dresden Entwicklungen in Richtung CAD/CAM-Labor und später CIM-TT (CIM-Technologietransferzentrum). Damit war an der TU Dresden 1989/90 ein Entwicklungsstand gegeben, der unmittelbar zu gemeinsamen deutsch-deutschen und internationalen EU-Projekten genutzt werden konnte. Dieses hohe Entwicklungsniveau wurde zur offiziellen Eröffnung des CIM-TT-Zentrums in den Eröffnungsreferaten durch den damaligen Wissenschaftsminister Dr. Riesenhuber und Ministerpräsident Prof. Biedenkopf gewürdigt. Durch die zum gleichen Zeitpunkt verfügte veränderte Nutzung des für das CIM-TT im Aufbau befindliche Gebäude durch die neugegründete Juristische Fakultät wurde der erfolgreich vorbereitete Weg verhindert. Unabhängig davon blieb meine fachliche Orientierung mit den gravierenden Weiterentwicklungen eng verbunden. Dazu trug das Sabbatical-Jahr in Norwegen und den USA 1992 maßgeblich bei. Mit dem Forschungsaufenthalt war die Entscheidungsvorbereitung für die vorgesehene Groß-Investition für das neueste generative Verfahren verbunden. Gleichzeitig mit dem fundierten Nachweis der bestgeeigneten sog. Rapid-Prototyping-Anlage vom deutschen Anbieter EOS München war die TU Dresden auf diesem neuen High-Tech-Gebiet 1992 in einer anerkannten Spitzenposition. Mit meiner Publikation eines der ersten Fachbücher im Gebiet Advanced Prototyping (jetzt Additiv Manufacturing) war darüber hinaus eine gute Basis für weitere innovative Aktivitäten gegeben Dazu gehört die Gründung einer High-Tech-Firma (SFM - Schnelle Fertigung von Modellen) mit bemerkenswerten beispielgebenden Ergebnissen. Hervorgehoben soll die zwanzigjährige aktive Kooperation mit der Universität Stellenbosch (RSA - Republik Südafrika), die unter anderem
mit meiner Berufung zum Extraordinary Professor im Jahr 2003 verbunden ist. Mit der Eröffnung eines Technologie-Zentrums nach dem Vorbild des ursprünglichen CIM TT -Zentrums der TU Dresden konnte für Südafrika ein wertvoller Beitrag geleistet werden.
Das gesamte Lebenswerk ist gekennzeichnet durch die Entwicklungsschritte von der Mathematisierung über die Algorithmierung bis hin zur Programmierung vielfältiger technologischer Sachverhalte. Die Ergebnisse sind in einer Anzahl von persönlichen Fachbüchern (z.T. übersetzt in das Russische und Ungarische) wie auch Konferenzberichten und mehr als 200 Veröffentlichungen (deutsch und englisch) dokumentiert.
Book chapters on the topic "PLM (production or plant lifecycle management)"
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Wuest, Thorsten, Stefan Wellsandt, and Klaus-Dieter Thoben. "Information Quality in PLM: A Production Process Perspective." In Product Lifecycle Management in the Era of Internet of Things, 826–34. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33111-9_75.
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Avvaru, Venkat Sai, Giulia Bruno, Paolo Chiabert, and Emiliano Traini. "Integration of PLM, MES and ERP Systems to Optimize the Engineering, Production and Business." In Product Lifecycle Management Enabling Smart X, 70–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62807-9_7.
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Ponnusamy, Senthil Kumar, and Yaashikaa Ponnambalam Ragini. "Product Lifecycle in the Pharmaceutical Industry." In Global Supply Chains in the Pharmaceutical Industry, 112–32. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5921-4.ch005.
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The composite of the present pharmaceutical industry requires more effective medication improvement and generation. A product lifecycle (PLC) is the progression of stages from the product's production to the world until its last withdrawal from the market. Product lifecycle comprises various stages that a product must possess in its lifespan, for example, launching, growth, maturity, and decline stage. While each stage brings huge changes, a progression of procedures for the administration of product lifecycle is required. Product lifecycle management (PLM) is a precise, controlled idea for overseeing and creating products and product-related data. Enhanced patient consistency, income development, extended clinical advantages, and faster market dispatch are among the primary utilization of product lifecycle management. To create a viable and productive product lifecycle management program many qualities are viewed like promising start, vital arranging clear authority, supporting information and abilities, readiness for changing tenets of government and associations.
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Bruno, Giulia, Emiliano Traini, Alberto Faveto, and Franco Lombardi. "Building a Factory Knowledge Base." In Advances in Computational Intelligence and Robotics, 50–75. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5879-9.ch003.
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In past decades, production has been characterized by the mass customization trend. This concept reaches its extreme with the one-of-a-kind production (OKP): every product is different for each customer. In order to develop unique product and complex processes in short time, it is mandatory to reuse the acquired information in the most efficient way. Several commercial software applications are already available for managing manufacturing information, such as product lifecycle management (PLM) and manufacturing execution system (MES), but they are not integrated. The aim of this chapter is to propose a framework able to structure and relate information from design and execution of processes, especially the ones related to anomalies and critical situations occurring at the shop floor, in order to reduce the time for finalizing a new product. To this aim, a central knowledge-based system (KBS), acting as integrator between PLM and MES, has been developed. The framework has been implemented with open source systems, and has been tested in a car prototyping company.
Conference papers on the topic "PLM (production or plant lifecycle management)"
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Zipori, Y. "An Analysis of Design and Digital Manufacturing Processes in a PLM Environment for the Aerospace Industry." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59588.
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Product Life Cycle Management (PLM) is a system that integrates computerized tools and methodologies for managing the engineering knowledge and information that defines products. The PLM approach covers all the stages of the product lifecycle, beginning with the initial concept definition and including requirement characterization, detailed design, analyses and simulations, transition from development to production, production planning, production, maintenance and end of life. PLM tools support design processes distributed among decentralized development groups, as well as knowledge and information management within and outside the organization, including suppliers, clients and business partners. As in ERP, which supports the supply chain and management of the organization’s operations, assets and resources, PLM supports the product definition information chain and management of the organization’s intellectual property (IP). PLM systems comprise the following main and tightly integrated components: • Systems engineering and requirement management tools; • CAD tools for defining the digital product; • Product data and engineering processes management – PDM; • Digital manufacturing system, including design and simulation of production lines. Integrating PLM into the management system can shorten time-to-market, reduce expenses, improve quality and encourage innovation and creativity in developing products and planning production and service processes. The paper describes the principles and components of the PLM approach and presents a case study involving a PLM implementation at Boeing and Airbus. The case study describes the design and digital manufacturing of the Airbus A380 and the Boeing 787 aircraft. Both companies used similar tools in the PLM environment. At the time of the study (2006), Airbus used Dassault Catia V4 and Catia V5 with the Enovia PLM system, while Boeing used Dassault Catia V5 with Enovia. Major differences were found in system implementation, engineering process definitions and management methods, leading to entirely different results. The main differences in the implementations at Boeing and at Airbus were as follows: • In both cases, the engineering project and the business environment were extremely complex. At Airbus, design and production took place in four different countries at 16 different sites, with 41,000 employees. At Boeing, 6,000 engineers at 135 sites designed the plane, with 300 major suppliers; • In the case of Airbus, because of CAD system incompatibility changes in the design of the electrical wiring harnesses caused the harnesses not to fit the airplane body. The digital prototype was not updated with all the changes, and the lack of fit was only discovered at the stage of the actual physical assembly; • Boeing laid down strict rules during the design process to ensure that the information was complete and up to date. At Boeing, all those involved in development and production were obligated to work with one central data base, which was updated at least twice a week by all participants; • Airbus reported major losses and delays in supplying the planes, while Boeing reported high profits and shorter time-to-market. Airbus reported a loss of 6 billion dollars and a two-year delay in supplying the A380. Boeing, in contrast, reported a savings of 2 billion dollars and a reduction of 12 months in the timetable for supplying the 787. The use of PLM in the above examples leads to the following conclusions: • The design of major engineering processes (i.e. change process) is a critical success factor to PLM implementation; • Digital information must be compatible among the various CAD systems in the entire design chain; • All participants in the design and supply chain must impose and enforce engineering procedures and processes; • The information must be integrated among all the components in the PLM system; • A single data base must be created to reflect the product definition during the entire lifecycle of the product.
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Guerra-Zubiaga, David A., and Simon Briceno. "Product Lifecycle Management Tools to Support Next Generation of Mechatronic Systems at Aerospace Industry." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71118.
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Product Lifecycle Management (PLM) Tools have been used extensively in different companies in recent years. These tools enable the development of components, products or assemblies in a digital way through their lifecycle. The entire lifecycle presents different challenges implementing digital tools and this paper explores relevant features between part design and manufacturing at mechatronics systems in the aerospace industry. New Product Introduction (NPI) process is a challenging task. In some cases, it is required not only the use of sophisticated robotics applications, but also in the integration of different instruments and controls in order to meet the accuracy and repeatability requirements. Complex scenarios need to be validated at early NPI stages at aerospace industry at not only part design, but also exploring the manufacturability of complex mechatronics processes demonstrating low cost production. Digital manufacturing tools in PLM are able to evaluate these complex scenarios through virtual prototyping to support the next generation of mechatronics systems in the aerospace industry. This paper argues that the understanding of virtual prototyping using digital PLM tools is an important issue for NExt GenerAtion MechAtronics SYstems (NEGAMASY) to support Aerospace Industry.
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Rafaj, Milan, and Stefan Valcuha. "Technology Solution for Small and Medium Sized Enterprises." In ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/esda2014-20374.
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Generally product lifecycle management (PLM) is characterized as an integrated management process of product information and related processes across the product lifecycle. PLM affects development time of product and optimize the cooperation of all components of the development process of products. Therefore attention has to be paid to this fact in production and research. Processes across the entire product lifecycle management are complex and it is difficult to support various levels of cooperation. It is necessary to identify technological solutions to facilitate the implementation of PLM systems into processes of product life cycle. In the paper is presented derivation of technology solutions for PLM (product lifecycle information modeling and management, product lifecycle knowledge management, design chain management, product lifecycle process management, product trade exchange, collaborative product service and product lifecycle portal for stakeholder, developer, customer, manufacturer and supplier) and applications of advanced information technologies for implementation of PLM. In the paper is also described the technological solution which was developed to meet industrial requirements and obtain long term sustainability in today’s highly competitive market. Currently, still only a few small and medium-sized enterprises (SMEs) uses real benefits that PLM offers. The small and medium-sized enterprises also try to implement those technologies but, despite their flexibility, they have difficulties in structuring and exchanging information. Enterprises also have problems in creating data models for structuring and sharing product information, especially in the context of extended enterprises. It is caused by several factors that may have information, technical and financial character. Article refers and highlights the benefits that PLM brings by extension of PLM into so called “Closed-Loop Lifecycle Management (CL2M)”. It also describes the major barriers to the implementation of PLM in SME and propose possible solutions.
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Ben Kheder, Anis, Sébastien Henry, and Abdelaziz Bouras. "Quality Improvement of Product Data Exchanged Between Engineering and Production Through the Integration of Dedicated Information Systems." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82914.
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Today, within the global Product Lifecycle Management (PLM) approach, success of design, industrialization and production activities depends on the ability to improve interaction between information systems that handle such activities. Enterprises deploy mainly PLM system, Enterprise Resource Planning system (ERP) and Manufacturing Execution System (MES) in order to manage sufficient product-related information and provide better customer-products. This paper proposes a methodological approach to improve the quality of data exchanged between engineering and production. This involves the integration among information systems especially the PLM-MES integration. Thus, the proposed approach aims to overcome the problem of data heterogeneity by proposing a mediation system resolving syntactic and semantic conflicts of data managed by these systems.
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Maletz, Michael, Martin Eigner, and Klaus Zamazal. "Issues of Today’s Product Lifecycle Management (PLM): Challenges and Upcoming Trends to Support the Early Phases of the Product Development Process." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87220.
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The requirements for the optimization of the Product Development Process (PDP) in manufacturing companies have grown enormously. There are many key concerns to which a modern PDP must respond. Lean production, structures oriented towards the business process, shorter product cycles and delivery times, as well as decreasing vertical range of manufacture in conjunction with decentralized customer/supplier cooperation, cost pressure, and quality management are only some examples. It is evident that in the early phase of the product development process 70% of the product costs are specified. This fact led to the beginning to already use improved methods, processes and IT solutions even in the early concept phase to have the highest influence on development projects. Typical topics for the optimization of the development processes and later realization in Product Lifecycle Management (PLM) solutions are Complexity Management, integration from Requirement Management to Product Structure, Multi-Domain (Mechatronic) Functional Product Description and Collaboration. This paper discusses above mentioned challenges to outline the originating problems arising from these challenges. Based on that, approaches to overcome these issues are outlined. Upcoming realization trends of PLM such as process oriented PLM implementation and Acceptance Management (to center human factors) complete this paper.
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Moser, Gerhard, Julien Le Duigou, and Magali Bosch-Mauchand. "Life Cycle Costing in Manufacturing Process Management." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82943.
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In the last two decades during which the competitive business environment increased, it became crucial for each company to find the most accurate strategy to make survive its business. For that reason they need to manage and control their costs. Life Cycle Costing is one of these tools, which helps to analyse the cost of a product in the whole life of a product. To be competitive, the organisations have to optimize not only their products but also all their processes. Manufacturing Process Management (MPM) addresses the area between product design and production. Therefore MPM supports to optimize the manufacturing area of a factory. With different virtual scenarios the best solution of the manufacturing process can be obtained and at the same time it is possible to reduce time to market, costs and increase the quality. The focus of this paper is to integrate Life Cycle Costing tools and methods in the MPM part of the Product Lifecycle Management (PLM). We will discuss the implementation of Activity Based Costing (ABC) and Case-Based Reasoning (CBR) methods in a PLM tool for an early design decision support.
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Clark, Corrie, and Christopher Harto. "Lifecycle Water Consumption of Geothermal Power Systems." In ASME 2013 Power Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/power2013-98167.
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Previous assessments of the sustainability of geothermal energy have focused on resource management and associated environmental impacts during plant operations. Within these constraints, studies have shown that overall emissions, water consumption, and land use for geothermal electricity production have a smaller impact than traditional base-load electricity generation technologies. According to the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE), geothermal energy generation in the United States is projected to increase nearly threefold, from 2.37 GW to 6.30 GW, by 2035 (EIA 2012). With this potential for significant growth in geothermal electricity production, there is a need to improve understanding of the environmental impacts across the life cycle of geothermal energy production systems. This paper assesses the use of freshwater in construction, drilling, and production activities of various geothermal power plants. Four geothermal technologies were evaluated: air-cooled enhanced geothermal systems (EGSs), air-cooled hydrothermal binary systems, evaporative-cooled hydrothermal flash systems, and air-cooled geopressured systems that coproduce natural gas. The impacts associated with these power plant scenarios are compared to those from other electricity generating technologies as part of a larger effort to compare the lifecycle impacts of geothermal electricity generation to other power generation technologies.
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Guerra-Zubiaga, David, Kevin Kamperman, and Mohamed Aw. "Virtual Commissioning for Advanced Manufacturing Using Digital Tools." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23335.
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Abstract Following the Industry 4.0 paradigm with the rise of smart factories, there is a growing need in exploring digital manufacturing tools compatible with Industrial Internet of Things (IIoT) functionalities. This paper discusses the concept of Virtual Commissioning (VC) including applications in present and near-future advanced automation and production. Specifically, global trends towards Industry 4.0 and virtual manufacturing processes are explored in addition to how and why these emerging technologies could be applied. Furthermore, the advantages of VC processes are contrasted to Traditional Physical Commissioning (TPC) to highlight the evolution of Product Lifecycle Management (PLM) software and the optimization of manufacturing processes since the turn of the century. This research aims to use state-of-the-art PLM software to replicate a physical prototype in near-perfect functionality to demonstrate the effectiveness of VC in an industrial setting. Developing a methodology for this research, the analysis is followed by a case study involving a Mini Festo Pick-and-Place (P&P) unit simulated in Siemens Tecnomatix Process Simulate and controlled via ladder logic executed in Totally Integrated Automation (TIA) Portal. As expected, the results of this case study validate the potential for optimized contemporary manufacturing solutions in which higher-quality goods are reliably produced with minimal delays at all-time low principal investments through the use of VC tools.
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Popa, Andrei, Ben Amaba, and Jeff Daniels. "A Framework of Best Practices for Delivering Successful Artificial Intelligence Projects. A Case Study Demonstration." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206014-ms.
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Abstract A practical framework that outlines the critical steps of a successful process that uses data, machine learning (Ml), and artificial intelligence (AI) is presented in this study. A practical case study is included to demonstrate the process. The use of artificial intelligent and machine learning has not only enhanced but also sped up problem-solving approaches in many domains, including the oil and gas industry. Moreover, these technologies are revolutionizing all key aspects of engineering including; framing approaches, techniques, and outcomes. The proposed framework includes key components to ensure integrity, quality, and accuracy of data and governance centered on principles such as responsibility, equitability, and reliability. As a result, the industry documentation shows that technology coupled with process advances can improve productivity by 20%. A clear work-break-down structure (WBS) to create value using an engineering framework has measurable outcomes. The AI and ML technologies enable the use of large amounts of information, combining static & dynamic data, observations, historical events, and behaviors. The Job Task Analysis (JTA) model is a proven framework to manage processes, people, and platforms. JTA is a modern data-focused approach that prioritizes in order: problem framing, analytics framing, data, methodology, model building, deployment, and lifecycle management. The case study exemplifies how the JTA model optimizes an oilfield production plant, similar to a manufacturing facility. A data-driven approach was employed to analyze and evaluate the production fluid impact during facility-planned or un-planned system disruptions. The workflows include data analytics tools such as ML&AI for pattern recognition and clustering for prompt event mitigation and optimization. The paper demonstrates how an integrated framework leads to significant business value. The study integrates surface and subsurface information to characterize and understand the production impact due to planned and unplanned plant events. The findings led to designing a relief system to divert the back pressure during plant shutdown. The study led to cost avoidance of a new plant, saving millions of dollars, environment impact, and safety considerations, in addition to unnecessary operating costs and maintenance. Moreover, tens of millions of dollars value per year by avoiding production loss of plant upsets or shutdown was created. The study cost nothing to perform, about two months of not focused time by a team of five engineers and data scientists. The work provided critical steps in "creating a trusting" model and "explainability’. The methodology was implemented using existing available data and tools; it was the process and engineering knowledge that led to the successful outcome. Having a systematic WBS has become vital in data analytics projects that use AI and ML technologies. An effective governance system creates 25% productivity improvement and 70% capital improvement. Poor requirements can consume 40%+ of development budget. The process, models, and tools should be used on engineering projects where data and physics are present. The proposed framework demonstrates the business impact and value creation generated by integrating models, data, AI, and ML technologies for modeling and optimization. It reflects the collective knowledge and perspectives of diverse professionals from IBM, Lockheed Martin, and Chevron, who joined forces to document a standard framework for achieving success in data analytics/AI projects.