To see the other types of publications on this topic, follow the link: Productivity machine.
Journal articles on the topic 'Productivity machine'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Productivity machine.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Qizi, Yunusova Nilufar Maxmudjon. "Productivity of Machine Translation." International Journal of Teaching, Learning and Education 2, no. 1 (2023): 01–02. http://dx.doi.org/10.22161/ijtle.2.1.1.
Full textAbstract:
This article is about the field of technical translation which is called machine translation (MT), or machine-assisted translation. This method of translation uses various types of computer software to generate translations from a source language to a target language without the assistance of a human. There are different methods of machine translation. A plethora of machine translators in the form of free search engines are available online. However, within the field of technical communication, there are two basic types of machine translators, which are able to translate massive amounts of text at a time. There are transfer-based and data-driven machine translators. Transfer-based machine translation systems, which are quite costly to develop, are built by linguists who determine the grammar rules for the source and target languages. The machine works within the rules and guidelines developed by the linguist. Due to the nature of developing rules for the system, this can be very time-consuming and requires an extensive knowledge base about the structures of the languages on the part of the linguist; nonetheless, the majority of commercial machine translators are transfer-based machines. .
2
Parkin, R., and F. Cutri. "Improving Machine Productivity." Integrated Manufacturing Systems 4, no. 3 (1993): 32–36. http://dx.doi.org/10.1108/09576069310042972.
Full text
3
Sauk, Hüseyin, and Mehmet Arif Beyhan. "Comparison of Performance Characteristics of Different Types of Hazelnut Harvesting Machines." Uluslararası Tarım ve Yaban Hayatı Bilimleri Dergisi 10, no. 2 (2024): 216–24. http://dx.doi.org/10.24180/ijaws.1421481.
Full textAbstract:
In this study, the possibilities of using the hazelnut harvesting machine with pneumatic effective harvesting unit produced by local manufacturers and the prototype manufactured hazelnut harvesting machine with mechanical effective harvesting unit in the mechanical harvesting of hazelnuts grown in flat and near flat land conditions were examined, some performance values (harvesting efficiency, labor requirement, machine+human labor requirement, field productivity, machine+human field productivity and kernel productivity) of hazelnut harvesting machines with mechanically operated harvesting units were determined under different orchard yield conditions. According to the results of the experiment, the hazelnut harvesting machine with a mechanical effective harvesting unit had a harvesting efficiency of 92.54-96.03% and; a labor requirement of 6.349-9.839 MİGh ha-1; machine+human labor requirement of 46.228-62.531 BİİGh ha-1; field productivity 0.158-0.102 ha MİGh-1; machine+human field productivity: 0.022-0.016 ha BİİGh-1; kernel productivity: 124.83-1322.08 kg h-1. The hazelnut harvesting machine with a pneumatic effective harvesting unit has a harvesting efficiency of 97.68-99.36%; labor requirement 70.349-105.647 BİİGh ha-1; machine+human labor requirement 108.509-147.481 BİİGh ha-1; field productivity 0.014-0.009 ha MİGh-1; machine+human field productivity 0.009-0.007 ha BİİGh-1; kernel productivity 18.90-67.18 kg h-1. As a result, when the characteristics of harvesting efficiency, field productivity, and kernel productivity of the machines are compared, the mass production of hazelnut harvesting machines with mechanically effective harvesting units can provide benefits for hazelnut producers in terms of reducing harvesting costs and demand for labor.
4
A. M. Ahmed Alwaise and Omer Haitham Kanam. "Study of Availability and Productivity of Automated Lines." International Journal for Research in Applied Sciences and Biotechnology 8, no. 1 (2021): 144–53. http://dx.doi.org/10.31033/ijrasb.8.1.17.
Full textAbstract:
In area of manufacturing, the indices of each manufacturing machine are the productivity and goodness of products. The theory of reliability is closely related to Indices of productivity, the both theories the efficiency of machines, and optimizations one. The reliability of machines has been guessed by standard indices of the theory of reliability. The main index of reliability of every manufacturing machine is its availability. However, indicated the reliability of industrial machines with complicate design have not expressed in equations of the productivity. These indices of accuracy should be a component of equations of a productivity of a machine and reflects changes of a productivity rate one on changes of indices of reliability and mechanical parameters of a machine. The availability has been included the equations of the machines productivity rate, therefore the reliability of machines is the integrated indication. The machines reliability with complicate design such as automated lines relies also on construction and technical data. The output modelling has been reported the output result with availability for the automated lines, defining their structures according to the grade of reliability and productivity as a task of technical motif of manufacturing machines with complex designs.
5
Yash, R. Ravande, N.Patil Vaibhav, D. Bedge Sachin, P. Dadibude Prathmesh, and J. Awati Kautuk. "Development of Multi Spindle Drilling Machine to Enhance the Productivity in Sonica Industries, Kagal." Journal of Recent Trends in Mechanics 5, no. 1 (2020): 1–5. https://doi.org/10.5281/zenodo.3739101.
Full textAbstract:
The productivity and quality gives larger growth to Indian manufacturing sector at larger rate. The productivity of sector depends upon many factors. One of the major factors is efficiency of manufacturing where the operation and other activities are carried out in the organization. Reducing the total machining time, combining the different operations gives better productivity. In the organizations where mass production is carried out in which variety of jobs are less and quantity to be produced is huge it is essential to produce the jobs at faster rates. There is necessary to use special purpose machine rather than general purpose machine. Improving productivity with quality is done by use of special purpose machine. The designing of multi spindle head attachment gives better performance and usefulness to existing drilling machines. This paper deals with development and design of drilling head for cycle time optimization of product. The report gives study of comparison between conventional drilling machines and special purpose drilling machines in terms of time, number of jobs produced and number of operators required.
6
Raval, Shreeom, Harshil Raval, Darshit Seta, and Rathour Anilkumar. "DESIGN AND DEVELOPMENT OF MULTI SPINDLE DRILLING MACHINE." International Journal of Innovative Research in Advanced Engineering VII, no. VI (2020): 299–304. https://doi.org/10.26562/ijirae.2020.v0706.003.
Full textAbstract:
This paper discusses the case study and comparison with productivity of component using traditional drilling machine to Multi spindle drilling machine. The growth of Indian manufacturing sector depends upon many factors, one of the major factors being manufacturing efficiency with which the operation /activities are carried out in the organization. Productivity can be improved by reducing the total machining time, combining the operations, etc. There are frequent needs of tightening and loosening screws, drilling, tapping, boring and grinding operational machines. Huge and complicated designed parts cannot be machined in ordinary machines. In a single machine all the above specified operations can be carried out after drilling operation by removing of drill head and using the required tools like grinding, tapping can etc. By this we can achieve our industrial requirements and production targets. Here we are going to develop a single multi spindle drilling machine which can useful for drilling multiholes and tapping operations in single setup of work piece.
7
Bhatia, Anmol, Deepa Manani, Anubhav Grover, and Jatin Kumar. "Design of Multi Spindle Drilling Machine." International Journal of Advance Research and Innovation 4, no. 2 (2016): 114–18. http://dx.doi.org/10.51976/ijari.421618.
Full textAbstract:
In today’s world, the growth of Indian manufacturing sector is highly dependent on how productivity and quality. Productivity can be increased by improving the efficiency of the operations carried out in the organization. This can be done by reducing the machining time, combining the operations etc. Thus special purpose machines needs to be used and one such machine is multi spindle drilling machine which performs multiple drilling operations more accurately and conveniently. This paper presents the design and development of a multi spindle drilling machine which would have a higher productivity as compared to conventional drilling machines. The proper sequence wise design analysis of the components of multi spindle machine is discussed.
8
Rasyid, Mohammad Andi, and Tedjo Sukmono. "Total Productive Maintenance Analysis to Increase Machine Productivity." Procedia of Engineering and Life Science 7 (March 17, 2024): 571–80. http://dx.doi.org/10.21070/pels.v7i0.1530.
Full textAbstract:
The food manufacturing industry, especially dry and instant noodles, continues to grow rapidly, especially export market opportunities. Companies are required to increase productivity to meet domestic and international market demand. The role of machine performance is very vital in the production process, therefore the machine must always be in optimal condition. The high downtime caused by frequent breakdowns of production machines has a big impact on the productivity that the company wants to achieve. This activity aims to measure the effectiveness of the machines used at PT. Surya Pratista Hutama and measuring the efficiency of production machines and equipment. Each company can find out the performance of the machines used by calculating the level of equipment performance using the Total Productive Maintenance (TPM) method. The method used to measure TPM performance is the Overall Equipment Effectiveness (OEE) method. The use of this method is intended to provide equipment performance results as well as accurate calculations to determine the performance of the machine used. The results of this activity show that the Overall Equipment Effectiveness (OEE) value still has an effectiveness level below standard. The main factors that influence low OEE values are reduced speed losses, idling minor stopage losses, defects in process and breakdown losses. Therefore, preventive maintenance measures are needed to minimize the occurrence of machine damage.
 Highlights:
 
 Rapid growth in the food manufacturing industry demands increased productivity.
 Machine performance is crucial for maintaining optimal production processes.
 Total Productive Maintenance (TPM) and Overall Equipment Effectiveness (OEE) methods help measure and improve machine efficiency.
 
 Keywords: Maintenance, Total Productive Maintenance, Overall Equipment Effectiveness, Six Big Losses.
9
Nurlaila, Qomarotun. "Peningkatan Produktivitas Pada Lini Perakitan Stopper Crash Stop Dengan Otomatisasi Mesin Produksi." SIGMA TEKNIKA 5, no. 1 (2022): 158–66. http://dx.doi.org/10.33373/sigmateknika.v5i1.4123.
Full textAbstract:
PT. ABC is a Japanese PMA that produces HDD (Hard Disk Drive) components, where the assembly process still uses a partial automatic machine whose productivity still depends on the performance of the operator to do manual work. This research aims to increase the productivity of HDD products on the assembly line. The research design used is a combination of exploratory and descriptive methods. Its research approach uses quantitative data. The variable of this study is productivity, the type of data used is primary data and secondary data. The method to increase productivity on the Crash Stop assembly line is to eliminate manual work and change the assembly machine (assemble rubber and stainless components) from partially automatic to fully automatic. The result after replacing the assembly machine from partially automatic to fully automatic was that productivity increased by 2.5 times compared to the previous one which was an increase of 4,707 pieces / person / hour (from 1,913 to 6,620 pieces / person / hour). From the research that has been done, it can be concluded that productivity on the assembly line increases after the replacement of the machine from a partially automated machine to a fully automatic machine. In the future, it is expected that automatic machines can be applied to other production machines.
10
Rahmasari, Venny, and Andung Jati Nugroho. "Analisis Produktivitas Flange Menggunakan Metode Objective Matrix (OMAX) dan Fault Tree Analysis (FTA)." ULIL ALBAB : Jurnal Ilmiah Multidisiplin 3, no. 4 (2024): 18–27. https://doi.org/10.56799/jim.v3i4.3076.
Full textAbstract:
PT Mitra Rekatama Mandiri is a metal casting company that produces flange (sand pump machine axis cover). Based on company data for 2023, flange production results experienced ups and downs with a total production output of 303,946 kg. The aim of the research’ is to determined the level of productivity, analyze the factors that influence the level of productivity and provide suggestions for improvement. The methods used are (OMAX) and (FTA). The results of productivity measurements show that production is unstable with an increase in extreme productivity levels in August 2023 of 690 and October 2023 of 711 as well as a decrease in extreme productivity levels in June 2023 of -27, September 2023 of -27 and November 2023 of -15. Factors that influence productivity levels are unscheduled machine maintenance, old machine components, machine capacity exceeding 500 kg, erosion of furnace linings, dirty machines, melting temperatures exceeding 1,200°C, hot environmental conditions and poor lighting. Proposed improvements include making a machine maintenance schedule, replacing machine components, checking the machine capacity does not exceed 500 kg, replacing the furnace lining material, cleaning the machine, checking the melting temperature, making ventilation and adding lighting.
11
Gagliardi, Kayla, Simon Ackerman, and Pierre Ackerman. "Multi-Product Forwarder-Based Timber Extraction." Croatian journal of forest engineering 41, no. 2 (2020): 231–42. http://dx.doi.org/10.5552/crojfe.2020.736.
Full textAbstract:
Accurate predictions in forest operations can be used towards effective planning, costing, and maximizing the productivity of machines in mechanised cut-to-length (CTL) harvesting. There is a general and substantial gap in forwarder productivity data available for pine sawtimber in South Africa at present, and as the number of product assortments being harvested increase there is a need for more work to quantify the effects of extracting products of different dimensions. The aim of this study was to calculate the time consumption and productivity of two models of Ponsse forwarders (15 t and 20 t capacity) to consider and compare the effects of multiple variables including machine capabilities, product assortment, load size, extraction distance and fuel consumption. Productivity averaged at 34.08 m3 per productive machine hour excluding delays longer than one minute (PMH1) for the smaller machine, and 55.94 m3/PMH1 for the larger machine. Productivity and average log volume were strongly positively correlated. Regression models were created for each machine where load volume and extraction distance were both significant factors for predicting productivity. Average fuel consumption of the smaller machine was 15.55 l/PMH1 and 0.47 l/m3, and 20.57 l/PMH1 and 0.43 l/m3 for the larger machine. The product with the largest volume was found to require the least fuel per m3. The models developed could aid in predicting system productivity and potentially carbon emissions under similar conditions in a South African context of industrial plantation forestry.
12
Kar, Avijit, and Arun Kiran Pal. "A new approach for effective productivity management of newspaper printing press." Journal of Graphic Engineering and Design 15, no. 2 (2024): 17–29. http://dx.doi.org/10.24867/jged-2024-2-017.
Full textAbstract:
Within the modern commercial printing press, a common problem is the ef-ficient management of the maintenance of different machines of newspaper printing press. If Effective Maintenance Management is applied, productivity of the machines can be increased by reducing breakdown time of the ma-chine. Productivity Management is an organizational framework that helps machines to improve productivity. Productivity of a machine is dependent on the failure probability which can be controlled by technical and management actions. The present investigation is established by the analysis of productivi-ty, effectiveness and failure probability on the basis of Pareto Analysis. Pareto chart is also developed to understand the actual scenario where highest prior-ity events are sequentially arranged. It has been observed that the web-offset printing machine has the highest productivity and effectiveness with less failure probability while the exposure unit has the highest failure probability having low productivity and effectiveness. Based on the reduction of proba-bility of failure to meet the acceptable criteria, further maintenance planning can be suggested. This approach confirms that productivity and effectivity of the machines of newspaper printing press can be increased by considering consequences of the machines and their corresponding failure assessments.
13
Widyantoro, Murwan, Yuri Delano Montororing, Paduloh Paduloh, Solihin Solihin, and Murhaban Murhaban. "Proposed Productivity Improvement of 1800 Press Machine Using Overall Equipments Effectiveness." Jurnal Mekanova: Mekanikal, Inovasi dan Teknologi 7, no. 2 (2021): 85. http://dx.doi.org/10.35308/jmkn.v7i2.4207.
Full textAbstract:
Increased productivity is an effort to increase production capacity by increasing the productivity of each factor of production. PT XYZ is a company that uses sophisticated machines and facilities to produce aluminium profiles that create various needs in the form of building goods or furniture products in the form of doors, windows, partitions, frames, rolling doors, etc. One of the machines used is the 1800 press machine. This study aims to increase productivity with Overall Equipment Effectiveness (OEE) to make improvements. Based on the calculation of the Overall Equipment Effectiveness (OEE) of the 1800 press machine during January - December, the final value was 52%, this value indicates that the effectiveness of the 1800 press machine has not reached the ideal deal of 85% so that some improvements are needed. The company experiences the three most considerable losses: Breakdown Losses, Setup and Adjustment Losses, and Reduce Speed Losses, so repairs must be made to these three losses so that the 1800 press machine can achieve its best performance. Keywords— Overall Equipments Effectiveness (OEE), Six Big Losses, 1800 press machine
14
Arifin, Iskandar, and Anhar Malik. "Analisis Produktivitas Mesin Mixer Batching Ready Mix dengan Metode OMAX di Kalla Beton." Elektriese: Jurnal Sains dan Teknologi Elektro 15, no. 01 (2025): 11–23. https://doi.org/10.47709/elektriese.v15i01.5654.
Full textAbstract:
Kalla Beton Unit Ready Mix Plant is a company that produces bulk concrete (ready mix). Until now, the company does not have a comprehensive understanding of the performance and level of production productivity, especially in the mixer batching plant machine. This mixer machine is the main component in production operations, so its efficiency and effectiveness greatly determine the company's output. This study aims to measure the productivity level of the mixer batching plant machine using the Objective Matrix (OMAX) Method. This method measures productivity separately in each production section, allowing for evaluation based on criteria by each section's functions and responsibilities. Productivity is a key factor in ensuring the success and sustainability of operations, so data-based analysis and evaluation are needed to improve company performance. In this study, the productivity of the mixer machine was measured based on three main criteria: raw material productivity, effective working hour productivity, and operational effectiveness of the mixer machine. The measurement results showed that the highest productivity value occurred in July, with an achievement of 5,822 tons/hour, while the lowest value occurred in April, with 2,374 tons/hour. A cause-and-effect diagram analysis was conducted to identify the causes of productivity fluctuations, which showed that the low season factor influenced the decline in productivity in the early to mid-year, where the number of orders was still relatively low. The findings of this study can be a basis for companies to design strategies for improving and increasing productivity, especially in optimizing the use of batching plant mixer machines to be more efficient and effective.
15
Mahesh, Nigade*1 Vipin D. Chopade2 Dhananjay D. Pise3 &. Amit H.Raheja4. "AN ADVANCED MANUFACTURING MACHINE, OCTAHEDRAL HEXAPOD MACHINING SYSTEM." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 4 (2019): 135–41. https://doi.org/10.5281/zenodo.2635797.
Full textAbstract:
The quest for higher productivity and higher precision in the manufacturing industry calls for higher productive machines. In the field of advanced machine tools, enhanced performance is seldom achieved without greater design complexity, reduced operational flexibility, and higher cost. These drawbacks have installed innovation in India where most research and development efforts focus on incremental improvements to conventional machines. Hexapod actuator is used with octahedral frame called as space frameThe quest for higher productivity and higher precision in the manufacturing industry calls for higher productive machines. In the field of advanced machine tools, enhanced performance is seldom achieved without greater design complexity, reduced operational flexibility, and higher cost. These drawbacks have installed innovation in India where most research and development efforts focus on incremental improvements to conventional machines. Hexapod actuator is used with octahedral frame called as space frame.The quest for higher productivity and higher precision in the manufacturing industry calls for higher productive machines. In the field of advanced machine tools, enhanced performance is seldom achieved without greater design complexity, reduced operational flexibility, and higher cost. These drawbacks have installed innovation in India where most research and development efforts focus on incremental improvements to conventional machines. Hexapod actuator is used with octahedral frame called as space frame.The quest for higher productivity and higher precision in the manufacturing industry calls for higher productive machines. In the field of advanced machine tools, enhanced performance is seldom achieved without greater design complexity, reduced operational flexibility, and higher cost. These drawbacks have installed innovation in India where most research and development efforts focus on incremental improvements to conventional machines. Hexapod actuator is used with octahedral frame called as space frame.
16
K.G.M., De Silva, P.R.Dadigamuwa Eng., and V.R. Jayasekara Mr. "Improving the Productivity of D-Brackets Manufacturing Process." European Journal of Advances in Engineering and Technology 7, no. 8 (2020): 17–20. https://doi.org/10.5281/zenodo.10667433.
Full textAbstract:
<strong>ABSTRACT</strong> <em>Manufacturing of goods in large quantities by using machines and techniques such as the assembly line and division of labour is known as Mass production. D-Brackets manufacturing can be identified as mass production process. D-Bracket is a part of low tension insulator and hardware component. It produces using mild steel. It is used for connecting shackle/Spool insulator to poles and for link fitting applications in 11/33 kv overhead lines.</em> <em>This project was focused on introducing a press machine combining two processes for the manufacturing process of D-Brackets. The press performs double lancing operations, which are shearing and punching on a single stroke of the press. Designing and fabrication of a press machine by combining shearing and punching processes were done. </em> <em>Designing was done using three-dimensional modeling of the components, analyzing stress and displacement on the components. The modeling and structural analysis of the components were carried out on Solid works 2012 and it was found to be acceptable. The design and selection of materials were carried out by following standards of press machine design approach and analysis method. This new machine can replace shearing machine and low capacity punching machine from the manufacturing process. </em> By introducing this double acting machine to the D-Bracket manufacturing process, it was reduced number of labours, manufacturing lead time and cost per D-Bracket. Thereby, considerable improvement of productivity per day of D-bracket manufacturing was achieved.
17
Rasyid, Mohammad Andi, Tedjo Sukmono, and Ribangun Bamban Jakaria. "Predictive Maintenance on Dry 8 Production Machine Line Using Support Vector Machine (SVM)." Jurnal Teknik Industri: Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri 10, no. 2 (2024): 363. http://dx.doi.org/10.24014/jti.v10i2.29802.
Full textAbstract:
Machines are the main element in manufacturing companies, and the role of machine performance is vital in the production process. Downtime problems caused by machine damage can significantly affect company productivity. This research implements the support vector machine (SVM) method for predicting Dry 8 production machine line maintenance, which aims to reduce downtime and increase productivity. The SVM method is known for its high accuracy and low error rate. The evaluation process used four kernel functions: linear, radial basis function (RBF), polynomial and sigmoid. The linear kernel function performed best with 99.8% accuracy, 83% precision, recall, and f1-score. These results show that the SVM method can be a viable solution to improve the efficiency of machine maintenance. Keywords: Confusion Matrix, Machine Learning, Predictive Maintenance, Support Vector Machine
18
Repdhi Febriyan and Bagus Dwi Cahyono. "Pemeliharaan Pada Mesin Moulding Unimat 22 A Di PT. Sejin Lestari Furniture." Jurnal Teknik Mesin, Industri, Elektro dan Informatika 2, no. 1 (2023): 262–74. http://dx.doi.org/10.55606/jtmei.v2i1.1521.
Full textAbstract:
Developments in the industrial world are increasingly rapid, resulting in increased competition in the industrial world, so that industrial companies are competing to improve production efficiency and effectiveness. Especially companies in the manufacturing sector, increasing productivity in a production system is an absolute thing that must be done. One of the main indicators in increasing productivity is the level of rehabilitation of production machines at the company. In measuring how good the rehabilitation of a production machine is, an effective and efficient maintenance maintenance process is needed for the company. Continuous use of the machine will decrease the level of readiness of the machine itself. In an effort to maintain the level of machine readiness so that production results are guaranteed due to continuous use of the machine, regular machine maintenance and maintenance activities are needed which are expected to prolong the condition of production machines so that they are not damaged, in case of machine damage it can disrupt production activities.
19
Nazarenko, Ivan, Victor Nechiporuk, and Vadim Tkachuk. "ASSESSMENT OF THE INFLUENCE OF ROAD EQUIPMENT PERFORMANCE ON THE EFFICIENCY OF ITS USE." Construction Engineering, no. 40 (December 17, 2024): 63–70. https://doi.org/10.32347/tb.2024-40.0306.
Full textAbstract:
The paper assesses the impact of road machinery performance on the efficiency of its use. It is accepted that the main operational parameters of road equipment for analyzing the technical condition and degree of use of machines include productivity, efficiency index, time for the technological process and losses. The influence of productivity on the strategy of machine operation, as one of the main parameters of the roadway arrangement process, is considered provided that road machines have not only different productivity, but also different rates of its change during operation. The analysis of the given dependencies and the given conditions for changing productivity has shown the impact of increasing and decreasing the rate of productivity decline on the optimal service life of the equipment. These results confirm the extremely important importance of measures aimed at maintaining high machine performance during their operation. The components of machine operating time are analyzed. It was found that the useful or effective working time is an estimated value that is the required time for a given volume of production at reference performance, that is, without loss of productivity and quality. The methods of monitoring the technical condition and the degree of use of road equipment in road construction are analyzed.
20
Ghaffariyan, Mohammad Reza. "A short review on studies on work productivity of mechanical tree planting." Silva Balcanica 22, no. 2 (2021): 25–32. http://dx.doi.org/10.3897/silvabalcanica.22.e64233.
Full textAbstract:
Reforestation can be carried out using natural regeneration or artificial regeneration. There are vari-ous methods for the artificial regeneration, including manual planting, mechanical planting and aerial/or ground seeding. This article aimed to review the current reports on the productivity of mechanical planting to provide a summary of productivity rates for the planting machines. According to the review&rsquo;s results, mechanical planting productivity may vary from 143 to 475 seedlings per productive machine hours depending on the machine type, environment (such as surfaces obstacles and stoniness) and the operator experience. Employing skilled operators and selecting suitable worksites can help increasing the work productivity. Integrating and optimising the whole planting chain, from the nursery to the plant-ing phase, can assist also with reducing the cost and improving the productivity. As mechanical planting machines get more widely adopted in different countries, their overall efficiency will improve over time.
21
Ghaffariyan, Mohammad Reza. "A short review on studies on work productivity of mechanical tree planting." Silva Balcanica 22, no. (2) (2021): 25–32. https://doi.org/10.3897/silvabalcanica.22.e64233.
Full textAbstract:
Reforestation can be carried out using natural regeneration or artificial regeneration. There are vari-ous methods for the artificial regeneration, including manual planting, mechanical planting and aerial/or ground seeding. This article aimed to review the current reports on the productivity of mechanical planting to provide a summary of productivity rates for the planting machines. According to the review’s results, mechanical planting productivity may vary from 143 to 475 seedlings per productive machine hours depending on the machine type, environment (such as surfaces obstacles and stoniness) and the operator experience. Employing skilled operators and selecting suitable worksites can help increasing the work productivity. Integrating and optimising the whole planting chain, from the nursery to the plant-ing phase, can assist also with reducing the cost and improving the productivity. As mechanical planting machines get more widely adopted in different countries, their overall efficiency will improve over time.
22
Singh Amin, Shivdasini, Rakesh Atre, Ankur Vardia, and Boby Sebastian. "Lean machine manufacturing at Munjal Showa limited." International Journal of Productivity and Performance Management 63, no. 5 (2014): 644–64. http://dx.doi.org/10.1108/ijppm-06-2013-0120.
Full textAbstract:
Purpose – The global manufacturing industry is becoming more competitive. Munjal Showa, a shock absorber manufacturer in India, is using indigenous development of lean machines by incorporating concepts of lean manufacturing and low-cost automation techniques to increase their competitiveness. This new approach has helped the company to reduce cost of manufacturing and to increase productivity by reducing cycle time and down time. The purpose of this paper is to offer an in depth study of how at Munjal Showa Ltd lean machines are being developed and manufactured. This paper explores how a cumbersome machine was transformed into a lean machine. Design/methodology/approach – This paper explores how a cumbersome machine was transformed into a lean machine. Findings – This new approach has helped the company to reduce cost of manufacturing and to increase productivity by reducing cycle time and down time. Research limitations/implications – The paper discusses the process of converting one cumbersome machine to a lean machine. Practical implications – Creativity before capital. In lean, team brainstorming of ideas and solutions is emphasized instead of spending large sums of money on capital expenditures Social implications – The cockpit model eases pressure of incumbents on the shop floor. Originality/value – The concepts espoused in the paper has increased productivity by 3.45 times and reduced costs.
23
Kyrychenko, Ihor, and Anton Kholodov. "Energy Aspects In Determining The Efficiency Of Earthmoving And Transport Machines." Bulletin of Kharkov National Automobile and Highway University, no. 108 (May 16, 2025): 130. https://doi.org/10.30977/bul.2219-5548.2025.108.0.130.
Full textAbstract:
Abstract. The article deals with the energy aspects of assessing the efficiency of earthmoving and transport machines. Approaches to determining the energy potential of productivity are analyzed. The application of the energy method for assessing the efficiency of machines and their working bodies is substantiated, which allows optimizing the use of energy resources. Problem. The efficiency of earth-moving and transport machines largely depends on energy consumption. Historically, increasing the unit power of machines was considered a direct way to enhance productivity. However, practical experience has shown that without significant changes in the design of working equipment, proportional growth in performance is not achieved. Goal. The goal of this study is to develop criteria for assessing the efficiency of construction machinery based on energy parameters. The study aims to examine existing analytical approaches, introduce generalized indicators, and validate their effectiveness in practical applications. Methodology. The research employs analytical methods to evaluate energy potential and efficiency indicators of earth-moving and transport machines. The methodology involves defining energy potential performance indicators and their application to industrial tractors and other construction machinery. Results. The study introduces the concept of generalized energy potential productivity, enabling a more accurate assessment of machine efficiency across various operational conditions. It also highlights the advantages of an energy-based approach in comparing machines and evaluating the effectiveness of modular construction systems. Originality. This research contributes to the formation of an energy-based methodology for assessing construction machinery efficiency. The introduction of energy-based evaluation criteria provides an objective framework for optimizing machine design and operational performance. Practical value. The proposed approach allows for a more accurate assessment of construction machine efficiency, enabling better resource allocation, improved machine design, and enhanced energy savings. It can be applied in optimizing machine sets and modular technological systems to ensure maximum productivity with minimal energy consumption.
24
Aldha, Aldha, and Asep Erik Nugraha. "Analisis Kinerja Mesin Welding dengan Menggunakan Metode Overall Equipment Effectiveness (OEE) Pada Divisi Alat Berat di PT. XY." Industrika : Jurnal Ilmiah Teknik Industri 8, no. 3 (2024): 576–86. http://dx.doi.org/10.37090/indstrk.v8i3.1399.
Full textAbstract:
XY is a manufacturing industry engaged in the production of defense equipment. In the production process, machines are one of the important things. As one of the most important aspects in the manufacturing process, machine productivity must always be improved. Therefore, methods are needed to increase productivity in line with fluctuating business needs. Overall Equipment Effectiveness (OEE) is a method that can be used to determine the productivity of a machine. OEE is related to the availability ratio, performance ratio, and quality ratio of the production process. The multiplication of these three factors produces the company's OEE value which will later be compared with the Japan Institute of Plant Maintenance (JIPM) standard OEE value. Research was carried out on welding machines at PT. XY. The machine is used to make bumpers. Based on calculations, the welding machine obtained an availability ratio (83%), quality ratio (100%) and performance efficiency (87%). So, if the three are multiplied, we get an OEE value of 72%, it can be seen that the OEE value is still below the global standard of 85%. Keywords: Availability Ratio, Overall Equipment Effectiveness (OEE), Performance Ratio, Quality Ratio, Welding Machine
25
Kuznetsov, Alexander P., and Hans-Joachim Koriath. "Energy - Information Regularities of Increasing Productivity in Metalworking Machine Tools." EPJ Web of Conferences 224 (2019): 05008. http://dx.doi.org/10.1051/epjconf/201922405008.
Full textAbstract:
Increasing productivity by higher cutting speed and achieving high precision of machined products at the same time is an important trend in the development of manufacturing technologies and metalworking machine tools. If the traditional method of exchangeable components in assemblies will lead to inefficient precise processes, the product costs will increase. The proposed energy-informational model considers a procedural system establishing the ratio of the cutting speed and the speed of physical processes in the machine tools. The energetic limit for the attainability of associated processes describes the allowable speed of materials processing by the machine tools. Stiffness of machine tool structures for highest precision manufacturing becomes comparable to work piece geometrical accuracy and manufacturing process tolerances. This paper gives several examples for admissible limits of increased productivity by increased process speeds in various manufacturing technologies for both traditional cutting and innovative methods.
26
Gopalakrishnan, Maheshwaran, Anders Skoogh, Antti Salonen, and Martin Asp. "Machine criticality assessment for productivity improvement." International Journal of Productivity and Performance Management 68, no. 5 (2019): 858–78. http://dx.doi.org/10.1108/ijppm-03-2018-0091.
Full textAbstract:
Purpose The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity. Design/methodology/approach An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety. Findings The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization. Originality/value Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities.
27
Leech, David P., and John T. Scott. "INTELLIGENT MACHINE TECHNOLOGY AND PRODUCTIVITY GROWTH." Economics of Innovation and New Technology 17, no. 7-8 (2008): 677–87. http://dx.doi.org/10.1080/10438590701785637.
Full text
28
Florentin, H. E., and V. K. Omachonu. "Computer applications in machine productivity measurement." Computers & Industrial Engineering 17, no. 1-4 (1989): 170–74. http://dx.doi.org/10.1016/0360-8352(89)90056-9.
Full text
29
Gavali, Pankaj B., Sujit S. Patil, Nilesh V. Sabnis, Nilesh S. Desai, and H. T. Shinde. "Modeling and Analysis of Twin Spindle Twin Turret Machine." Journal of Advancement in Machines 7, no. 1 (2022): 1–13. http://dx.doi.org/10.46610/joam.2022.v07i01.001.
Full textAbstract:
In the industrial industry, Special Purpose Machines (SPM) play a critical role in increasing productivity. Drilling and riveting activities are done on different machines in the majority of industrial processes, resulting in inefficient productivity. Drilling and riveting had hitherto been thought of as two separate procedures. To increase production, this study attempts to integrate two spindles and two turrets on a single machine. Work components are drilled on a drilling spindle and subsequently cut on a turret in this special purpose machine. Because the spindle shaft, ball screw, and slider base employed in this machine are crucial elements, static and modal analysis is performed using the Finite Element Analysis tool to determine stress distribution and natural frequency.
30
Ihor, Pimonov, Mykhailo Tkachenko, Yefymenko Andrii, Penkina Nalia, and Saliy Yuriy. "IMPROVING THE QUALITY OF CONSTRUCTION AND ROAD EQUIPMENT THROUGH THE USE OF MACHINE CONTROL." Annali d'Italia 64 (February 27, 2025): 75–77. https://doi.org/10.5281/zenodo.14937561.
Full textAbstract:
The use of machine monitoring in modern mobile machines is increasingly common on individual machines and in machine sets. Timely monitoring of parameters helps to keep the machine in optimum condition, extend its service life and minimise downtime. The use of automated monitoring and machine control systems greatly simplifies the diagnostic and control process. Machine control significantly improves the quality of hydraulic actuators, making their operation more reliable, efficient and safe. The introduction of such technologies requires an initial investment, but quickly pays for itself through increased equipment life, reduced repair, maintenance and service costs, and increased productivity
31
López-Pereira, Ariana. "Neural Machine Translation and Statistical Machine Translation: Perception and Productivity." Tradumàtica: tecnologies de la traducció, no. 17 (December 30, 2019): 1. http://dx.doi.org/10.5565/rev/tradumatica.235.
Full text
32
Shinde, Prof S. P. "Android Application for Analysis of Productivity of Precision Machine Shop." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 4513–17. http://dx.doi.org/10.22214/ijraset.2022.44336.
Full textAbstract:
Abstract: Overall Equipment Effectiveness (OEE) of a machine plays an important role within the present scenario, where right quality and right delivery at the proper time are the main factors influencing a customer. The aim of this project is to review the effectiveness and implementing of an independent maintenance system during a workshop for enhancing OEE with the assistance of Total Productive Maintenance (TPM) and 5S techniques employing a systematic approach. This has been focused to attenuate the breakdown, increase the performance and quality rate of machines so on improve the effectiveness. During this discussion of research, reviewing of documentation and sequential records and direct observations were used as data collection methods. during this case study, increase during analysis and productivity of machines in terms of OEE by implementing TPM in a workshop are discussed. This research work deals with the aspects of availability, performance and quality which are to calculate the OEE of a machine. The TPM techniques like 5S, preventive maintenance and cleaning were effectively applied on the machine. the ultimate result showed that the OEE improved by 5% in horizontal machining center and by 7% in vertical machining center.
33
Wibowo, Moh Muhyidin Agus, Anggia Kalista, and Hendra Suwardana. "ANALISIS PRODUKTIVITAS BAGIAN PEMBUATAN KALSIUM KARBONAT MENGGUNAKAN METODE MARVIN E. MUNDEL DI PT. “XZ”." Journal Mechanical and Manufacture Technology (JMMT) 3, no. 2 (2022): 108–17. http://dx.doi.org/10.35891/jmmt.v3i2.3367.
Full textAbstract:
During this company PT. “XZ” pay less attention to the efficient use of resources (input) owned both in terms of materials, energy, labor and maintenance of machinery that support the production process, based on the results of surveys and interviews there are some problems that become benchmarks for the background of this research is : first, material: this material is composed of limestone often wet and delay in ordering. Second, electrical energy: This electric energy consists of less efficient electricity usage is the light is often not in the dead time during the day. Third, labor: This workforce consists of less disciplined workforce and less professional workforce. Fourth, machine maintenance: maintenance of this machine consists of less maintenance and old machines. The result of productivity analysis shows that productivity index level of calcium carbonate making section is good. Depreciation productivity index is 105.2, material 107,5, labor 108, energy 102,8, maintenance 150,8, and total productivity 105,1 In addition to increase productivity there are many ways that can be done that raw material should be given cover of asbestos, regular job training, machine scheduling.
34
Ummah, Nur Hidayatul, and Said Salim Dahda. "Analisis Efektifitas Kinerja Mesin Cutting Manual Dan Otomatis Menggunakan Metode OEE (Overall Equipment Effectiveness ) Di PT. XYZ." Jurnal Teknik Industri: Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri 8, no. 2 (2022): 345. http://dx.doi.org/10.24014/jti.v8i2.19765.
Full textAbstract:
Competition in the manufacturing industry is currently getting tougher due to rapid developments from time to time. The use of tools or machines as a supporting factor for the operation is something that cannot be separated in the industrial world. Therefore, engine performance is a factor that must be considered. Over time, machine performance will decline due to age, maintenance and minimal experience of human resources. In improving performance (effectiveness) to obtain productivity, researchers can calculate the level of performance effectiveness of manual and automatic (CNC) cutting machines. By measuring using the OEE (Overall Equipment Effectiveness) method. The steps in measuring the OEE method are carried out by taking into account Availability (A), Performance Efficiency (P) and Product Quality (R). Based on the advantages of OEE, further analysis of the calculation of Six big losses is carried out. Where the Overall Equipment Effectiveness (OEE) value of the Cutting Automatice (CNC) machine is 73.24% while the manual cutting machine is 55.32%. Both machines have not met the ideal OEE performance value of 85%. While the results of the calculation of Six big losses obtained a large value and affect the effectiveness of the two machines to be minimized is the Breakdown loss factor, Setup and Adjustment Loss and Defect Loss Process. So that continuous and periodic improvements are needed to maintain the effectiveness of both machines and increase productivity. Keywords : Machine performance, Overall Equipment Effectiveness (OEE), Six Big Losses, productivity and automatic (CNC) and manual cutting machines.
35
Muhamad Ryan Agustin and Desmira Desmira. "Preventive Maintenance Mesin Filling Sachet Dalam Mengurangi Downtime Dan Menjaga Produktivitas Di PT. Centa Brasindo Abadi." Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika 2, no. 2 (2024): 319–28. http://dx.doi.org/10.61132/jupiter.v2i2.235.
Full textAbstract:
Centa Brasindo Abadi (CBA) is a company operating in the agricultural sector. To maintain and increase productivity, maintenance of production machines is required. Preventive Maintenance (PM) is an approach used in maintaining equipment and machines to prevent unwanted damage or failure. A sachet filling machine is a machine for packaging products that will be distributed in sachet packaging according to the predetermined product weight. Preventive maintenance helps identify potential problems, saves on costly repairs, and keeps equipment in optimal operational condition. The aim of this research is to determine the implementation of preventive maintenance to maintain productivity in an effort to reduce downtime.
36
Andansari, Dita, and Ruspita Sihombing. "Training on the use of corn sheller machine in Kutai Lama Village, Kutai Kartanegara." Community Empowerment 6, no. 9 (2021): 1718–23. http://dx.doi.org/10.31603/ce.5970.
Full textAbstract:
The corn sheller machine used by the Kutai Lama Village farmer group produces corn cobs that are cut or crushed, so it cannot be used as a medium for making mushrooms and worms. To solve this problem, the team developed a corn sheller machine and trained farmer groups to use the product. In this activity, two corn shelling machines were handed over and given training on how to use a corn sheller machine which is equipped with a 'belt cover' as a safety and added with a 'guide tool' so that the corn kernels do not spill. In addition, the machine is proven to increase the productivity of corn shelling activities. When compared with the manual method, the productivity increases to 4800%.
37
Dmytriv, Vasyl, Ihor Dmytriv, Yurij Lavryk, and Ivan Horodeckyy. "Models of adaptation of the milking machines systems." BIO Web of Conferences 10 (2018): 02004. http://dx.doi.org/10.1051/bioconf/20181002004.
Full textAbstract:
Two systems of milking machines were considered - biotechnical and vacuum. Methodology for estimation of efficiency of the "machine-animal" biotechnical system was worked out. The dependences of the efficiency parameters of the technical system operation were analyzed. The KMMO operator load factor of the milking machine was proposed. The factor characterizes the technological process of the machine milking. The analytical dependences were worked out for the simulation of the productivity of milking machines and oscillation of the vacuum-gage pressure. As to the simulation results, when the vacuum pipeline diameter was increased the oscillation of the vacuum-gage pressure decreased. The results of analysis and theoretical researches on technological process of the cow machine milking gave a possibility to define the requirements to the improvement of technological process and technical equipment, which will provide the increase of efficiency of the milking systems. Usage of the developed cyber-physical system of the machine milking of cows will increase the productivity of the milking machine in 1.26…1.85 times. At the vacuum gage pressure oscillation of ΔPvp = 2500 Pa the suction ability of milking machine will be E=4.093 m/s accordingly. The defined index of efficiency of the adapted systems functioning of the milking machine is KBTS2 = 55.3.
38
Nurlaila, Qomarotun, and Muhammad Deni Wahyudin. "Peningkatan Produktivitas Mesin Sanblasting Dengan Mengubah Setting Parameter Pada Mesin." SIGMA TEKNIKA 4, no. 1 (2021): 115–23. http://dx.doi.org/10.33373/sigmateknika.v4i1.3053.
Full textAbstract:
The research was conducted to increase the productivity of the sandblasting machine on the SSIP model at PT. XYZ. The average productivity in March 2017 was 238 pieces / hour, which is below the productivity target set at 400 pieces / hour. Refer to root cause analysis low productivity on the sandblasting machine due to machine settings. The sandblasting machine settings before being changed were turn table parameters 15Hz , rotary gun parameters 50 Hz and pressure parameters 5 bar. By conducting several experiments on parameter combinations, parameter combinations can be obtained that can reduce cycle time and do not affect to product quality. The new sandblasting machine settings are 17 Hz turn table parameters, 60 Hz rotary gun parameters and 6 bar pressure parameters. The cycle time for setting up the new sandblasting machine is 9 seconds, equivalent to a productivity of 400 pieces / hour. So that productivity increases by 68% (from 238 pieces / hour to 400 pieces / hour).
39
Anderson, J. L. "Space Station Productivity from Information Technology." Journal of Engineering for Industry 107, no. 1 (1985): 26–32. http://dx.doi.org/10.1115/1.3185960.
Full textAbstract:
A space station will involve the formation and operation of an assembly of humans and machines with the intent of achieving sustained operation in space for a period of 10–20 years. A major goal of space station technology efforts is to enable both the initial and evolutionary productivity of the space station. Because a space station is expected to be an information-rich system, technologies that improve the acquisition, processing, and interpretation of information will have a high leverage on station productivity. Specific information technology functions and requirements that promote human–machine productivity for a space station are examined.
40
Mallick, Arpit, Subhra Dhara, and Sushant Rath. "Application of machine learning algorithms for prediction of sinter machine productivity." Machine Learning with Applications 6 (December 2021): 100186. http://dx.doi.org/10.1016/j.mlwa.2021.100186.
Full text
41
Raj, Ritik. "Mental Health and Productivity Among Students." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47745.
Full textAbstract:
Abstract— In recent years, the mental health of students has emerged as a critical concern affecting academic performance, motivation, and overall productivity. The pressures of academic workloads, social expectations, and lifestyle choices contribute significantly to students' psychological well-being. This research paper explores the intricate relationship between mental health, lifestyle factors, and productivity among students using machine learning techniques. The primary objective of the study is to uncover patterns and correlations that may inform early intervention strategies and promote healthier academic environments. A comprehensive dataset was collected through surveys, incorporating various attributes such as sleep duration, screen time, physical activity, dietary habits, stress levels, anxiety indicators, study hours, and academic performance. Data preprocessing techniques were applied to clean and normalize the dataset. Several machine learning models, including Decision Trees, Random Forest, Logistic Regression, and Support Vector Machines, were implemented to identify the most significant factors impacting productivity and mental health. The study found strong correlations between mental health conditions such as anxiety and depression and lower levels of academic performance and daily productivity. Lifestyle choices like poor sleep, high screen time, and lack of physical activity were found to be major contributors to mental fatigue and reduced academic efficiency. Feature importance analysis highlighted that mental health scores, sleep patterns, and stress levels were among the most influential predictors of student productivity. The findings underscore the need for targeted mental health interventions and awareness programs within educational institutions. By leveraging machine learning for predictive analysis, this study offers a data-driven approach to understanding student well-being and optimizing academic outcomes. This research contributes to the growing field of educational data science and emphasizes the importance of mental health in academic success.
42
Kosasih, Elsje, Felisia Sutomo, Tanto Kurnia, and Andy Jusuf. "Analisis Produktivitas Sumber Daya dalam Menurunkan Biaya Produksi untuk Meningkatkan Laba Perusahaan." Jurnal Riset Akuntansi dan Keuangan 8, no. 3 (2020): 481–88. https://doi.org/10.17509/jrak.v8i3.22971.
Full textAbstract:
The productivity of a company could be seen from the productivity of the human resources and machines. The research is done in PT. Bina Nusantara Prima (BNP) at Cimahi. PT.BNP produced greige fabric. According the general manager, PT.BNP has 70% machine productivity level, so it is still possible to increase it. The purpose of the research is to find ways to increase productivity of the human resources, increase machine effectiveness, and to analyze how productivity of the human resources and machine effectiveness could help the company to minimalize their production costs and eventually increase their profits. The method used for the research is descriptive analytics. Results obtained from the research are productivity of the human resources shown by the graphic has average score of 80%, while machine productivity shown by Overall Equipment Effectiveness (OEE) has average score of 70.90%. Increasing human resource and machine productivity could prevent increases in production costs while increasing the quantity of goods produced, which eventually leads to higher profit margin. Abstrak. Produktivitas perusahaan dapat diwujudkan melalui peningkatan produktivitas tenaga kerja dan mesin. Penelitian dilakukan pada PT. Bina Nusantara Prima (BNP) yang terletak di Cimahi, yang bergerak dalam bidang pembuatan kain greige dari bahan baku berupa benang. Berdasarkan hasil wawancara dengan general manager perusahaan, PT.BNP saat ini masih memiliki tingkat produktivitas mesin sebesar 70%, sehingga tidak tertutup kemungkinan untuk meningkatkannya. Tujuan dari penelitian yang dilakukan adalah untuk mengetahui cara untuk meningkatkan produktivitas sumber daya manusia, mengetahui cara untuk meningkatkan efektivitas mesin, serta menganalisis bagaimana peran produktivitas tenaga kerja dan efektivitas mesin dalam menurunkan biaya produksi untuk meningkatkan laba perusahaan. Metode penelitian yang digunakan adalah analisis deskriptif. Hasil yang diperoleh berdasarkan kuesioner dari karyawan PT. BNP, yang dituangkan dalam Grafik Radar menunjukkan bahwa produktivitas tenaga kerja memiliki nilai kekuatan rata-rata 80%. Produktivitas mesin yang diukur dengan Overall Equipment Effectiveness menunjukkan nilai rata-rata dalam periode penelitian adalah 70.90%. Dengan peningkatan produktivitas tenaga kerja dan mesin, maka peningkatan biaya-biaya produksi yang dikeluarkan perusahaan dapat ditekan, produk yang dihasilkan dapat meningkat, sehingga dengan demikian laba perusahaanpun akan meningkat.
43
Kondakov, A. I. "PRODUCTIVITY OF MACHINE TOOLS AND PRODUCTION SYSTEMS." Spravochnik. Inzhenernyi zhurnal, no. 277 (April 2020): 52–55. http://dx.doi.org/10.14489/hb.2020.04.pp.052-055.
Full textAbstract:
Productivity is the most important indicator of labor efficiency. Productivity estimates poorly take into account the interaction of production systems equipment and the technological complexity of labor objects. There is proposed an integral assessment of the performance of these systems, which characterizes the effectiveness of the financial expenses of production resources in the manufacture of parts. It is proposed to characterize their technological complexity by multiplying the increase in the labor subject value after technological impact by the part release volume. The proposed assessment can be used in the development of software applications that automate the tasks of analyzing the effectiveness of production systems.
44
Minecci, Catherine M., and Gail Hodge. "Machine-aided indexing: productivity and organizational implications*." Information Services & Use 8, no. 2-4 (1988): 133–38. http://dx.doi.org/10.3233/isu-1988-82-414.
Full text
45
Kondakov, A. I. "PRODUCTIVITY OF MACHINE TOOLS AND PRODUCTION SYSTEMS." Spravochnik. Inzhenernyi zhurnal, no. 277 (April 2020): 52–55. http://dx.doi.org/10.14489/hb.2020.04.pp.052-055.
Full textAbstract:
Productivity is the most important indicator of labor efficiency. Productivity estimates poorly take into account the interaction of production systems equipment and the technological complexity of labor objects. There is proposed an integral assessment of the performance of these systems, which characterizes the effectiveness of the financial expenses of production resources in the manufacture of parts. It is proposed to characterize their technological complexity by multiplying the increase in the labor subject value after technological impact by the part release volume. The proposed assessment can be used in the development of software applications that automate the tasks of analyzing the effectiveness of production systems.
46
NAKANISHI, Kenichi. "0810 Development of High productivity multitasking machine." Proceedings of Conference of Hokuriku-Shinetsu Branch 2012.49 (2012): 081001–2. http://dx.doi.org/10.1299/jsmehs.2012.49.081001.
Full text
47
Simpson, Leigh. "Machine vision improves productivity in many ways." Assembly Automation 23, no. 3 (2003): 243–48. http://dx.doi.org/10.1108/01445150310698427.
Full text
48
V.K., Kalichkin. "Machine learning in predicting crop rotation productivity." Agricultural Engineering, no. 1 (2025): 41–52. https://doi.org/10.26897/2687-1149-2025-1-41-52.
Full textAbstract:
Crop rotation contributes to maintaining sustainable farming systems. The application of machine learning will enable more efficient design and prediction of crop rotation productivity. Traditional data processing methods do not meet the requirements of intelligent farming. To evaluate the application of machine learning, models for predicting crop rotation productivity were built based on six algorithms: decision tree (CART), random forest (RF), bootstrap aggregating (Bagging), Gradient Boosting, extreme gradient boosting (XGBoost), and artificial neural network (ANN). The study used time series data on the productivity of nine types of crop rotations at three levels of technogenic inputs, obtained in the forest-steppe of the Ob region in Novosibirsk Oblast by the Siberian Research Institute of Agriculture and Chemicalization of Agriculture of the SFSCA RAS during 1999-2019. As an additional predictor, the model included an atmospheric moisture indicator in the form of the Standardized Precipitation Index (SPI), calculated as the average atmospheric moisture indicator for May-July over the rotation of each analyzed crop rotation. Models describing crop rotation productivity based on ANN, Gradient Boosting, and XGBoost algorithms were characterized by the highest predictive abilities depending on the prevailing atmospheric moisture conditions and the level of cultivation technology intensification (R2 = 0.90…0.93). Comparative analysisshowed that the model based on extreme gradient boosting demonstratesthe best performance with a determination coefficient (R2 ) of 0.93, root mean square error (RMSE) of 2.34, and mean absolute error (MAE) of 1.81. The possibility of applying machine learning methods as an effective tool for predicting crop rotation productivity has been demonstrated.
49
Kristinawati, Eti. "Penentuan Interval Perawatan Mesin Produksi Untuk Meningkatkan Availability Melalui Analisis Keandalan." Jurnal Teknik Industri 2, no. 1 (2010): 36. http://dx.doi.org/10.22219/jtiumm.vol2.no1.36-46.
Full textAbstract:
Productivity in a production system is ar important problem and having many factors influence it such as machine condition. With getting machine order, the realibility value is also going to decrease so that machine component will get trouble that will decrease the machine productivity indirectly.
50
Saxena, Surbhi, Anant Deogaonkar, Rupesh Pais, and Reshma Pais. "Workplace Productivity Through Employee Sentiment Analysis Using Machine Learning." International Journal of Professional Business Review 8, no. 4 (2023): e01216. http://dx.doi.org/10.26668/businessreview/2023.v8i4.1216.
Full textAbstract:
Purpose: The objective of this study was to analyze workplace productivity through employee sentiment analysis using machine learning. Theoretical framework: A lot of literature is already published on employee productivity and sentiment analysis as a tool, but the study here is intended to address the issues in employee productivity post-COVID’19. Design/methodology/approach: The authors have studied the relationship between sentiments and workplace productivity post-COVID- 19. Sentiments were captured from the text inputs given by seventy-two survey respondents from a mid-sized consultancy firm and correlated against the productivity scores. A machine learning model was developed using Python to calculate the sentiment score. Findings: 98.6% of the respondents had a high productivity score, whereas 88.9% showed positive sentiments. The majority of the responses showed a positive correlation between positive sentiments and high productivity levels. Research, Practical and Social Implications: The study paves way for identification of action plan for productivity enhancement through sentiment analysis. Originality/Value: No previous work on employee productivity using sentiment analysis is done till now.