Cyber-physical production systems (CPPS) represent a relevant aspect related to industry 4.0 and the advances promoted by the digitization and use of artificial intelligence in the production environment in the search for the development of smart factories. This study aims to assess the maturity level of cyber-physical production system (CPPS) within manufacturing industries in the Amazon. The research uses a quali-quantitative approach to analyze the problem by conducting exploratory case studies (indepth case) and the research framework used aimed to evaluate and measure the CPPS within three manufacturing industries in the Amazon (n = 3) to measure their maturity. Findings reveal a positive relationship between the type of production system adopted by the company, the level of automation, and the maturity of the CPPS. The proposed methodology can assist other companies in the development of the technological strategy, supporting the digital transformation process in order to obtain competitive advantage. The study contributes by addressing the topic of cyber-physical production systems from the point of view of operations management and strategy.
{"title":"Cyber-physical production system assessment within the manufacturing industries in the Amazon","authors":"Moises Andrade Coelho, Franciel Andrade de Oliveira, Lindara Hage Dessimoni, Nicole Sales Libório","doi":"10.4995/ijpme.2022.16130","DOIUrl":"https://doi.org/10.4995/ijpme.2022.16130","url":null,"abstract":"Cyber-physical production systems (CPPS) represent a relevant aspect related to industry 4.0 and the advances promoted by the digitization and use of artificial intelligence in the production environment in the search for the development of smart factories. This study aims to assess the maturity level of cyber-physical production system (CPPS) within manufacturing industries in the Amazon. The research uses a quali-quantitative approach to analyze the problem by conducting exploratory case studies (indepth case) and the research framework used aimed to evaluate and measure the CPPS within three manufacturing industries in the Amazon (n = 3) to measure their maturity. Findings reveal a positive relationship between the type of production system adopted by the company, the level of automation, and the maturity of the CPPS. The proposed methodology can assist other companies in the development of the technological strategy, supporting the digital transformation process in order to obtain competitive advantage. The study contributes by addressing the topic of cyber-physical production systems from the point of view of operations management and strategy.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42544438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.4995/ijpme.2022.16617
J. Deuse, Nikolai West, Marius Syberg
Industrial Engineering, through its role as design, planning and organizational body of the industrial production, has been crucial for the success of manufacturing companies for decades. The potential, expected over the course of Industry 4.0 and through the application of Data Analytic tools and methods, requires a coupling to established methods. This creates the necessity to extend the traditional job description of Industrial Engineering by new tools from the field of Data Analytics, namely Industrial Data Science. Originating from the historic pioneers of Industrial Engineering, it is evident that the basic principles will remain valuable. However, further development in view of the data analytic possibilities is already taking place. This paper reviews the origins of Industrial Engineering with reference to four pioneers, draws a connection to current day usage, and considers possibilities for future applications of Industrial Data Science.
{"title":"Rediscovering scientific management. The evolution from industrial engineering to industrial data science","authors":"J. Deuse, Nikolai West, Marius Syberg","doi":"10.4995/ijpme.2022.16617","DOIUrl":"https://doi.org/10.4995/ijpme.2022.16617","url":null,"abstract":"Industrial Engineering, through its role as design, planning and organizational body of the industrial production, has been crucial for the success of manufacturing companies for decades. The potential, expected over the course of Industry 4.0 and through the application of Data Analytic tools and methods, requires a coupling to established methods. This creates the necessity to extend the traditional job description of Industrial Engineering by new tools from the field of Data Analytics, namely Industrial Data Science. Originating from the historic pioneers of Industrial Engineering, it is evident that the basic principles will remain valuable. However, further development in view of the data analytic possibilities is already taking place. This paper reviews the origins of Industrial Engineering with reference to four pioneers, draws a connection to current day usage, and considers possibilities for future applications of Industrial Data Science.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43255426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.4995/ijpme.2022.16736
H. Al-Khazraji
Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WAP is an NP-hard combinatorial optimization problem. Due to its importance, several algorithms have been developed to solve it. In this paper, it is considered that a manager is required to provide a training course to his workers in order to improve their level of skill or experience to have a sustainable competitive advantage in the industry. The training cost of each worker to perform a particular job is different. The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. MATLAB Software is used to perform the simulation of the two proposed methods into WAP. The computational results for a set of randomly generated problems of various sizes show that the FPA is able to find good quality solutions.
{"title":"Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem","authors":"H. Al-Khazraji","doi":"10.4995/ijpme.2022.16736","DOIUrl":"https://doi.org/10.4995/ijpme.2022.16736","url":null,"abstract":"Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WAP is an NP-hard combinatorial optimization problem. Due to its importance, several algorithms have been developed to solve it. In this paper, it is considered that a manager is required to provide a training course to his workers in order to improve their level of skill or experience to have a sustainable competitive advantage in the industry. The training cost of each worker to perform a particular job is different. The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. MATLAB Software is used to perform the simulation of the two proposed methods into WAP. The computational results for a set of randomly generated problems of various sizes show that the FPA is able to find good quality solutions.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41317542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.4995/ijpme.2022.16666
Alicia Olivares-Gil, Adrián Arnaiz-Rodríguez, José Miguel Ramírez-Sanz, José Luis Garrido-Labrador, Virginia Ahedo, C. García-Osorio, J. I. Santos, José Manuel Galán
Understanding the scientific and social structure of a discipline is a fundamental aspect for scientific evaluation processes, identifying trends and niches, and balancing the trade-off between exploitation and exploration in research. In the present contribution, the production of doctoral theses is used as a proxy to analyze the scientific structure of the knowledge area of business organization in Spain. To that end, a complex networks approach is selected, and two different networks are built: (i) the social network of co-participation in thesis examining committees and thesis supervision, and (ii) a bipartite network of theses and thesis descriptors. The former has a modular structure that is partially explained by thematic specialization in different subdisciplines. The latter serves to assess the interdisciplinary structure of the discipline, as it enables the characterization of affinity levels between fields, research poles and thematic clusters. Our results have implications for the scientific evaluation and formal definition of related fields.
{"title":"Mapping the scientific structure of organization and management of enterprises using complex networks","authors":"Alicia Olivares-Gil, Adrián Arnaiz-Rodríguez, José Miguel Ramírez-Sanz, José Luis Garrido-Labrador, Virginia Ahedo, C. García-Osorio, J. I. Santos, José Manuel Galán","doi":"10.4995/ijpme.2022.16666","DOIUrl":"https://doi.org/10.4995/ijpme.2022.16666","url":null,"abstract":"Understanding the scientific and social structure of a discipline is a fundamental aspect for scientific evaluation processes, identifying trends and niches, and balancing the trade-off between exploitation and exploration in research. In the present contribution, the production of doctoral theses is used as a proxy to analyze the scientific structure of the knowledge area of business organization in Spain. To that end, a complex networks approach is selected, and two different networks are built: (i) the social network of co-participation in thesis examining committees and thesis supervision, and (ii) a bipartite network of theses and thesis descriptors. The former has a modular structure that is partially explained by thematic specialization in different subdisciplines. The latter serves to assess the interdisciplinary structure of the discipline, as it enables the characterization of affinity levels between fields, research poles and thematic clusters. Our results have implications for the scientific evaluation and formal definition of related fields.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42156058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.4995/ijpme.2022.15894
Jia Yuik Chong, P. Perumal
The adoption of lean manufacturing (LM) in small and medium-sized enterprises (SMEs) is not as vigorous as in large organizations. This purpose of this study is to assess the maturity level of LM implementation in the machinery and equipment (ME) SMEs. The close-ended survey questionnaire method was adopted in three Malaysian manufacturing ME SMEs, and data was collected for the descriptive analysis. The findings showed that these case companies are generally at a low-to-moderate level in terms of LM understanding. Meanwhile, the extent of LM implementation and the success level is still moderate. The proposed LM conceptual model provides valuable perspectives and establishes a holistic understanding of the phenomena in LM maturity status for ME SMEs. The proper synchronization of LM understanding, implementation, and success are vital to building the strong LM maturity foundation for lean organizational transformation. It serves as useful guidance and strategic framework to other companies in dealing with the operational excellence challenges. The significance of this study will help ME SMEs to identify their current position and promote progress in the lean application journey. This will benefit the management team and lean practitioners in decision-making and enhance tactics to attain a higher level of success.
{"title":"Conceptual model for assessing the lean manufacturing implementation maturity level in machinery and equipment of small and medium-sized enterprises","authors":"Jia Yuik Chong, P. Perumal","doi":"10.4995/ijpme.2022.15894","DOIUrl":"https://doi.org/10.4995/ijpme.2022.15894","url":null,"abstract":"The adoption of lean manufacturing (LM) in small and medium-sized enterprises (SMEs) is not as vigorous as in large organizations. This purpose of this study is to assess the maturity level of LM implementation in the machinery and equipment (ME) SMEs. The close-ended survey questionnaire method was adopted in three Malaysian manufacturing ME SMEs, and data was collected for the descriptive analysis. The findings showed that these case companies are generally at a low-to-moderate level in terms of LM understanding. Meanwhile, the extent of LM implementation and the success level is still moderate. The proposed LM conceptual model provides valuable perspectives and establishes a holistic understanding of the phenomena in LM maturity status for ME SMEs. The proper synchronization of LM understanding, implementation, and success are vital to building the strong LM maturity foundation for lean organizational transformation. It serves as useful guidance and strategic framework to other companies in dealing with the operational excellence challenges. The significance of this study will help ME SMEs to identify their current position and promote progress in the lean application journey. This will benefit the management team and lean practitioners in decision-making and enhance tactics to attain a higher level of success.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48378268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.4995/ijpme.2022.16021
M. Komarudin, Rosalendro Eddy Nugroho
This study aims to analyze the failure factors of PT. XYZ in 2018 – 2020 in terms of time, cost, labor, Health, Safety, and Environment (HSE), and quality based on the Success Project Factor (SPF). It includes 183 projects with the Non-Probability Sampling technique. The researcher uses fishbone and Pareto to identify problems. The results showed Schedule Performance Index (SPI) 1 indicated the project is in the late category, the Cost Performance Index (CPI) 1 indicated cost overrun, Safety Performance Index (SFPI) 0 indicated the K3 target could not be reached, the Client Satisfaction Index (CSI) = 34.03, indicated that it is in the dissatisfied category, then Productivity Coefficient Plan Realization, it meant the workforce was less productive. After the analysis of fishbone and Pareto, the data show that the highest cause was 13% due to lack of supervision, project cost aspects were 13% due to delays, HSE project aspect were 13% due to no K3 process before work begins, the quality aspect was 17% due to no training, and the labor aspect was 17% due to poor worker discipline.
{"title":"Analysis of the project success factor through time, cost, labour, health, safety, environment and quality aspects at PT XYZ","authors":"M. Komarudin, Rosalendro Eddy Nugroho","doi":"10.4995/ijpme.2022.16021","DOIUrl":"https://doi.org/10.4995/ijpme.2022.16021","url":null,"abstract":"This study aims to analyze the failure factors of PT. XYZ in 2018 – 2020 in terms of time, cost, labor, Health, Safety, and Environment (HSE), and quality based on the Success Project Factor (SPF). It includes 183 projects with the Non-Probability Sampling technique. The researcher uses fishbone and Pareto to identify problems. The results showed Schedule Performance Index (SPI) 1 indicated the project is in the late category, the Cost Performance Index (CPI) 1 indicated cost overrun, Safety Performance Index (SFPI) 0 indicated the K3 target could not be reached, the Client Satisfaction Index (CSI) = 34.03, indicated that it is in the dissatisfied category, then Productivity Coefficient Plan Realization, it meant the workforce was less productive. After the analysis of fishbone and Pareto, the data show that the highest cause was 13% due to lack of supervision, project cost aspects were 13% due to delays, HSE project aspect were 13% due to no K3 process before work begins, the quality aspect was 17% due to no training, and the labor aspect was 17% due to poor worker discipline.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45426099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-30DOI: 10.4995/IJPME.2021.16084
Mohammad Zakaraia, H. Zaher, Naglaa Ragaa
The U-shaped assembly lines help to have more flexibility than the straight assembly lines, where the operators can perform tasks in both sides of the line, the entrance and the exit sides. Having more than one operator in any station of the line can reduce the line length and thereby affects the number of produced products. This paper combines the U-shaped assembly line balancing problem with the multi-manned assembly line balancing problem in one problem. In addition, the processing times of the tasks are considered as stochastic, where they are represented as random variables with known means and variances. The problem is formulated as a mixed-integer linear programming and the cycle time constraints are formulated as chance-constraints. The proposed algorithm for solving the problem is a differential evolution algorithm. The parameter of the algorithm is optimized using experimental design and the computational results are done on 71 adapted problems selected from well-known benchmarks.
{"title":"Solving stochastic multi-manned U-shaped assembly line balancing problem using differential evolution algorithm","authors":"Mohammad Zakaraia, H. Zaher, Naglaa Ragaa","doi":"10.4995/IJPME.2021.16084","DOIUrl":"https://doi.org/10.4995/IJPME.2021.16084","url":null,"abstract":"The U-shaped assembly lines help to have more flexibility than the straight assembly lines, where the operators can perform tasks in both sides of the line, the entrance and the exit sides. Having more than one operator in any station of the line can reduce the line length and thereby affects the number of produced products. This paper combines the U-shaped assembly line balancing problem with the multi-manned assembly line balancing problem in one problem. In addition, the processing times of the tasks are considered as stochastic, where they are represented as random variables with known means and variances. The problem is formulated as a mixed-integer linear programming and the cycle time constraints are formulated as chance-constraints. The proposed algorithm for solving the problem is a differential evolution algorithm. The parameter of the algorithm is optimized using experimental design and the computational results are done on 71 adapted problems selected from well-known benchmarks.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44497768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-28DOI: 10.4995/ijpme.2021.14985
Emrae Jung
The objective of this study is to develop a car assembly sequence that is mutually agreed between car manufacturers and Tier-1 module suppliers such that overall modular supply chain efficiency is improved. In the literature so far, only constraints of car manufacturers have been considered in the car sequencing problem. However, an assembly sequence from car manufacturer imposes a module assembly sequence on Tier-1 module suppliers since their assembly activities are synchronous and in sequence with assembly line of that car manufacturer. An imposed assembly sequence defines a certain demand rate for Tier-1 module suppliers and has significant impacts on operational cost of these suppliers which ultimately affects the overall modular supply chain efficiency. In this paper, a heuristic approach has been introduced to generate a supplier cognizant car sequence which does not only provide better operational conditions for Tier-1 module suppliers, but also satisfies constraints of the car manufacturer.
{"title":"Integrating Tier-1 module suppliers in car sequencing problem","authors":"Emrae Jung","doi":"10.4995/ijpme.2021.14985","DOIUrl":"https://doi.org/10.4995/ijpme.2021.14985","url":null,"abstract":"The objective of this study is to develop a car assembly sequence that is mutually agreed between car manufacturers and Tier-1 module suppliers such that overall modular supply chain efficiency is improved. In the literature so far, only constraints of car manufacturers have been considered in the car sequencing problem. However, an assembly sequence from car manufacturer imposes a module assembly sequence on Tier-1 module suppliers since their assembly activities are synchronous and in sequence with assembly line of that car manufacturer. An imposed assembly sequence defines a certain demand rate for Tier-1 module suppliers and has significant impacts on operational cost of these suppliers which ultimately affects the overall modular supply chain efficiency. In this paper, a heuristic approach has been introduced to generate a supplier cognizant car sequence which does not only provide better operational conditions for Tier-1 module suppliers, but also satisfies constraints of the car manufacturer.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45945565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-31DOI: 10.4995/ijpme.2020.11953
Ö. Yılmaz, Ö. Demirel, S. Zaim, S. Sevim
The philosophy of production without waste is the fundamental belief behind lean manufacturing that should be adopted by enterprises. One of the waste elimination methods is assembly line balancing for lean manufacturing, i.e. Yamazumi. The assembly line balancing is to assign tasks to the workstations by minimizing the number of workstations to the required values. There should be no workstation with the excessively high or low workload, and all workstations must ideally work with balanced workloads. Accordingly, in this study, the axiomatic design method is applied for assembly line balancing in order to achieve maximum output with the installed capacity. In order to achieve this aim, all improvement opportunities are defined and utilized as an output of the study. Computational results indicate that the proposed method is effective to reduce operators’ idle time by 12%, imbalance workload between workstations by 38%, and the total number of workers by 12%. As a result of these improvements, the production volume is increased by 23%.
{"title":"Assembly line balancing by using axiomatic design principles: An application from cooler manufacturing industry","authors":"Ö. Yılmaz, Ö. Demirel, S. Zaim, S. Sevim","doi":"10.4995/ijpme.2020.11953","DOIUrl":"https://doi.org/10.4995/ijpme.2020.11953","url":null,"abstract":"The philosophy of production without waste is the fundamental belief behind lean manufacturing that should be adopted by enterprises. One of the waste elimination methods is assembly line balancing for lean manufacturing, i.e. Yamazumi. The assembly line balancing is to assign tasks to the workstations by minimizing the number of workstations to the required values. There should be no workstation with the excessively high or low workload, and all workstations must ideally work with balanced workloads. Accordingly, in this study, the axiomatic design method is applied for assembly line balancing in order to achieve maximum output with the installed capacity. In order to achieve this aim, all improvement opportunities are defined and utilized as an output of the study. Computational results indicate that the proposed method is effective to reduce operators’ idle time by 12%, imbalance workload between workstations by 38%, and the total number of workers by 12%. As a result of these improvements, the production volume is increased by 23%.","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43808812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-31DOI: 10.4995/IJPME.2019.12035
Sugoi Uriarte Marcos, R. Rodríguez-Rodríguez, Maier Uriarte Marcos, J. Alfaro-Saíz
Performance measurement in Judo usually focuses on some KPIs whose values indicate the final performance of the athlete. This paper deals with firstly identifying which these main KPIs in Judo are. Once this is done, the KPIs are classified into four different clusters: Physical training, specific training, Psychology and Lifestyle. Then, it proposes the multi-criteria decision aim technique of Analytic Network Process as the most indicate one to link not only the impact of the Judo KPIs with the achievement of the judoka’s strategic objectives but also to identify both the relative and the global importance of each of these KPIs.
{"title":"Performance measurement in Judo: main KPIs, cluster categorization and an ANP-based approach","authors":"Sugoi Uriarte Marcos, R. Rodríguez-Rodríguez, Maier Uriarte Marcos, J. Alfaro-Saíz","doi":"10.4995/IJPME.2019.12035","DOIUrl":"https://doi.org/10.4995/IJPME.2019.12035","url":null,"abstract":"Performance measurement in Judo usually focuses on some KPIs whose values indicate the final performance of the athlete. This paper deals with firstly identifying which these main KPIs in Judo are. Once this is done, the KPIs are classified into four different clusters: Physical training, specific training, Psychology and Lifestyle. Then, it proposes the multi-criteria decision aim technique of Analytic Network Process as the most indicate one to link not only the impact of the Judo KPIs with the achievement of the judoka’s strategic objectives but also to identify both the relative and the global importance of each of these KPIs. ","PeriodicalId":41823,"journal":{"name":"International Journal of Production Management and Engineering","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45779281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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