Abstract
When calculating the production cost of a product, two basic items are taken into consideration. The first is the material cost and the second is the labor cost. Material costs can be calculated very clearly due to the lack of personal judgment. Because the amount of material used for the production of that product is certain. However, the calculation of labor costs may not always be as simple and precise. The amount of product produced per unit time directly affects product costs. Therefore, to calculate the costs correctly, the number of parts produced per unit time must be calculated correctly. At this point, production times per product gain importance. It is not considered sufficient to use the values on the chronometer when calculating the production times of parts or products. Standard production times are calculated by adding performance and tolerance values to the chronometer values. Worker performance may vary from person to person. Performance varies depending on worker ability, effort, consistency and working environment. This difference in performance becomes very important in manual production processes. In automatic production processes, this difference is especially important when disassembling and assembly processes of the parts to the automatic machines. Tempo rating systems have been proposed to standardize worker performances and to minimize the negative effects of performance differences between individuals. The Classical Westinghouse Method is one of the common use tempo rating system. In the CWM, the performance of the worker is calculated by using skill, effort, environmental conditions, and consistency values. Evaluations of these four criteria are obtained by observing by decision-makers. In this study, the fuzzy rule-based Westinghouse method was developed because decision-makers use linguistic expressions to evaluate worker performance. The proposed Fuzzy Westinghouse Method is applied to a part of the company that produces automatic cutting machines in order to prove its validity. As a result of the study, it was determined that the proposed model produces more sensitive values.
Keywords
Tempo rating system Classical Westinghouse method normal time fuzzy logic Fuzzy Westinghouse method
Thanks
This paper is an extension of a conference paper entitled “Fuzzy Westinghouse Tempo Rating System: A Case Study in an Automotive Company” that published in Conference Proceedings of “10th International Symposium on Intelligent Manufacturing and Service Systems (IMSS’19)”.
References
- Barnes, R. M. (1980). Motion and Time Study Design and Measurement of Work. United States of America: John Wiley & Sons.
- Bircan, H., & İskender, G. (2005). Application of Time Study among The Work Measurement Techniques on Endoscopic Data. Cumhuriyet University Journal of Economics and Administrative Sciences, 6(2), 199–219.
- Cevikcan, E., & Kilic, H. S. (2016). Tempo rating approach using fuzzy rule based system and westinghouse method for the assessment of normal time. International Journal of Industrial Engineering : Theory Applications and Practice, 23(1), 49–67.
- Cevikcan, E., Kilic, H. S., & Zaim, S. (2012). Westinghouse method oriented fuzzy rule based tempo rating approach. In Proc. Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management, Istanbul, Turkey (pp. 1670-1677).
- Kanawaty, G. (2004). Introduction to Work Study. International Labour Office.
- Lehto, M. R., & Landry, S. J. (2013). Introduction to Human Factors and Ergonomics for Engineers. Taylor & Francis Group, CRC Press.
- Matias, A. C. (2001). Work Measurement: Principles and Techniques. New York, USA: John Wiley & Sons.
- Namazov, M., & Bastürk, O. (2010). DC Motor Position Control Using Fuzzy Proportional-Derivative Controllers With Different Defuzzification Methods. TJFS: Turkish Journal of Fuzzy Systems, 1(1), 36–54.
- Suwittayaruk, P., Goubergen, D. Van, & Lockhart, T. E. (2011). A Tool to Visualize Response Selection and Execution on Pace Rating. In 9th International Industrial Simulation Conference. Venice.
Abstract
When calculating the production cost of a product, two basic items are taken into consideration. The first is the material cost and the second is the labor cost. Material costs can be calculated very clearly due to the lack of personal judgment. Because the amount of material used for the production of that product is certain. However, the calculation of labor costs may not always be as simple and precise. The amount of product produced per unit time directly affects product costs. Therefore, to calculate the costs correctly, the number of parts produced per unit time must be calculated correctly. At this point, production times per product gain importance. It is not considered sufficient to use the values on the chronometer when calculating the production times of parts or products. Standard production times are calculated by adding performance and tolerance values to the chronometer values. Worker performance may vary from person to person. Performance varies depending on worker ability, effort, consistency and working environment. This difference in performance becomes very important in manual production processes. In automatic production processes, this difference is especially important when disassembling and assembly processes of the parts to the automatic machines. Tempo rating systems have been proposed to standardize worker performances and to minimize the negative effects of performance differences between individuals. The Classical Westinghouse Method is one of the common use tempo rating system. In the CWM, the performance of the worker is calculated by using skill, effort, environmental conditions, and consistency values. Evaluations of these four criteria are obtained by observing by decision-makers. In this study, the fuzzy rule-based Westinghouse method was developed because decision-makers use linguistic expressions to evaluate worker performance. The proposed Fuzzy Westinghouse Method is applied to a part of the company that produces automatic cutting machines in order to prove its validity. As a result of the study, it was determined that the proposed model produces more sensitive values.
Keywords
Tempo derecelendirme sistemi Klasik Westinghouse Yöntemi Normal Zaman Bulanık Mantık Bulanık Westinghouse Yöntemi
References
- Barnes, R. M. (1980). Motion and Time Study Design and Measurement of Work. United States of America: John Wiley & Sons.
- Bircan, H., & İskender, G. (2005). Application of Time Study among The Work Measurement Techniques on Endoscopic Data. Cumhuriyet University Journal of Economics and Administrative Sciences, 6(2), 199–219.
- Cevikcan, E., & Kilic, H. S. (2016). Tempo rating approach using fuzzy rule based system and westinghouse method for the assessment of normal time. International Journal of Industrial Engineering : Theory Applications and Practice, 23(1), 49–67.
- Cevikcan, E., Kilic, H. S., & Zaim, S. (2012). Westinghouse method oriented fuzzy rule based tempo rating approach. In Proc. Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management, Istanbul, Turkey (pp. 1670-1677).
- Kanawaty, G. (2004). Introduction to Work Study. International Labour Office.
- Lehto, M. R., & Landry, S. J. (2013). Introduction to Human Factors and Ergonomics for Engineers. Taylor & Francis Group, CRC Press.
- Matias, A. C. (2001). Work Measurement: Principles and Techniques. New York, USA: John Wiley & Sons.
- Namazov, M., & Bastürk, O. (2010). DC Motor Position Control Using Fuzzy Proportional-Derivative Controllers With Different Defuzzification Methods. TJFS: Turkish Journal of Fuzzy Systems, 1(1), 36–54.
- Suwittayaruk, P., Goubergen, D. Van, & Lockhart, T. E. (2011). A Tool to Visualize Response Selection and Execution on Pace Rating. In 9th International Industrial Simulation Conference. Venice.
Details
| Primary Language | English |
|---|---|
| Subjects | Industrial Engineering |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | April 30, 2021 |
| Acceptance Date | February 6, 2021 |
| Published in Issue | Year 2021 Volume: 32 Issue: 1 |
