WESTINGHOUSE TEMPO DERECELENDİRME SİSTEMİNE BULANIK MANTIK İLE YENİ BİR YAKLAŞIM

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.

A NEW APPROACH TO WESTINGHOUSE TEMPO RATING SYSTEM WITH FUZZY LOGIC

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.

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