A modeling approach for performance measurement and improvement in process manufacturing: An application

A MODELING APPROACH FOR PERFORMANCE MEASUREMENT ANDIMPROVEMENT IN PROCESS MANUFACTURING: AN APPLICATIONGökhan AKYÜZIn today?s competitive world, firms could continue their existence by continuouslyimproving themselves. Realizing the improvement could be possible by improving theperformance based on monitoring firms? performance as to past periods and/or sector?ssituation. Firms? point of view for performance has changed in parallel with the changes incompetition factors and management insights, and evolved to more extended structurewhich covers the whole enterprise and formed as a management system conception. Alongwith this new conception, performance management system had undertaken an importantrole in structuring and successfully implementing the strategic plans and the qualitymanagement system operations. Because, it has been an important factor that acceleratesthe system by its measurements and analyses towards the aim of realizing the continuousimprovement.The main purpose of this study is improving the performance of process manufacturing.In this purpose, a modeling approach has performed for measuring and improving theperformance of mirror manufacturing process of a factory that operates in the processindustry. Initially the structural model of the process has developed. This model measuresthe effects of process characteristics in manufacturing processes on final productcharacteristics, and focuses on improving the performance of final product characteristics.The model has characteristics of simultaneous equations. There are eighteen variables andthirteen equations along with the external and previously determined variables in themodel. Three of the equations define final product characteristics, and the remaining ten ofthem define process characteristics. Equations are linear and their coefficients havepredicted by ordinary least squares method.The model predicts the values of process characteristics gradually according to valuesof external and previously determined variables, and finally achieves the predicted valuesof the final product characteristics. The model has run by systematic and stochasticsimulation applications. By evaluating the results that obtained from these applications,new tolerance intervals have determined for process characteristics which improves theperformance of the final product characteristics. These intervals that are lower than presentsituation have improved the performance and increased the process capabilities toacceptable levels.