A linear programming approach to quaity improvement project and product mix selection under inspection error and rework

Thesis Type: Postgraduate

Institution Of The Thesis: Middle East Technical University, Faculty of Engineering, Department of Industrial Engineering, Turkey

Approval Date: 2006

Thesis Language: English

Student: Nedret Şarbak



In this study, the effect of inspection error on the product mix and quality projects selection in a manufacturing environment where rework and inspection errors exist is examined. It is assumed that the products (items) for which rework is necessary are reprocessed at a separate work center and 100% inspection is performed for the products both after rework and processing operations. Markov chain approach is used to compute yield and rework rates. In addition, nominal-the-best type of a quality loss function is used in computing quality loss due to products shipped to the customers. A linear programming (LP) model is developed to support the product mix and quality improvement project selection decisions. The use of LP model is demonstrated on an example problem. The results obtained under different experimental conditions are compared with solutions of a naive QI project selection method, improving the least capable process. The analysis shows that developed LP model is relatively better than process capability approach. Besides, according to the results obtained under different experimental conditions, the factors that have significant effect on throughput and QI project selection are being determined.