DEVELOPMENT OF A QUALITY IMPROVEMENT OPTIMIZATION MODEL IN MULTI-STAGE PRODUCTION SYSTEMS
Almost all production processes produce variance around the desired target value of quality characteristic. This variance affects the product quality level. Accordingly variance reduction need to be done as the main goal of quality improvement programs. However effort to improve quality of each prod...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/12394 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Almost all production processes produce variance around the desired target value of quality characteristic. This variance affects the product quality level. Accordingly variance reduction need to be done as the main goal of quality improvement programs. However effort to improve quality of each product unit must take into account to improvement costs.<p> This research focus on the development of an optimization model for quality improvement in multi-stage production systems using a non linear programming model by selecting alternatives process and determining unit of production of each stage to maximize the difference between total income and total cost. Total cost includes manufacturing cost, quality loss cost, rework and scrap cost, and quality improvement implementation cost. This optimization model is implemented in make-to-order manufacturer that produces crimper (a parts of joining plastic package in packaging machine) which consist of five main stage production processes. The optimal solution resulted from the optimization shows that new process with the lower rework and scrap rate are selected to improve stage one and three. Meanwhile current process in the production systems are selected to maintain existing processes in stage two, four and five. Solution report generated from the optimization shows that the addition of new value in the constraints will not generate a new optimal solutions that have a better objective function, with the exception of addition of delivery time. Sensitivity analysis shows that the optimal solution is not sensitive if little changes occur in the constraints scenario. Thus, adding the value constraint on the quality specification, stage capacity, and quality improvement budget will not improve the objective function. <br />
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