Where is the best place in the production life cycle to place statistical process control? Applying the Taguchi loss function to the cost of quality
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Authors
Harizavi, Dean Amin
Issue Date
2010
Type
Capstone
Language
en
Keywords
Systems engineering
Alternative Title
Abstract
Statistical Process Control (SPC) applications allow for detection and analysis of nonconformance and variation in the manufacturing processes. Proper positioning of SPC implementation in the production and operations life cycle is crucial in minimizing resource waste. Analyzing various categories of quality costs will help determine the optimal point for SPC placement. Taguchi Loss Function (TLF) is used to account for tangible and non-tangible quality costs and to help derive an original inequality, a mathematical formulation, for the determination of the ideal position of SPC implementation. TLF and its applicability is also investigated and mathematically optimized for use in this study. This work will provide a background of process variation management, SPC implementation, analysis of various quality costs, including pre-, in-, and post-production costs to the manufacturer and post production cost of quality to the customer. Extensive research material is reviewed to identify the costs and how accurate positioning of SPC implementation can reduce the overall cost of production to the manufacturer. The sum of these costs is used to derive a mathematical formula that would help the process designer identify the most-cost effective place for the SPC application along the production line. The resulting equation uses the gain, or the loss reduction as a result of SPC implementation, on one side and an economical average per unit cost, or marginal cost of the SPC system on the other side. Comparing these two derived values, the study allows the decision maker to decide if & where to implement SPC diagnostic applications along the production life cycle. To help better the material presented, this study provides multiple case examples, in addition to a comprehensive and illustrative multivariate, multi-station, production line example in determining an economically viable SPC placement strategy.