Abstract
Manufacturing quality cost optimization is a priority in any manufacturing sector due to quality issues impacting companies’ reputations and has financial consequences. Quality costs are composed of tangible and intangible costs, however, only tangible costs used to be analyzed because there is no suitable methodology for measuring intangible costs. In this context, an innovative decision support system is developed with an empirical base, applying Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Lean methodology to reduce all quality costs in an efficient way. In quality departments, perceptions, thoughts, and judgments (intangible costs) are not measured and controlled. This study develops an innovative methodology that allows to address this issue in an effective way. Another major innovation is the application of both multi-criteria methodologies to obtain the best combined result for decision making and the optimization of this result, developing an effort–impact matrix based on Lean manufacturing methodology. This system speeds up the decision-making process and assures its efficiency for quality department applications. Moreover, this decision support system may be applicable to any manufacturing sector.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
6 articles.
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