Quality control strategy based on quality cost models with uncertain parameters

Abstract

All rights reserved. In manufacturing companies, quality control plans are essential to fulfil quality requirements and can be expressed by quality appraisal and failure costs. However, there are barriers to the determination of quality costs, limiting the ability of companies to establish quality control plans at the lowest cost and consequently becoming more competitive. The paper objective is to develop a framework to define a quality control strategy for a given manufacturing process, by selecting amongst alternative quality control strategies (e.g., 100% inspection, statistical process control, and no inspection), the one that minimizes quality costs. Cost of quality determination depends on many parameters; many of them are volatile and uncertain. The framework represents such uncertainty by intervals and through simulation defines the best quality control strategy. A risk indicator is also developed to represent the possibility that the quality control strategy defined may not be the optimal solution in the future. Sensitivity analysis is performed to identify the model parameters with more impact on the cost of quality, allowing to create multidisciplinary teams that through cooperation, can better characterize relevant uncertain parameters, among the many parameters Industry 4.0 era makes available to managers.