Abstract
Process quality planning should establish a Quality Control Plan (QCP) to achieve the desired quality level with minimum Cost of Quality (CoQ). This plan establishes the critical quality variables, control stations in the process, and control method at each control station. The purpose of this study is to, through a simulation approach, determine a QCP for a manufacturing process, which minimizes the CoQ. The inputs to the simulation model are inspection and repair/replace costs, proportion of defectives at process output, type I and Type II inspection errors, alternative control methods (no control or 100% inspection), and the cost of delivering defective units to the customer. The proposed model was developed in Simulation Modelling Based on Intelligent Objects (SIMIO) software to estimate the total CoQ and number of compliant units delivered. This model allows to determine the CoQ of the alternative scenarios and to define a QCP that minimizes the total CoQ. An illustrative example based on a manufacturing process demonstrates the applicability of this model, and the results indicate that the best QCP, amongst defined alternatives, may vary when the model parameters are updated. As future research directions, the simulation models could be relevant when defining digital twins of manufacturing processes and models’ results can support process improvements.
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Acknowledgment
This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.
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Sousa, S.D., Dias, L.S., Nunes, E.P. (2024). Assessment of Alternative Quality Control Plans in Dynamic Contexts: A Simulation Approach. In: Silva, F.J.G., Ferreira, L.P., Sá, J.C., Pereira, M.T., Pinto, C.M.A. (eds) Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems. FAIM 2023. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-38165-2_52
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