Abstract
Mistake proofing solutions are industrial design procedures aimed at reducing the risk of errors during production. Such procedures are widespread in any industrial sector as they allow the risk prevention by not expensive proactive actions at the level of a process design or setting. The study proposes a useful classification of the Poka-Yoke in order to assist choosing the most suitable solution for a given industrial problem. Alternative solutions are assessed and rated on the basis of a set of criteria. Additionally, the solution efficiency is estimated by applying Fuzzy Inference to selected KPIs taken from the mentioned set of criteria. Some examples which are taken from real industrial case studies demonstrate the proposed method.
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