Using Analytic Hierarchical Process for Scheduling Problems Based on Smart Lots and Their Quality Prediction Capability
The scheduling problem in manufactories with high rework rates remains an actual complex research source. This paper presents a combination of a predictive schedule with proactive decision making based on smart lots. Each batch embeds an algorithm which allows predicting the risk of rework on the next workstation. If the risk of rework is above a defined threshold, a collaborative re-scheduling decision, using analytic hierarchical process (AHP), is initiated for the other batches. A simulation model, inspired from a lacquering robot case study is described. Then, the results of different scenarios are presented and discussed.
KeywordsProactive decision making Analytic Hierarchical Process (AHP) Quality prediction Smart lots
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