The scheduling problem in manufacturing companies with high rework rates remains a complex research area to date. This paper presents a new approach for manufacturing scheduling that combines a predictive schedule with a proactive multicriteria decision-making method based on smart batches and their quality prediction capability. Each batch embeds an algorithm that allows it to predict its quality out of the next workstation. As soon as a batch determines that its process is too hazardous, a collaborative rescheduling decision, using the analytic hierarchy process (AHP), is initiated with its peer. This article details the proposed approach along with the AHP structure and presents the considered decision problem. A simulation model inspired by a lacquering-robot case study is described to validate this proposition. Then, the results of different scenarios are presented and discussed, highlighting the impact of social myopia on smart batches.

迄今为止，返工率高的制造公司的调度问题仍然是一个复杂的研究领域。本文提出了一种新的制造调度方法，该方法将预测性调度与基于智能批次及其质量预测能力的主动多标准决策方法相结合。每个批次都嵌入了一种算法，可以预测下一个工作站的质量。一旦批次确定其过程太危险，就会与其对等方启动使用层次分析过程 (AHP) 的协作重新调度决策。本文详细介绍了所提出的方法以及 AHP 结构，并提出了所考虑的决策问题。描述了一个受涂漆机器人案例研究启发的仿真模型来验证这一命题。然后，