Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos, Xiaochen Zheng
Nowadays, the manufacturing industry is constantly changing. Production systems must operate in a highly dynamic environment where unexpected events could occur and create disruption, making rescheduling inevitable for manufacturing companies. Rescheduling models are fundamental to the robustness of production processes. This paper proposes a model to address rescheduling caused by unexpected events, aiming to achieve the zero-defect manufacturing (ZDM) concept. The goal of the model is to incorporate traditional and ZDM–oriented events into one methodology to calculate when the next rescheduling will be performed to effectively react to unexpected events. The methodology relies on the definition of two key time parameters for each event type: event response time (RT) and event delay response time (DRT). Based on these parameters, an event management algorithm is designed to identify the optimal rescheduling solution. The DRT parameter is calculated based on a multi-parametric dynamic formula to capture the dynamics of production. Moreover, ANOM, and ANOVA methods are used to analyse the behaviour of the developed method and to assess the level of robustness of the proposed approach. Finally, a case study based on real production scenarios is conducted, a series of simulation experiments are performed, and comparisons with other rescheduling policies are presented. The results demonstrate the effectiveness of the proposed event management algorithm for managing rescheduling.
2021
