Manufacturing processes are often disrupted by unexpected events, such as machine breakdowns, raw material shortages, and the arrival of new orders. Effectively managing these uncertainties is ...crucial for maintaining the feasibility and optimality of the production system. The efficiency of a manufacturing system is heavily dependent on the optimality of its scheduling plan. In this study, we present a reactive scheduling approach based on the S-graph framework. The proposed method is specifically designed to handle the arrival of new jobs and generate schedules with the shortest makespan, i.e., the minimum total completion time. Whenever a new order is received, the method dynamically adjusts the production plan through rescheduling. Three distinct scheduling policies are identified that determine which tasks require scheduling or rescheduling and which tasks should remain unchanged in their schedules. To evaluate the effectiveness of the algorithm, we solve several examples from the literature and analyze the results. The findings demonstrate the efficiency and efficacy of the proposed approach. The ability to accommodate new job arrivals and generate schedules with a minimized makespan highlights the practical relevance and benefits of the S-graph-based reactive scheduling method.
The optimization of manufacturing systems is rarely a deterministic task in practice, as uncertainties of various origins often have significant impact on the feasibility or quality of a production ...plan. The decision making process is often a complex multi-stage mechanism that anticipates and reacts to numerous parameter changes, both internal and external. Such optimization problems and the corresponding approaches are often classified and categorized based on the features of the addressed uncertainties and the desired objective. The goal of this paper is twofold. First, a systematic approach is presented to enumerate the possible optimization problems for a given set of uncertainties and degree of freedom in the planning. This approach is illustrated via a scheduling example that is inspired by literature case studies and focuses on financial objectives with varying demands and prices in the market. Then, selected problem classes identified by the approach are discussed in detail, illustrating and examining the available techniques to tackle them, citing literature studies applying the same or similar approaches.
One of the new challenges of the 21st century is the Industry 4.0. Manufacturing companies moving away from mass production and getting closer to customized production and manufacturing of customized ...products through digitization. The expectations are high, meeting the requirements is a real challenge to industrial partners. In order to help meet the challenges the University of Pannonia Nagykanizsa Campus started to establish a fully automatized industrial laboratory. In this paper the architecture of the Industry 4.0 laboratory and the purpose of the Factory Subsystem is presented.
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