A graph-based decision support system for analyzing hybrid make-to-stock/make-to-order manufacturing environments - Sammak Jalali, Moeen; Fatemi Ghomi, S.M.T.; Rabbani, Masoud (Brazilian Journal of Operations & Production Management, 2020)
Goal: This paper aims to facilitate production-planning strategies for demand responsiveness. Our paper implements graph-rewriting systems towards supporting operative decision making in production environments. Design/Methodology/Approach: We design a decision support approach which is able to recognize and resolve conflicts amongst workstations in a hybrid production system. During the proposed stages of the presented approach, we rewrite the hybrid system by means of graph representation procedure, identify conflicts among the workstations by means of the developed graph coloring algorithm, and evaluate performance of the reorganized system by defining key performance indicators for the presented system. Results: We prove that the graphs’ chromatic numbers in such systems are less than or equal to entire number of dummy nodes applied to the system by means of our proposed algorithm. Furthermore, the presented structure improves the performance of the system by analyzing production bottlenecks. Limitations of the investigations: we only considered the Key Performance Indicators according to products, workstations, and customers. However, the problem can be more generalized by adding some more elements. Practical Implications: Our methodology enables managers to assess the performance of the reorganized system after applying the heuristic algorithm, by means of representing a performance evaluation procedure. Originality/ Value: We focus on presenting a novel structure to help companies using hybrid make-to-stock (MTS)/make-to-order (MTO) production strategies to (1) identify conflicting workstations and the relations among them, (2) propose dialectical prioritization rules and techniques by means of graph-coloring concepts for resolving the conflicts, (3) reorganize the system, and evaluate performance.