A new project scheduling approach for improving multi-product multi-period production planning problems

• Published in: Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture Vol. 222; no. 11; pp. 1517 - 1527
• Main Authors: Noori, S, Bagherpour, M, Zorriassatine, F, Makui, A, Parkin, R
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.11.2008; Sage Publications; SAGE PUBLICATIONS, INC
• Subjects: Applied sciences; Computer simulation; Criteria; Demand; Exact sciences and technology; Feasibility; Inventory control, production control. Distribution; Leveling; Linear programming; Machine tools; Machining; Machining centres; Matching; Mathematical programming; Mechanical engineering; Mechanical engineering. Machine design; Operational research and scientific management; Operational research. Management science; Production planning; Project management; Scheduling; Scheduling, sequencing; MPMP; production planning; machine profile; project scheduling; Project management; Machining; Product planning; Linear programming; Scheduling; Multiple production; Modeling; Production management; Production rate; Production planning; Resource constraint; Graph matching; Levelling
• ISSN: 0954-4054; 2041-2975
• DOI: 10.1243/09544054JEM1081

The problem of matching production levels for individual products to demand fluctuations during multiple periods is known in the production planning literature as the multi-product multi-period (MPMP) problem. Linear programming (LP)-based solutions have been extensively reported in this respect. MPMP problems are commonly solved by using either analytic or simulation methods. More recently, hybrid solutions consisting of both analytical models and simulation analysis have been proposed where some operational criteria, e.g. the order of visit to machining centres, are taken into account. In this paper, results related to some of the literature based on hybrid solutions are used as the initial feasible solutions and then examined in the context of project scheduling by considering the influences of resource constraints. After converting the MPMP to a project network problem and assigning resources to activities and consequently levelling the resource profiles, it is discovered that machine utilization can be further improved by applying unused machine capacities. A LP model is therefore developed in order to maximize feasible production rates over all the production planning periods. The proposed approach results in improvements on the results of earlier hybrid solutions reported in the literature. Finally, three different planning problems are suggested for further applications of the proposed approach in the context of manufacturing environments.