Supply chain optimisation with assembly line balancing

• Published in: International journal of production research 2012-06, Vol.50 (11), p.3115-3136
• Main Authors: Paksoy, Turan, Özceylan, Eren, Gökçen, Hadi
• Format: Article
• Language: English
• Subjects: Applied sciences; Assembly; assembly line balancing; Assembly lines; Costs; Decision making models; Decision theory. Utility theory; Decisions; Exact sciences and technology; Integer programming; Inventory control, production control. Distribution; Logistics; Networks; nonlinear mixed-integer programming; Operational research and scientific management; Operational research. Management science; Optimization; Production planning; Scheduling, sequencing; Stations; Studies; supply chain design; Supply chain management; Supply chains; Transportation problem (Operations research)
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2011.593052

Supply chain management operates at three levels, strategic, tactical and operational. While the strategic approach generally pertains to the optimisation of network resources such as designing networks, location and determination of the number of facilities, etc., tactical decisions deal with the mid-term, including production levels at all plants, assembly policy, inventory levels and lot sizes, and operational decisions are related to how to make the tactical decisions happen in the short term, such as production planning and scheduling. This paper mainly discusses and explores how to realise the optimisation of strategic and tactical decisions together in the supply chain. Thus, a supply chain network (SCN) design problem is considered as a strategic decision and the assembly line balancing problem is handled as a tactical decision. The aim of this study is to optimise and design the SCN, including manufacturers, assemblers and customers, that minimises the transportation costs for determined periods while balancing the assembly lines in assemblers, which minimises the total fixed costs of stations, simultaneously. A nonlinear mixed-integer model is developed to minimise the total costs and the number of assembly stations while minimising the total fixed costs. For illustrative purposes, a numerical example is given, the results and the scenarios that are obtained under various conditions are discussed, and a sensitivity analysis is performed based on performance measures of the system, such as total cost, number of stations, cycle times and distribution amounts.