Abstract
This paper proposes a production planning approach for a job shop type manufacturing company in electronics sector that operates with make-to-order (MTO) convention and has a high-mix production range. A novel Mixed Integer Linear Programming (MILP) model is proposed that finds workload-dependent planning horizon by making order acceptance decisions. Partial acceptance of orders and delayed internal target deliveries contribute to the novelty of the proposed model. We establish the complexity of the problem and solve real-life problem instances of a medium-size manufacturing company in the south of The Netherlands. Our computational results show that the proposed MILP model can allocate desired workload to work centers by dynamically adjusting the time horizon for production plans. Our approach can practically be used within reasonable times for daily updates of internal production targets. We perform a sensitivity analysis to show how the time horizon is determined with varying system conditions. The obtained workload amounts satisfy minimum requirements of production units, as this cannot be achieved by the current practice.
Highlights
Efficient production planning and capacity management is a crucial as well as challenging task in MTO flexible job-shop type production companies with high-mix product range
This is achieved through comparing the workload per resource that is derived from both order selection approaches; the approach presented in this paper with a dynamically selected time horizon and the current practice at Applied Microelectronics (AME) with a fixed time horizon of one month (31 days)
The portions of the bar shaded in orange indicate a shortage of workload: this means that the given time horizon does not ensure for a selection of orders that is able to fill required minimum workloads
Summary
Efficient production planning and capacity management is a crucial as well as challenging task in MTO (make-to-order) flexible job-shop type production companies with high-mix product range. There are pioneering studies tackling integrated process planning and scheduling problem, they can solve limited instance sizes, e.g. up to 25 jobs (Sobeyko and Mönch, 2017) and 80 jobs (Shokouhi, 2018) This indicates the need for large-scale optimization approaches. In the low density case, the planning horizon is selected with a longer length This leads to some order rejections for work centers that are highly loaded. Our production planning approach contributes to the integration of order management, production scheduling, and material requirement, it is a promising component for internal flexibility of a production control of the considered manufacturing system.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
