Keywords: assemble–to–order systems, ATO, production planning, load–dependent lead times, clearing functions, service level requirements, robust optimisation, manufacturing industry, capacity utilisation, inventory holding cost, inventory planning, demand uncertainty
Load–dependent production planning for an assemble–to–order system
Assemble–to–order (ATO) systems enable manufacturing firms to be cost–effective and at the same time responsive to changing customer orders. In this paper, we study an assemble–to–order (ATO) system, where raw materials are released into a capacitated production stage. Inventory of produced components is kept in stock ready for final assembly once specific orders for products are received. An important planning issue is to find an optimal trade–off between capacity utilisation and components inventory holding cost with the aim to meet uncertain demand of end products. In this paper, we formulate two integrated production/inventory planning models using clearing functions while considering demand uncertainty. In the first model, we assume that demand is normally distributed and propose a chance constrained formulation. In the second model, we consider the case of unknown demand distributions and use a robust optimisation approach. The proposed models are linear programmes that provide safe production plans. We illustrate the proposed models using a real case study from the literature and analyse the effect of congestion and demand uncertainty.