Customized orders management in connected make-to-order supply chains

This paper solves the order acceptance and scheduling (OAS) problem of customized products in make-to-order (MTO) supply chains. A new integrated framework that links supply chain operations is presented to overcome uncertainties in order variations and maximize the agility and responsiveness of those systems. A novel mixed integer programming mathematical model is proposed to optimize order acceptance, production planning, maintenance, and transportation decisions. The products are produced based on job-shop scheduling plans while considering the real-time access to available supply and distribution resources. To validate the efficiency of the proposed framework, the model is tested with a four-layer supply chain. Then, a wide range of experiments is implemented to study the effects of different factors such as order uncertainty, costs, maintenance, and customer satisfaction. The results proved that the proposed integrated order acceptance and scheduling can save up to 30% of supply chain expenses with efficient management of the supply, production, and distribution capacities. The results also showed that defining reasonable target customer satisfaction plays an important role in the success of these complex service systems. In addition, a scalability test proved the efficiency of the proposed model for decision making in large systems.