Most of the products we use in our daily lives are brought to the markets by supply chains. Companies that want to have competitive edge realize the importance of concentrating on core competencies and outsourcing the rest of the activities from others. In addition to focusing on core competencies, the search for low labor costs has led to vertical disintegration of multinational companies. Therefore, customers and end users of products are dependent on a large number of often distant and hard to control manufacturers and service providers.
In this research line we contribute to the scientific literature by developing algorithms for optimizing the supply chain decisions of multi-echelon systems subject to demand and supply uncertainties. These algorithms are applied by many multi-national companies and they bring significant cost benefits.
One particular system type that has been extensively studied in our Supply Chain Management research is the configure-to-order system. The end products of configure-to-order systems are in most cases unique and fulfill the exact needs of the customer. Examples include advanced medical systems, electronic microscopes and lithography systems. These products are created through the careful combination of different hardware modules and software.
The supply chain of a configure-to-order business distinguishes between two main phases. The first part of the supply chain concerns the modules. These must be ordered in advance in order to prevent excessive total customer lead time. Therefore, the first part of the supply chain is driven by forecast. The latter part of the supply chain is driven by the customer order. In our research we focus on the optimal design and operational coordination of these two phases of the configure-to-order systems.