A joint economic lot size model with third-party processing. (April 2017) - Ferretti, Ivan; Mazzoldi, Laura; Zanoni, Simone; Zavanella, Lucio Enrico
Highlights: A joint economic lot size model with third-party processing is studied. Aim of this work is to analyse the performance of different supply chain configurations. Results show that adopting a coordination policy between Vendor and Manufacturer can lead to a total cost saving. Results show that VMI with CS policy can additionally improve such results. Abstract: This contribution presents a production-inventory model for a supply chain that incorporates three distinct entities a Vendor, a third-party external Manufacturer and a Buyer. The Vendor purchases raw materials from a supplier and performs preliminary manufacturing operations, the semi-finished goods are sent to a third-party Manufacturer for additional manufacturing operations then the products are sent back to the Vendor for final operations or assembly with other components and finally they can be sold to the customer. The study of this particular Supply Chain configuration has been inspired by an industrial case observed in the aeronautical sector. The aim of this work is to analyse the performance of different supply chain configurations with third-party processing for operations carried out by the Manufacturer. The first option is to consider a traditional production-inventory system where the Vendor and the Manufacturer follow a centralised traditional agreement policy. The second option involves a centralised Vendor Managed Inventory policy with consignment stock agreement between the Vendor and the Manufacturer. The objective is to determine the optimal lot size policy, i.e. traditional agreement or consignment stock agreement, in order to minimize supply chain total cost. Finished goods are assumed to have price-independent deterministic demand, while cost components are assumed to be constant over time. The analysis is carried out considering system total cost as the objective function to be minimized.