A decision support system for improving customer order management in manufacturing production planning

Customer order management plays an important role in manufacturing production planning, particularly when companies face dynamic demand, limited production capacity, and different customer priority levels. This study aims to develop a web-based decision support system (DSS) to improve customer order management in manufacturing production planning. The proposed system is designed to support the prioritization and allocation of customer orders by considering production capacity, order status, customer segment, delivery requirements, and company rules. The analytical hierarchy process (AHP) was applied to determine the priority weights of three customer segments, namely original equipment (OE), aftermarket (AM), and general parts (GNP). The results show that OE has the highest priority weight, followed by AM and GNP. The developed system enables users to input order data, monitor production capacity, allocate orders automatically, and generate recovery plan recommendations when backorders occur. Based on historical order data, the system produced priority decisions that were consistent with the existing company policy while significantly reducing the time required for order allocation and recovery planning. The system enables the decision-making process to be completed faster and in a more structured manner than the manual approach. Therefore, the proposed DSS can improve the efficiency, consistency, and objectivity of customer order management in manufacturing production planning.