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A customer order driven production planning method is developed by combining the buying behaviour of the customers, i.e. the required customer delivery lead time, with the production capacity needed to meet the customer orders. The method can be applied in order to determine the WIP cap and the work-ahead-window of a CONWIP controlled production and can also be used to implement a new market driven production planning. In addition an a priori check is presented to investigate the ability to install a pure make to order system

The market is forcing production towards shorter lead times to ensure shorter delivery times. The favoured production system is a make to order (MTO) system with a production lead time shorter than the customer required delivery time. Wortmann et al. (1997) or Berry et al. (1995) stated that customer driven manufacturing is the key concept for the factory of the future. There are several strategies to decrease the production lead time and to change a production system from a make to stock (MTS) into a MTO system. An important prerequisite is to reduce the inventory. Improvements in plant layout, processes, organization and production planning and control methods can lead to a decrease in inventory. In Kosonen and Buhanist (1995) for instance the change of a factory into a customer focused lean production system is discussed or Wisner and Siferd (1995) showed the advantages of process oriented manufacturing in order to meet customer requirements. In the field of production planning and control systems, especially pull systems like KANBAN (see Ohno, 1988) or hybrid systems like constant work in process (CONWIP) (see Spearman et al., 1990) try to ensure low inventory and have a customer order focus. Hendry and Kingsman (1989) suggested developing more suitable production planning and control methods for MTO systems. He et al. (2002) developed optimal and near-optimal inventory control policies for MTO systems. The approach developed in this paper is applied to a CONWIP system to determine the control parameters. Hopp and Roof (1998) developed an adaptive method called Statistical Throughput Control for setting the control variable WIP level. Their goal is to meet target production rates. Framinan et al. (2003) present a good overview of operation, application and comparison of CONWIP presented. Evaluation of a CONWIP system, especially concerning quality, is discussed in Duri et al. (2000). The main idea of the presented paper is a focus on a combination of the customer buying behaviour with the plant capacity. Some authors address similar relationships. For instance, Spearman et al. (1989) in their hierarchical architecture to control inventory have taken into account the capacity and demand. Chen and Wan (2005) compared two competing MTO firms concerning capacity and short delivery times, while Arslan et al. (2001) addressed expediting in MTO production systems and Ozdamar and Yazgac (1997) discussed capacity driven due date setting in MTO systems. Market-driven production planning and control is also discussed in combination with deteriorating items or remanufacturing, see for instance Chen and Chen (2006), Souza and Ketzenberg (2002) or Yang and Wee (2001).

In this paper, a model for customer order driven production planning is introduced. The main idea is to combine the required customer delivery lead time with the required capacity to meet the customer orders. An equation which describes the ability to implement a make to order system without stock outs is developed and a formula to calculate the average production lead time is yielded. The method can be applied to determine the control variable for a CONWIP system and to design a new market driven planning method. In Duenyas (1993) it is shown that M-CLOSED input policy (separated card counts for every type of product) outperforms S-CLOSED (only one card count for all types of product). In further research work the proposed method for the card setting in a CONWIP system based on S-CLOSED should be extended to M-CLOSED policy. Additional further research should be done on analyzing the performance of the introduced method and to compare the method with existing production planning strategies. In addition, further applications should be developed, for instance for more complex production systems. Furthermore, an investigation of the influence of the lot size, of the processing time and of the set up time should be analyzed to improve the understanding of the concept.