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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ijpe.2005.03.003 Byline: Donatella Corti, Alessandro Pozzetti, Marta Zorzini Keywords: Make-to-order manufacturing; Due date setting; Capacity management Abstract: In MTO firms the production planning and control process is critical because of the various sources of uncertainty that distinguish such an environment from the MTS configuration. Product specifications are unknown until a customer formulates a request and, even after the order has been confirmed, they can vary during the processing phase. Furthermore, the time gap between a request and the acceptance of the order can be considerably long and the percentage of requests that actually become orders is very low. As a consequence, lead time cannot be predicted with exactness and probabilistic assumptions about resources workload have to be made during the tendering phase, when the MTO firm has to propose a reliable due date to the customer. Improving the efficiency of the tendering phase would allow practitioners to obtain benefits for the whole firm. The model proposed in this paper is aimed at supporting decision makers when they have to verify the feasibility of the due date required by a potential customer. In order to compare the capacity requirements of the order pool with the actual available capacity of the system, a capacity-driven approach is adopted. Specific analytical tools are proposed for this purpose, particularly for the evaluation of the load level of the system and the identification of potential overload situations. Compared to previous methods taking into consideration capacity issues, a distinguishing feature of the presented model is the 'what if' analysis, which allows the robustness of the obtained output to be verified. Author Affiliation: Management, Economics and Industrial Engineering Department, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133 Milano, Italy Article History: Received 6 May 2004; Accepted 17 March 2005

In MTO firms the production planning and control process is critical because of the various sources of uncertainty that distinguish such an environment from the MTS configuration. Product specifications are unknown until a customer formulates a request and, even after the order has been confirmed, they can vary during the processing phase. Furthermore, the time gap between a request and the acceptance of the order can be considerably long and the percentage of requests that actually become orders is very low. As a consequence, lead time cannot be predicted with exactness and probabilistic assumptions about resources workload have to be made during the tendering phase, when the MTO firm has to propose a reliable due date to the customer. Improving the efficiency of the tendering phase would allow practitioners to obtain benefits for the whole firm. The model proposed in this paper is aimed at supporting decision makers when they have to verify the feasibility of the due date required by a potential customer. In order to compare the capacity requirements of the order pool with the actual available capacity of the system, a capacity-driven approach is adopted. Specific analytical tools are proposed for this purpose, particularly for the evaluation of the load level of the system and the identification of potential overload situations. Compared to previous methods taking into consideration capacity issues, a distinguishing feature of the presented model is the 'what if' analysis, which allows the robustness of the obtained output to be verified. Keywords: Make-to-order manufacturing; Due date setting; Capacity management

A multi-case study of the Italian capital goods manufacturers is conducted to explain the differences that are seen in the customer enquiry management (CEM) processes of different companies in a sector. The degree of product customization, uncertainty and the flexibility of the system are shown to be the three major factors that affect the techniques used for CEM in different organizations.

A method for improving the setting up of air-jet looms by clarifying the function which links different variables involved is presented. A method for measuring the fabric quality depending on the factor values is also developed. The proposed procedure is seen to reduce cost and time of the setting up of air jet looms.