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.
A capacity-driven approach to establish reliable due dates in a MTO environment
CORTI, DONATELLA;POZZETTI, ALESSANDRO;ZORZINI, MARTA
2006-01-01
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.File | Dimensione | Formato | |
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