Abstract

The increasing frequency of new product introductions force today's companies to continuously upgrade their production capacities. The frequent revision of production capacities and the capacity loss during this period increase the importance of ramp up duration in evaluating capacity investments. This thesis aims to explore how a firm should optimally allocate its capacity investments among different manufacturing systems considering the capacity evolution in ramp up period. The proposed models in this thesis address a production facility making products that has a specific life cycle pattern.
In this study, the duration of reconfiguration period for reconfigurable manufacturing system (RMS) is modeled as a function of the amount of capacity change. Through a sensitivity analysis, the impact of reconfiguration on the selection of manufacturing systems has been analyzed with respect to different product life cycle patterns.
Through a mixed integer programming model, a various ramp up time patterns are taken into account and a more suitable reconfiguration type for a manufacturer in terms of system layout and response range is analyzed.
Finally, the response time of a system is considered in the context of a supply chain network to improve the supply chain responsiveness. The appropriate response speed is selected through a decision tree analysis and based on the expected cost of the supply chain. The results show a faster response speed is a better choice as the failure probability of main supply node increases and/or the recovery of the main supply node decreases.