Flexibility has been recognized as a key competitive advantage for any manufacturing firm. It is particularly important in the current manufacturing environment with growing dominance of high mix and low volume production. The characterization and measurement of the flexibility is the focus of this dissertation. The goal is to enable manufacturing professionals to plan, monitor and manage the flexibility of their manufacturing resources, particularly in situations when response is critical, the future demands are difficult to forecast and error tolerance is relatively small....[ Read more ]

Flexibility has been recognized as a key competitive advantage for any manufacturing firm. It is particularly important in the current manufacturing environment with growing dominance of high mix and low volume production. The characterization and measurement of the flexibility is the focus of this dissertation. The goal is to enable manufacturing professionals to plan, monitor and manage the flexibility of their manufacturing resources, particularly in situations when response is critical, the future demands are difficult to forecast and error tolerance is relatively small.

To accomplish this goal, initially, attempts were made to understand the notion behind the flexibility. By departing from approaches accepted by contemporary researchers who view flexibility as directly linked with changes in the operating environment, or performance criteria, or both, this thesis considers flexibility as an independent measure. Taking the viewpoint that flexibility is an intrinsic nature of a manufacturing system, efforts have been made to characterize flexibility in the form of four flexibility descriptors, namely: capacity range, capacity response, capability range, and capability response. Based on the flexibility characterization, an approach to the measurement of flexibility at a given system level is defined. The discussion is mainly confined to the quantification of the descriptors at the workstation and at the work system level. The critical aspect is to identify the distinct capability regions based on critical capability drivers, and to model the relationship of capacity among the regions. This relationship is captured in the form of system of equations.

The research results are validated by conducting several case studies in the garment industry. An application in the area of capacity planning is also presented. The comparisons were made with the traditional way of performing capacity planning in MRP systems. The results show that in most of the cases the traditional approach of capacity planning does not take advantage of the inherent flexibility resulted from the similarity of the resources leading to either under utilization or over utilization of resources. The approach of capability representation, which incorporates the flexibility offered by the resources into the resource planning, can overcome these limitations.