Uncertainty and Changeability in Manufacturing Equipment Planning

Abstract

Increasing time and cost pressure are forcing companies to plan and design their manufacturing systems with fuzzy product data in order to keep pace with shorter and agile product development cycles. This development is accompanied by a multitude of requirements for the planning of the respective manufacturing equipment. Many of these requirements are associated with a high degree of uncertainty and can thus only be specified vaguely in early planning phases, eventually leading to costly, originally unforeseen changes to the specified type of equipment. This consequently underlines the need for a predictive evaluation of uncertainty, or changeability in this context, to enable a more efficient planning approach based on quantified levels of uncertainty. In this paper, the authors therefore present the results of a systematic literature review on the evaluation of changeability in manufacturing systems design with special focus on uncertainty. Most importantly, standardized methods are not available yet; hence, product development as well as project management approaches are frequently adapted to manufacturing systems design. Furthermore, FMEA and fuzzy-logic-based methods are promising techniques for the assessment of uncertainty as a key element of changeability. Concluding, the paper discusses how the findings could support the development of a holistic approach to identify and predictively evaluate uncertainty in order to use it as a decision-making factor for the application of agile planning methods, thus contributing to better decision-making and higher achievement levels of project targets in industrial practice.