Today's society is characterized by a high degree of change where the manufacturing systems are affected by both internal and external factors. To adapt to current manufacturing requirements in the form of short lead-time, more variants, low and fluctuating volumes, in a cost-efficient manner, new approaches are needed. As the global market and its uncertainties for products and its lifecycles change, a concept called 'reconfigurable manufacturing system' has been developed. The idea is to design a manufacturing system for rapid structural change in both hardware and software to be responsive to capacity and functionality. A company's development towards the concept is often based on a strategy of incremental investments. In this situation, the challenges are to prioritize the right project and maximize the performance as well as the financial efficiency of a multi-approach problem. The report is based on three different issues. Partly how to standardize relevant performance-based metrics to measure current conditions, how new performance-based metrics can be developed in collaboration with reconfigurability characteristics, and set a direction for how decision models can be used to optimize step-based investments. The study is structured as an explorative study with qualitative methods such as semi-structured interviews and document study to get in-depth knowledge. Related literature addresses concepts in search areas such as reconfigurable manufacturing system, key performance indicators, investment decisions, and manufacturing readiness levels.

The findings are extracted from interviews and document studies that generate a focal company setting within the automotive industry, which acts as the foundation for further analysis and decisions throughout the thesis. The analysis results in sixteen performance measurements where new measures been created for product flexibility, productionvolume flexibility, material handling flexibility, reconfiguration quality and diagnosability using reconfigurability characteristics. A conceptual decision support model is introduced with an underlying seven-step investment process, analyzing lifecycle cost, risk triggered events in relation to cost, and performance measurements. The discussion chapter describes how different approaches are used during the project that has been revised by internal and external factors. Improvement possibilities regarding method choice and the aspects of credibility, transferability, dependability, and conformability are discussed.

Furthermore, the authors argue about the analysis process and how the result has been affected by circumstances and choices. The study concludes that a three-pronged approach is needed to validate the investment decision in terms of system performance changes, cost, and uncertainty. The report also helps to understand which performance-based metrics are relevant for evaluating manufacturing systems based on operational goals and manufacturing requirements.