Date of Award
Master of Science
Rapinder S. Sawhney
Harry Lee Martin, Russell L. Zaretzki
Many manufacturing organizations have used different measures and measurement systems to determine their performance. Yet, one can improve only what one can measure. Performance measurement is indispensable and is a requirement to identify the issue, troubleshoot, and improve the production system. There are various types of performance measurement systems (PMS) presented in the literature and some of them are commonly used, for example, the balanced scorecard. However, there is little experience of performance measurement in research organizations and only 0.5% of publications are related to performance measurement systems. More specifically, the type of research organization referred in this study is established to provide affordable and convenient access to R&D expertise, facilities, and tools to facilitate rapid adoption of advanced manufacturing technologies to enhance the competitiveness of the U.S. workforce. In this research, a review of the existing literature (between 1995 and 2017) is undertaken to determine the building blocks of a PMS to build a conceptual model for designing PMSs. Based on the findings, the following four components were identified as the building blocks of conceptual model for designing PMS: 1) vertical integration, 2) horizontal integration, 3) cause-and-effect relationship, and 4) daily management system reporting framework. Based on the conceptual model a PMS was designed for assessing the throughput of a manufacturing case study identified in a research organization. A simulation model of the manufacturing case study was developed to validate and test the effectiveness and shortcomings of PMS. The conceptual model developed in this research is not limited to research organizations, it can be applied and tested in industries.
Poondi Srinivasan, Vijayakrishnan, "Design and Validation of Manufacturing Performance Measurement System Using a Case Study. " Master's Thesis, University of Tennessee, 2018.