Advanced Manufacturing – EPSRC funded applied research
This case study highlights how an Engineering and Physical Sciences Research Council (EPSRC) funded research project at the Department of Management Science has developed new methods for manufacturing companies to analyse supplier risk.
Who is involved?
This was a multi-disciplinary project with colleagues from Mathematics, Computer Science and Operations Management at the Universities of Bristol, Coventry and Nottingham. Throughout the project we engaged with supply chain managers within various companies.
What is involved?
The overall EPSRC project developed a set of mathematical methods to support designing resilient supply networks and managing supplier risk. Working across disciplines and engaging with industry supply chain managers allowed us to define challenges for which analytical methods would be useful and to test our ideas. The Strathclyde team led the development of analytical methods for assessing supplier risk.
What did we do?
We created methods for estimating supplier risk using data routinely available in company databases about for example, delivery and quality performance. We created a new method for robust ranking of supplier performance. The method of ranking provides a reliable means of identifying high or poor performing suppliers. We also created models for assessing the value of investing in supplier development to buy down uncertainties about the future performance of a supplier. Novel processes for assessing knowledge uncertainties were developed so that learning from past suppliers can be used to express the uncertainty associated with the performance of new suppliers with whom a company has no experience.
What are the expected benefits?
The methods should enable companies to make better use of data on suppliers in contexts where performance review of existing suppliers is needed as well as when making choices to invest in developing new or underperforming suppliers.
