Production Logistics of a Microbiology Laboratory

Describe the proposed research in a style that would be accessible to an interested 14 year old [up to 4000 chars] This project is concerned with the development of mathematical modelling and optimisation techniques. It focuses on the smooth running of a state-of-the-art microbiology laboratory, of importance for national food safety. The laboratory is run, by RHM Technology Ltd., to the highest quality standards, with individual samples controlled with bar coding. The laboratory was formerly run along traditional lines with manual testing and operator decision. More recently, automated testing equipment, and a Laboratory Management Information System, have been introduced. Despite these improvements, the running of the laboratory has not been optimised to exploit the new opportunities presented. Surges in demand have been found to put unexpected strain on the system. The purpose of this project is to treat the laboratory as a production process. The configuration of the microbiology laboratory is at the boundary of classified mathematical scheduling problems. It contains a mixture of batching and sequential activities to be carried out in parallel. In addition, a central issue is that of co-ordinating tests (analogous to production) with reporting of results (deliveries), in common with many supply chains. The laboratory setting will thus provide new mathematical and algorithmic challenges. Our aim is to build upon the wealth of existing academic knowledge of mathematical production scheduling and to deveop new methodologies for the various novel aspects presented by the microbiology laboratory.This project offers a rare opportunity to study an application in detail without being committed to customised deliverables. The sponsoring company, RHM Technology Ltd., are looking for new insights into the workings of their microbiology laboratory. The academics are interested in having the opportunity to test out their theory and developing new solution methods. If the resultant scheduling methodology is sufficiently comprehensive, RHM is committed to trialling it, following a proof of concept simulation exercise. It is anticipated that this project will give rise to aspects of the logistics of real life scheduling as yet unexplored in the mathematical literature.