Systems Integration of Automatic Specimen Processor with a Petri Net Approach to Control, Diagnose and Prevent System Faults
Microbiology analysis is an essential tool for diagnosing infectious diseases in health and medical services. The subfield of Bacteriology receives the largest volume in human specimens (i.e. urine and swab samples). For an average sized clinical lab, 1,000 to 5,000 samples would need to be processed daily. Such high demand in conjunction with the labour‐intensive and error prone analysis techniques makes automation an excellent solution for optimizing laboratory human resources. The focus of this research internship with Dynacon, an automated specimen processor provider, is to apply Controlled Petri nets (Ct1PNs) to the specimen processing task and to explore its potential capabilities in identifying and diagnosing system faults. The inherent contribution of this approach is twofold: 1.) the implementation of Ct1PNs on a microbiological specimen processing task in a novel application of Petri nets; 2.) anticipated results from actual hardware interactions will be instrumental in the further development of robust and fault tolerant Flexible Manufacturing Systems.