Analysis on quality of diagnostic processes in power electrical engineering using combined methods of lead six sigma and fuzzy approaches

Abstract

Process control is a statistics and engineering discipline that deals with architectures, mechanisms and algorithms. In power electrical engineering and diagnostics field it is important to evaluate which are the critical factors influencing on the quality of the process, as well as to determine which the factors are leading to the failures. Applying Lean Six Sigma methodologies on different stages can help to benefit on many process levels: to evaluate the efficiency of the chosen diagnostic schema, make the diagnostic process run faster and more stable with less failures and can help to create a systematic approach in all the mentioned benefits above. In turn Fuzzy approach and Fuzzy logic based systems with their capability to deal with incomplete information, imprecision, and incorporation of qualitative knowledge shows a great potential for application in electric system fault detection as well as serve as a good basis for measuring effectiveness of chosen methods. Combining different type of quality methods and fuzzy mathematical tools will provide a broader view on the performed process and will help to create an understanding where it can be improved, and thus control and improve the quality. Fault tolerance design has been examined by Lean Six Sigma approach, as well as identification of the fault itself has been analyzed using fuzzy expert system.