Factory Production Machine Damage Detection System Using Case-Based Reasoning Method

Abstract

Computers are essential in industrial processes because they play a part in the life cycle of company-produced product systems. Damage to production equipment happens frequently as a result of a lack of detailed periodic maintenance, making it difficult for operator and technician staff to maintain production machines. Because they are still utilizing the manual approach, repair times are long and costly accurate. Case-Based Reasoning (CBR), a problem-solving technique based on prior experience and applied in the present, is one discipline of computer science that is commonly employed by humans to help and facilitate work. CBR is used to find solutions by exploiting or analyzing previously collected case data. Case representation, case indexing, case retrieval, case adaptation, and case maintenance are the five goals of CBR in knowledge formation. The process of discovering and measuring the case with the greatest closeness is known as case retrieval. The goal of this research is to create a way to automatically detect system failures in machines, so that if a malfunction happens with a CBR-based system, it will be easier to detect early, repair faster, and be more accurate. The accuracy of the system utilized is 90%, according to the results of testing the tools manufactured, and it is effective for managing production machine repairs. While the test error is twenty times with the highest result of 33.33 % and the lowest is 0% according to the level of accuracy of the sensor on the object.