RSM based expert system development for cutting force prediction during machining of Ti–6Al–4V under minimum quantity lubrication

• Published in: International journal of system assurance engineering and management 2023-12, Vol.14 (Suppl 4), p.938-945
• Main Authors: Shetty, R., Kumar, C. R. Sanjeev, Ravindra, M. R.
• Format: Article
• Language: English
• Subjects: Cutting force; Cutting parameters; Engineering; Engineering Economics; Expert systems; Logistics; Lubrication; Machining; Manufacturing; Marketing; Mathematical models; Organization; Original Article; Quality Control; Reliability; Response surface methodology; Safety and Risk; Titanium base alloys
• ISSN: 0975-6809; 0976-4348
• DOI: 10.1007/s13198-021-01495-z

In recent days the manufacturing process have become more precise and cost efficient due to advancement in the field of computer technology. Information technology has been integrated with manufacturing practice and has resulted in time reduction from concept of a product to marketing of the product. Cutting force generated is the main manufacturing issue raised among industries as it clearly affects quality and cost of the final product. Hence using extensive literature and data base knowledge optimum cutting parameters are selected. Therefore, this paper focuses on a response surface methodology (RSM) based expert system that has been developed using JAVA programming with the help of response surface second order model to automatically generate values of cutting force during machining of Ti–6Al–4V alloy under minimum quantity lubrication (MQL) for different process input parameters. From RSM it has been observed that calculated value of F (20.36) was greater than the F-table value (3.02) and hence the model developed can be effectively used for machining of Ti–6Al–4V alloy. Further the developed RSM based expert system model can be successfully used to predict the force generated during cutting process while machining Ti–6Al–4V alloy under MQL conditions.