5th International Conference on Industrial Engineering and Operations Management, IEOM 2015, 3 March 2015 through 5 March 2015
Artificial intelligence; Carbon; Carbon fiber reinforced plastics; Combinatorial optimization; Failure analysis; Fault detection; Fiber reinforced plastics; Information analysis; Machining; Pattern recognition; Carbon fiber reinforced polymer; CFRP plates; Force and torques; Geometric profile; Logical analysis of data; Machining conditions; Machining Process; Nonconforming products; Quality control
Force is considered to be one of the indicators that best describe the machining process. Measured force can be used to evaluate the quality and geometric profile of the machined part. In this paper, a combinatorial optimization approach is used to characterize the effect of force on the quality of a machined part made of Carbon Fiber Reinforced Polymers (CFRP) material. The approach is called Logical Analysis of Data (LAD) and is based on machine learning and pattern recognition. LAD is used in order to map the machining conditions, in terms of force and torque that lead to conforming products and those which lead to nonconforming products. In this paper, the LAD technique is applied to the drilling of CFRP plates, and the results, based on data obtained experimentally, are reported. A discussion of the potential use of LAD in manufacturing concludes the paper.
IEOM 2015 - 5th International Conference on Industrial Engineering and Operations Management, Proceeding, 7093752 (5 March 2015).