A part-mix batch-sizing and machinability data system for milling operations: an optimal sustainable cost of quality approach

With increased global competition and higher demand for sustainability in emerging markets, manufacturers are actively exploring new avenues to reduce production costs without compromising product quality. To address this challenge, a novel mixed integer nonlinear model is formulated by incorporating internal quality costs, environmental impact considerations, and the impact of buffer size to solve the micro-computer aided process planning problem. The scope covered is limited to milling operations for a part mix involving different materials being machined. Surface roughness is used to evaluate the desired quality level of finish. The internal quality failure cost model, including scrap and rework, is developed based on Taguchi’s quadratic loss function. Mathematical programming is employed to validate the results of genetic algorithms (GAs). Because of the nonlinear nature of the model, GAs has been used. Considering strict quality cost measures, the model minimises internal quality-related costs while minimising the environmental impact.