Robust Evolutionary Optimal Tolerance Design for Machining Variables of Surface Grinding Process

A Taguchi sliding-based differential evolution algorithm with orthogonal array (TDEOA) is proposed for solving tolerance design problems. Tolerance affects system performance and leads to violation of design constraints. By including a Taguchi three-level orthogonal array, the proposed TDEOA obtains robust optimal solutions that minimize the impact of variations in machining variables and that maintain compliance with a comprehensive set of process constraints. After evaluating its performance in practical case studies of rough and finish grinding processes, the performance of the proposed TDEOA is compared with those of other nature-inspired optimization approaches. In addition, a distinct way has been introduced to estimate the reliability of a set of measurements for a surface grinding process. Reliability tests from the proposed TDEOA approach confirm its effectiveness as specified tolerances are considered.