With the advent of latest technology, manufacturing process becomes so sophisticated and complicated that a single response variable (quality characteristic) can not reflect the true product quality and there is intense competition between market participants for cost and delivery (productivity) as well. Any manufacturing process in the present state requires multi objective optimization model to optimize quality, cost and productivity simultaneously. Optimum prediction is critical as it requires lot of experiments for data capturing which involves time and cost. In the present manufacturing set up, it is essential to identify optimum parametric combination for multi objective function real time problems with lesser experiments and lesser effort with better accuracy. Taguchi method is a well known fraction factorial design, which requires minimum number of trials for Identifying optimum parametric combination in real time problems.In this paper an attempt is made to review the literatures of various methods used by researchers for multi - objective optimization problems using Taguchi methods.
Multi-Objective Optimization of Manufacturing Process in Carbon Fiber Industry Using Artificial Intelligence Techniques
