Optimization in Quality Control presents a broad survey of the state of the art in optimization in quality, and focuses on industrial and national competitiveness. Each chapter has been carefully developed and refereed anonymously by experts in the area of optimization in quality control. Some of the topics covered in this volume include: fundamentals of optimization techniques contemporary approaches to optimization models in process control economic design of control charts determining optimal target values in multiple criteria economic selection models examining quality improvement schemes by trading off between expected warranty servicing costs and increasing manufacturing costs designing optimal inspection plans. This book will serve as an important reference source for academics, professionals and researchers.

Control chart are widely used to establish and maintain statistical control of a process. In other words it is a tool used to monitor processes and to assure that they remain "In Control" or stable The vital function of control chart is to find out the occurrence of assignable causes so that the necessary corrective action can be taken before a huge amount of defective product is produced. The X-bar control chart is preferred most in comparison to any other control chart technique if quality is measured on a regular scale. In the present project, we here develop the economic design of the X-bar control chart using Genetic Algorithm to determine the values of the sample size, sampling interval, width of control limits such that the expected total cost per hour is minimized. The genetic algorithms (GA) are applied to search for the optimal values of the three test parameters of the X-bar chart. In genetic algorithm we use mutation and cross-over technique to get the optimal solution. Finally, a sensitivity analysis will be carried out to investigate the effect of model parameters on the solution of the economic design.