Improvement of Piston Ring Quality: A Case Study

Student Name: H. S. Nataraja

The management of the organization the student was working for, was facing a serious quality problem due to high scrap rates in most of their products. In this work, a systematic step by step approach was adopted for solving this quality management problem using various statistical quality and process control techniques. First the most delicate and costly ring was selected for this case study and a Pareto analysis revealed axial thickness as the most problematic quality characteristic. Next it was checked whether the processes affecting axial thickness were in statistical control or not by means of control charts. Two such processes were identified which were not in statistical control. A simple recommendation solved the problem with one of the processes. For the other process, which was not in statistical control, an in-depth study led to an Ishikawa Diagram, diagnosing the various factors affecting the axial thickness. Then these factors were classified into control and noise factors and a full factorial experiment with replication was designed and carried out to analyze the variances of the averages and signal to noise ratios of the experimental results. These ANOVA's and multiple comparison $t$-tests suggested certain optimum levels for the control factors. A confirmatory experiment with these optimal settings yielded highly improved process capability indices. The underlying assumptions of all the applied statistical techniques were appropriately validated. This research helped the organization drastically reduce its scrap rates resulting in a dramatic increase in profit.