Rejection Analysis in Piston Manufacturing Unit

Abstract

Rejection Analysis is a process of identification of quality and productivity related problems which the key factors in manufacturing process. The application of rejection analysis allows studying the failed parts. It helps to capture the minute failing details. It provides effective suggestion to the problem encountered in manufacturing process. It eliminates the scrap and tells which part can be rework. After preliminary study on machining process of piston in 6M production line at FEDERAL MOGUL GOETZE INDIA LTD, it was apparent that production line was having more defect and rework and had rejection percentage rate of about 10% .In order to examine this project, study was conducted to observe the process going on in the production line, to reduce the rejection rate by tracking the root causes and by providing suggestion. Some of tools and techniques used to achieve the objectives were check sheet, Pareto chart, cause and effect diagram and control charts. The methodology employed to achieve the stated objective, includes the study on nature of defect occurrence, collection of data on number of defects occurred during three months of study using check sheet, identification of major defect percentage using Pareto chart, finding the causes using cause and effect diagram and investigating the process is in control or not by statistical control charts. Lastly providing the suggestion regarding minimizing the defect and rework. The outcome of project was reduction in overall rejection rate in production line from 10% to 7 % and thus the production line was able to meet the required demand

Keywords

Quality, Defects, Pareto Analysis, Root Cause, Pareto Analysis.

INTRODUCTION

An automotive manufacturing industry aims at meeting the customer requirement by providing the good quality of product. So many company focuses to reach the global market in satisfying the customer demand. Quality of the product is achieved by minimization of rework, reducing scrap rate and minimizing man hour on rework. Rejections in automotive industry occur due to not placing the product for required specification. Now a day’s rework of rejected parts are common but rework add losses to the company net profit, if the company is a continuous mass production where the products go through a series of process to come out with final product. Piston head manufacturing travels through a sequence of manufacturing and machining processes to become end product. Quality control at every workstation is important. Controlling measures for preventing the defect parts being accepted and sent through next stations need to be avoided to reduce the defect rate in the processing itself. Pareto analysis helps to identify and classify the defect according to percentage significant. Cause and effect diagram is a useful tool in identifying the major causes. This diagram helps to build a relationship. Brainstorming is done with utilising these quality tools to provide an effective solution. Thus quality management tools are effective and significant in reducing the rework and rejection rate.

II. LITERATURE REVIEW

This section highlights on different journals papers regarding area of the project study. These researches uphold the effective methods and techniques which will enhance the project. The literature review focus mainly on topics such as root cause analysis, data analysis, Pareto analysis, statistical process control.

DALGOBIND MAHTO [1] in this paper, it gives details of root cause analysis methods and techniques in identification quality of major key characteristics in manufacturing process. It is very risk in identifying problem in multistage operation. In this paper, root cause analysis was adopted to reduce the defect rate in cutting operation in CNC machines. This study dives detail structure to solve human related problem in manufacturing process. This study gives an idea for stakeholders to promote effective and better solution all time.

TANVIR AHAMAD [2] this paper presents on use of Pareto chart and cause and effect diagram in analysing the defect caused in garment industry. This papers aims at reducing the defect rate caused while stitching clothes. Using these methods it was identified about 80% defect rate in process of stitching. The top five defects was identified and analysed. Using cause and effect diagram causes and effect are constructed. The study provided suggestion to reduce the defect rate. Thus this papers gives idea of how effectively minimizing the rework and defect rate.

A.L. MOE and A.B ABU [3] in this paper, it uses the six sigma approach in defect reducing in automobile industry. The six sigma processes like define, analysis, measure, improve and control are applied. This study includes tools like quality management tools such as Pareto analysis, data analysis, cause and effect diagram and design of experiments. This study aims at finding out the root cause to problem and providing solution .This paper highlighted the cause foe product rejection rate. This paper aims at reducing rejection rate from 38% to 13%. Hence six sigma approach was effective in reducing the defect.

Md .MAZIDHUL IBRAM [4] this paper highlights on use of quality tool in minimizing the rework in apparel industry. This paper gives idea of quality and productivity improvement in apparel industry. The methods helps to provide the framework in indentify the defect and analyse. It helps to reduce the defect rate. This paper gives the idea of application of process performance of critical process which leads to proper utilization of machines and time. The paper aims at improve the productivity by minimizing cost and internal throughput.

III. METHODOLOGY

The study exhibited in this chapter includes simple approach in the analysis of rejection rate in particular production line in piston machine shop. The production line consists of sequence of operation in making final product. Defects occur due to deficiency in machining process. The study aims at analysing the rejection rate using quality tools like check sheet, Pareto chart and cause and effect diagram.

IV. DATA COLLECTION

The data has been taken from 6M production line. Identification of defect was made and 10 types of defects were found. Number of defects of the production lines is listed on the Check Sheet. The defect types are expressed by some specific defect codes.

Nature of defect occurrence in 6 months production

Pareto chart of defects

Observations from Pareto Analysis for Top Defect Positions

Compression height variation is the most frequent defect with as much as 27% of the total defect. • Part damages are the second most frequent defect with 26.10% of the total defect. • Among other defects contribution of skirt variation is 7%, scratches is 6.1%, fixture seat variation is 4.9% of the total defect. • These five top defect positions are the vital few which contribute to 72% of total defects occur.

VII. RESULTS

We found that overall 10% rejection rate can be reduced by mainly concentrating on two areas of defect like compression height variation and part damages. We have provided some suggestion related to defect types. So by taking corrective and effective measure it is possible to meet nearer to zero defects.

VIII.CONCLUSION

Minimization of defect and rework is an important factor ensuring the quality of product. The importance of automotive industry in the economy is high. So manufacturing the quality product is essential to sustain in the global market. Customer satisfaction depends on quality of product. Good quality results in good establishment of brand name, good providers and builds reputation in market. We should know that 1 % defect leads to 100% defective for customer to buy product. This study indicates eliminating non-value added activity like rework, man hour spent on rework and taking effective measures will enhance the net profit, saves time and improve overall quality of product.

References

Md.Mazadul Islam, Improvement in the apparel industry, International journal of engineering applied science, Jan 2013, volume (1). Tanvir Ahmed, Application of Pareto analysis to reduce defect in garment industry, International journal of modern engineering, volume (3), December 2013. MayankJha, Reduction of rejection components assembly line, scholar research library, volume 2(3), 2013. Suresh, AL MOE AND AB ABU, Defect reduction in piston manufacturing plant, Journal of industrial and intellectual information, volume 3, march 2013. Sanjay kumar, Scrap reduction using TQM method, International journal of industrial engineering, volume 16(4), 2009. Dalgobind, Application of root cause analysis, Journal of industrial engineering and management, Volume 01(02), 2008. E V Jijo, Application of six sigma methodology in grinding process, Quality and reliability engineering, 10.1002. Afzal Matathil, Reduction of scrap in electronic assembly line, SASTECH Journal, volume11, issue 2, sept 2012. Pramod AK, Productivity improvement in piston manufacturing plant, SASTECH JOURNAL, volume 4, sep2012. Dr. JA DOSHI, Root cause analysis for radiator refection, International journal of engineering research and application , volume 2, issue6, 2012.