The effects of performance feedback on the implementation of a statistical process control (SPC) program (original) (raw)
Related papers
Quality Improvement With Statistical Process Contro l in the Automotive Industry
2016
In this context of a worldwide market opening, the economy defies firms with numerous challenges, is no longer enough to produce, the current principles are based on quality as a condition for achieving productivity and competitiveness. And given that the quality is not static, it is constantly being changed, and because customers are increasingly demanding, any business organization that aims to be competitive it has to innovate. In the competitive environment in which we live organizations increasingly seek to produce quality at the lowest possible cost, to ensure their own survival. One response to this claim is the Statistical Process Control (SPC) a powerful management method which enables quality improvement and waste elimination. This paper suggests the improvement of the quality of a process through the use of SPC in an enterprise of the automotive industry makes a brief review of concepts related with the methodology and aims to demonstrate all the advantages associated wit...
An Economic Approach to the Management of High-Quality Processes
2012
Modern manufacturing developments have forced researchers to investigate alternative quality control techniques for highquality processes. The cumulative count of conforming (CCC) control chart is a powerful alternative approach for monitoring high-quality processes for which traditional control charts are inadequate. This study develops a mathematical model for the economic design of the CCC control chart and presents an application of the proposed model. On the basis of the results of the application, the economic and classical CCC control chart designs of the CCC control chart are compared. The optimal design parameters for different defective fractions are tabulated, and a sensitivity analysis of the model is presented for the CCC control chart user to determine the optimal economic design parameters and minimum hourly costs for one production run according to different defective fractions, cost, time, and process parameters.
Implimantation of Statistical Process Control in Small Scale Industries-A
2015
SPC have been introduced into a vast number of companies around the world in the last decades. The methods and practicesof process control in manufacturing help companies to continually meet and exceed the needs of their customers in providing highquality products at a low price. Quality has become one of the most important customer decision factors in the selection among the competing product and services. Consequently, understanding and improving quality is a key factor leading to business success, growth and an enhanced competitive position. Hence quality improvement program should be an integral part of the overall business strategy. Quality has become one of the most important customer decision factors in the selection among the competing product and services. Consequently, understanding and improving quality is a key factor leading to business success, growth and an enhanced competitive position. Hence quality improvement program should be an integral part of the overall busin...
2019
In order to survive in a competitive market, improving quality and productivity of product or process is a must for any company. The principal aim of this study is about identifying the practices and challenges of a company in applying statistical process control (SPC) tools in the production processing line and on final product in order to improve the quality of the product and suggesting appropriate solution for the challenges. The approach used in this study is direct observation, thorough examination of production process lines, and information has been collected from managements, quality department and from company's workers working in the area of production process through interview and questionnaire. Pareto chart/analysis and control chart was constructed in order to prioritize the major defects occurred and to suggest a suitable control limits for some variables. From the analysis of the data, it has been found that the company has many practices like usage of control charts, Usage of computerized technology for data recording, usage of calibrated measuring devices, Planning for quality improvement, Presence of in house technical staff experts and setting definition for quality are in use in the organization etc. and challenges specifically like there is lack of higher management support, lack of team working, lack training etc. If a statistical process control practices are employed effectively, it could improve the quality of the product and overall organizational performance by knowing the customer requirement and meeting them. Even if the company has many constraints to implement all suggestion for improvement within short period of time, but it is important to give training for employs and management commitment is important and the company recognized that the suggestion will provide significant productivity improvement in the long run.
Improving Quality with Basic Statistical Process Control (SPC) Tools: A Case Study
Jurnal Teknologi, 2001
In order to survive in a competitive market, improving quality and productivity of product or process is a must for any company. Some simple techniques like the "seven basic quality control(QC) tools" provide a very valuable and cost effective way to meet these objectives. This paper presents a case study in which a local plastic injection moulding company deployed some part of the "seven basic quality control(QC) tools" to significantly improved the monthly defect quality from 13.49% to 7.4%. However, to make them successful as cost effective and problem solving tools, strong commitment from top management is required.
Statistical quality control a modern introduction
John Wiley & Sons, Inc.
Dr. Montgomery has research and teaching interests in engineering statistics including statistical quality-control techniques, design of experiments, regression analysis and empirical model building, and the application of operations research methodology to problems in manufacturing systems. He has authored and coauthored more than 190 technical papers in these fields and is the author of twelve other books. Dr. Montgomery is a Fellow of the American Society for Quality, a Fellow of the American Statistical Association, a Fellow of the Royal Statistical Society, a Fellow of the Institute of Industrial Engineers, an elected member of the International Statistical Institute, and an elected Academican of the International Academy of Quality. He is a Shewhart Medalist of the American Society for Quality, and he also has received the Brumbaugh Award, the Lloyd S. Nelson Award, the William G. Hunter Award, and two Shewell Awards from the ASQ. He is a recipient of the Ellis R. Ott Award. He is a former editor of the Journal of Quality Technology, is one of the current chief editors of Quality and Reliability Engineering International, and serves on the editorial boards of several journals.
A CASE STUDY OF QUALITY CONTROL CHARTS IN A MANUFACTURING INDUSTRY
collection of problem solving tools and the most sophisticated useful method in achieving process stability and improving the process capability through the reduction of variability. In the manufacturing process, every product doesn't meet the desired range of quality consistently with the customer specification. This inconsistency occurs due to several sources of variations such as machines, operators, materials etc. The Ultimate target of control chart is to monitor the variations, and subsequently control the process. On account of applying SPC methods, this study deals with the control and improvement of the quality of bolt by inspecting the bolt's height, diameter and weight from a bolt manufacturing company. In this inspection, we have developed X bar chart, S and Range control chart for each three variables. Furthermore, we have also focused on Estimated Weighted Moving Average (EWMA) for detecting small process shifts and multivariate Hotelling's T 2 for simultaneous monitoring of height and diameter of bolt. These inspections show that either the process is in control or out of control. For the out of control situation, the assignable reasons behind it should be identified and prevented by taking necessary steps.