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Dr. Dipayan Das Assistant Professor Dept. of Textile Technology Indian Institute of Technology Delhi Phone: +91-11-26591402 E-mail: Dipayan@textile.iitd.ac.in Statistical Quality Control in Textiles Module 1: Introduction to Quality and Quality Control
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Introduction to Quality
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Concept of Quality Simply, quality refers to one or more desirable characteristics that a product should possess. Quality is inversely proportional to (unwanted) variability. Product A Product B
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Quality Characteristics Every product possesses a number of properties that jointly describe what the user or consumer thinks of as quality. These properties are known as quality characteristics. For example, fiber length is known to be one of the important quality characteristics of a fiber.
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Quality Cost Preventing, detecting and dealing with defects cause costs that are called quality costs or costs of quality. Quality costs can be broken down into four broad groups. (1). Prevention Costs: product/process design. Process control. Burn-in. Training. Quality data acquisition and analysis.
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Quality Cost (Continued) (2). Appraisal Costs: Inspection and test of incoming material. Product inspection and test. Material and services consumed. Maintaining accuracy of test equipment. (3). Internal failure Costs: Scrap Rework Retest
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Failure analysis Downtime Yield losses Downgrading/ off-spacing (4). External failure costs: Complaint adjustment Returned product/material Liability costs External costs Quality Cost (Continued)
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Quality history [1] YearEvent 1700-1900Quality was largely determined by the efforts of an individual craftsman. 1915-1919WWI- British government began a supplier certification program. 1919Technical Inspection Association was formed in England, this later becomes the Institute of Quality Assurance. 1924W A Shewhart introduced the concept of control charts in Bell Laboratories technical memorandum. 1928Accepatance sampling techniques were developed and refined by H. F. Dodge and H. G. Romig at Bell Labs. 1931W. A. Shewhart published Economic control of quality of manufactured product – outlining statistical methods for use in production and control chart methods. 1932-1933British textile industry began use of statistical techniques for product/process development. 1944 Industrial Quality Control began publication. 1954E. S. Page introduced CUSUM control chart.
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Quality history (Continued) YearEvent 1960The concept of quality control circle was introduced in japan by K. Ishikawa. 1960The zero defects (ZD) programs are introduced in US induatries. 1975-1978The concept of total quality management (TQM) was developed in the US. 1989The journal Quality Engineering was appeared. 1989Motorola’s six sigma initiative began
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Introduction to Quality Control
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Concept of quality control Quality control describes the directed use of testing to measure the achievement of a specified standard. Quality control is a superset of testing, although it often used synonymously with testing. The concept of quality, namely that the object, the service, the performance – whatever it is – should be “fit for purpose”. Quality does not mean being at the top of the range, but it does mean being efficient (so things happen on time and on cost), reliable (whatever the weather, every day of the week) and giving good value for money. “The goal of quality control should be to identify process steps that best predict outcomes” - A. Blanton Godfrey
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Link Among Quality, Productivity, and Cost Take an example. A ring frame machine produces 1000 cops per day. The production cost per cop is Rs. 15. It is seen that 75% of the cops conform to specifications and 60% of the non-conforming cops can be reworked at an additional expense of Rs. 5 per cop, the rest 40% of the nonconforming cops is scrapped. The cost per good cop is then After implementation of process control program, it is seen that 80% of the cops conform to specifications and 60% of the non-conforming cops can be reworked at additional expense of Rs. 5 per cop, the rest is required to be scrapped. The cost per good cop is then
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Quality Control Methodology Statistical process control Statistical product control Six sigma Total quality management (TQM) Total quality assurance (TQA) Note: TQM and TQA are beyond the scope of this course.
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Statistical Process Control Statistical process control involves measurement and analysis of process variation by using statistical techniques namely control charts. This is most often used for manufacturing processes, in the intent of statistical process control is to monitor product quality and maintain processes to fixed targets.
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Statistical Product Control Statistical Product Control involves in making dispositions on accepting or rejecting a lot (or batch) of product that has already been produced. It is most often used to evaluate products that are received from outside sources and where it is not possible to implement statistical process control.
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Six Sigma Technical products with many complex components typically have many opportunities for failure or defects to occur. Motorola developed the six-sigma program as a response to the demand for such products. The focus of six sigma lies in reducing variability in key product quality characteristics to the level at which failure or defects are extremely unlikely.
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Frequently Asked Questions & Answers
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Q1: A ring-spun yarn shows more strength variability that a rotor-spun yarn. Can we say that the ring-spun yarn offers better strength quality than the rotor-spun yarn? A1: Yes Q2: Is it so that the application of statistical techniques for quality control in textiles has started recently? A2: No, the British textile industry began use of statistical techniques for product/process development in 1932-1933. Q3: Why quality control is at all required? A3: Effective quality improvement can result in increase in productivity and reduction in cost.
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References 1.Montgomery, D. C., Introduction to Statistical Quality Control, John Wiley & Sons, Inc., Singapore, 2001.
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Sources of Further Information 1.Montgomery, D. C., Introduction to Statistical Quality Control, John Wiley & Sons, Inc., Singapore, 2001. 2.Grant, E. L. and Leavenworth, R. s., Statistical Quality Control, Tata McGraw Hill Education Private Limited, New Delhi, 2000. 3.Leaf, G. A. V., Practical Statistics for the Textile Industry: Part I, The Textile Institute, UK, 1984. 4.Leaf, G. A. V., Practical Statistics for the Textile Industry: Part II, The Textile Institute, UK, 1984.
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