Quality Control

1. Quality Control

2. Quality Foundations • To move to Quality means different things to different people. • Quality- The processes and tools used to measure and record the degrees of quality achieved in production. • Statistical process control- Technique in which the degree of variation in a product’s charts is recorded with statistically determined limits.

3. W. Edwards Deming • States that Improving Quality would reduce rework and mistakes, and this would lead to improved production effectiveness and higher productivity. • Customers respond to better quality and lower prices, which results in market share increases that help make companies profitable and provide more jobs. • States that Variation is the Enemy. • Natural variations (common causes that are inherent to the process) are part of all processes.

4. Joseph Juran • Scholar of Quality • Four categories of cost related to quality that companies can use to better understand where they spend money on quality. • They are prevention, appraisal, internal failure, and external failure costs. • These can be used to highlight problem areas and begin the process of quality-cost reduction.

5. Armand Feigenbaum and Kaoru Ishikawa • TQM- Total Quality Management • Quality leadership with a strong focus on planning is essential to a successful quality system. • Replaced outside consultants with trained employee experts. • The commitment of quality needs to be supported by skilled consultants and the continuous training and motivation of employees.

6. Philip Crosby • The statistical tools available to companies cannot be used effectively before a receptive corporate culture exists. • Quality must be defined and a plan must be developed for improving quality. These must be conveyed to everyone in the company in a way that they can all understand it.

7. Philip Crosby The four statements that define his quality framework: • Quality must be defined as conformance to requirements, not goodness • The system for causing quality is prevention of defects • The performance standard for quality is zero defects • The measurement of quality is the price of nonconformance, not indexes

8. Philip Crosby • Unlike Quality proponents that came before him, his programs were not a motivational system. He taught companies how to use statistics and a fundamental change in design and operational philosophies to improve quality.

9. Philip Crosby In addition to this he introduced the concepts of: • Cost of Non-quality • Price of Conformance (POC) • Price of Nonconformance (PONC)

10. Philip Crosby – 14 steps • Committee for planning Zero Defects Day • Zero Defects Day • Goal setting • Error cause removal • Recognition • Quality council • Do it over again • Management Commitment • Quality Improvement Team • Quality Education • Quality Measurement • Cost of Quality • Quality Awareness • Corrective actions 14 Steps

11. Philip Crosby The quality process involves four major elements: • Appropriate technology at all levels in the enterprise to control and measure critical quality parameters. • Good design that permits manufacturing and assembly with near-zero defects. • Management understanding of all quality-related issues and the commitment to strive for a defect-free operation within the enterprise. • Broad workforce training and involvement of every employee in the effort to reach the quality goals.

12. TOTAL QUALITY MANAGEMENT • DEFINITION • A TERM COINED TO DESCRIBE JAPENESE-STYLE MANAGEMENT APPROACHES TO QUALITY IMPROVEMENT. • A MANAGEMENT APPROACH TO LONG TERM SUCCES THROUGH CUSTOMER SATISFACTION

13. TOTAL QUALITY MANAGMENT • TWO COMPONENTS • THE PRINCIPLES OF TQM • TQM IMPLEMENTATION PROCESS

14. THE PRINCIPLES OF TQM • CUSTOMER FOCUS • PROCESS FOCUS • PREVENTION FOCUS • WORKFORCE MOBILIZTION FOCUS • FACT-BASED DECISION MAKING FOCUS • CONTINUOUS FEEDBACK FOCUS

15. Implementation process • 5 STEP PROCESS • PREPARATION • PLANNING • ASSESSMENT • IMPLEMENTATION • Process action teams • EVANGELIZATION

16. Quality tools and processes • The goal of every manufacturer is to produce items correctly the first time • 15 to 30 cents per sales dollar are lost due to fixing poor production the traditional way • Correcting quality problems before the product is manufactured costs less then 5 cents per sales dollar

17. Statistical Quality Control • Acceptance Sampling • Process Control or Control Charts • Data can be • Attribute Data (e.q. defects) • Variable Data: measured characteristics (e.g. height)

18. Statistical Process Control • The name statistical process control implies that statistical analysis of manufactured parts will be used to control and improve the manufacturing process. • SPC is a group of statistical methods used to • Measure • Analyze • regulate • a production process to reduce defects. • Defect is defined as any variation of a required characteristic of the product or part that deviates sufficiently from the nominal value to prevent the product or part from fulfilling the physical and functional requirements of the customer.

19. Statistical Process Control (SPC) cont’d Based on Normal statistical distribution (variation from mean is predictable) Data is collected to calculate means and standard deviations SD are used to set Upper and Lower acceptable limits Variable characteristics are specified by the designer as a normal value ( target ) and a tolerance about the target (variability) Histograms are used to produce and display the different values and help approximate its normal distribution.

20. Normal distribution curve

21. Statistical Process Control (SPC) cont’d • Control charts are constructed to track variation • Control charts: • define acceptable process parameters • predict when process is changing • shows when statistical control of process is reached • monitoring the process stability

22. Statistical Process Control (SPC) cont’d • Measured quantities: • X-charts - show sample averages • R - charts show moving ranges • Attributes • c-charts - no. of defects in a part • p - charts - percentage of defective parts

23. C- Chart

24. Solving SPC Problems • 1. Problem Identification: Problems in quality are detected by the operator, in downstream operations, or at inspection. Techniques used in problem identification include Pareto analysis, control charts, and process capability studies. • 2. Identification of cause(s): The cause(s) of the problem usually results from a process element such as people, tools, machines, material, or process methods. Investigation of the problems often includes cause-and-effect analysis using an Ishikawa diagram. If industrial experiments are needed to help differentiate among interrelated influencing factors, Taguchi techniques for experiment design are used.

25. Solving SPC Problems • 3. Problem Correction: The range of possible corrective actions, from a simple machine adjustment to redesign of a complete process, is broad. In addition to the corrective action, a verification that the fix has corrected the problem must be performed. • 4. Maintaining control: After the problems are corrected, process control is achieved by using either statistical methods or physical systems. The statistical technique uses control charts, and the physical system uses instructions embedded in hardware and software. Constant improvement in the system is possible only if the corrections to the system are maintained.