Mod1 9-ns4

1

COURSE MATERIAL FOR VTU: By: Prof.N.S.Narahari, Director – Placement and Training, R.V.College of Engineering, RV Vidyaniketan Post, 8th Mile, Mysore Road, Bangalore – 560 059.

CONTENT SHEET:

Sessions Description Page Nos.

Session 1 Basics of Quality : ��

��

��

3-21

Session 2 �� 23-24 Session 3 �� !��

�� "��#��

26-27

Session 4 �� $��

�� $�� 29-30

Session 5 �� $�� "�

��

��

32-53

Session 6 ��%��!��

#��

��

55-61

Session 7 !��

��&��

63-68

Session 8� ��%��%�� $��

��%�

70-76

Session 9� ��%�� 78-91

2

Session No.1:

Basics of Quality

3

Course Material of VTU EDUSAT Program:

Session 1 :

1.0 : Definitions and Meaning of Quality

Definition

Quality means fitness for use.

Quality is inversely proportion to variability - This is a modern definition of quality

• This is a traditional definition

• Quality of design

• Quality of conformance

The Transmission Example

Definition

Quality Improvement is the reduction of variability in processes and product.

• The transmission example illustrates the utility of this definition

• An equivalent definition is that quality improvement is the elimination of waste. This is useful in service or transactional businesses.

1.1 : The Eight Dimensions of Quality

1. Performance

2. Reliability

3. Durability

4. Serviceability

5. Aesthetics

6. Features

4

7. Perceived Quality

8. Conformance of Standards

• Suppliers and supply chain management must be involved

• Must focus on all three components: Quality Planning, Quality Assurance, and Quality Control & Improvement

1.2 : Terminology

Every product possesses a number of elements that jointly describe what the user or consumer thinks of as quality. These parameters are often called quality characteristics. Sometimes these are called critical-to-quality (CTQ) characteristics. Quality characteristics may be of several types:

1. Physical: length, weight, voltage, viscosity.

2. Sensory: taste, appearance, color.

3. Time Orientation: reliability, durability, serviceability,

Since variability can only be described in statistical items, statistical methods play a central role in quality improvement efforts. In the application of statistical methods to quality engineering, it is fairly typical to classify data on quality characteristics as either attributes or variables data. Variables data are usually continuous measurements, such as length, voltage, or viscosity. Attributes data, on the other hand, are usually discrete data, often taking the form of counts. We will describe statistical – based quality engineering tools for dealing with both types of data.

• Specifications

– Lower specification limit

– Upper specification limit

– Target or nominal values

• Defective or nonconforming product

• Defect or nonconformity

• Not all products containing a defect are necessarily defective

5

1.3 : History of Quality Improvement :

7

1.4 : Statistical Methods for Quality Control and Improvement

Production process inputs and outputs

Statistical Methods

• Statistical process control (SPC)

– Control charts, plus other problem-solving tools

– Useful in monitoring processes, reducing variability through elimination of assignable causes

– On-line technique

• Designed experiments (DOX)

– Discovering the key factors that influence process performance

– Process optimization

– Off-line technique

• Acceptance Sampling

8

Walter A. Shewart (1891-1967)

• Trained in engineering & physics

• Long career at Bell Labs

• Developed the first control chart about 1924

A factorial experiment with three factors

Variations of acceptance sampling

9

1.5 : Management aspects of Quality Improvement

Effective management of quality requires the execution of three activities:

1. Quality Planning

2. Quality Assurance

3. Quality Control and Improvement

1.6 : Quality planning is a strategic activity, and it is just as vital to an organization’s long-term business success as the product development plan, the financial plan, the marketing plan, and plans for the utilization of human resources. Without a strategic quality plan, an enormous amount of time, money, and effort will be wasted by the organization dealing with faulty designs, manufacturing defects, field failures, and customer complaints. Quality planning involves identifying customers, both external and those that operate internal to the business, and identifying their needs (this is sometimes called listening to the voice of the customer). Then product or services that meet or exceed customer expectations must be developed. The Organizations must then determine how these products and services will be realized. Planning for quality improvement on a specific, systematic basis is also a vital part of this process.

1.7 : Quality assurance is the set of activities that ensures the quality levels of products and services are properly maintained and that supplier and customer quality issues are properly resolved. Documentation of the quality system is an important component. Quality system documentation involved four components: policy, procedures, work instructions and specifications, and records. Policy generally deals with what is to be done and why, while procedures focus on the methods and personnel that will implement policy. Work instructions and specifications are usually product-, department-, tool-, or machine-oriented. Records are a way of documenting the policies, procedures, and work instruction that have been followed. Records are also used to track specific units or

10

batches of products, so that it can be determine exactly how they were produced. Records are often vital in providing data for dealing with customer complaints, corrective actions, and, it necessary, product recalls. Development, maintenance, and control of documentation are important quality assurance functions. One example of document control is ensuring that specifications and work instructions developed for operating personnel reflects the latest design and engineering changes.

1.8 : Quality control and improvement involve the set of activities used to ensure that the products and services meet requirements and are improved on a continuous basis. Since variability is often a major source of poor quality, statistical techniques, including SPC and designed experiments, are the major tools of quality control and improvement. Quality improvement is often done on a product-by-project basis and involved teams led by personnel with specialized knowledge of statistical methods and experience in applying them. Projects should be selected so that they have significant business impact and are linked with the overall business goals for quality identified during the planning process. The techniques in this book are integral to successful quality control and improvement.

11

1.9 : Quality Philosophies and Management Strategies

W. Edwards Deming

• Taught engineering, physics in the 1920s, finished PhD in 1928

• Met Walter Shewhart at Western Electric

• Long career in government statistics, USDA, Bureau of the Census

• During WWII, he worked with US defense contractors, deploying statistical methods

• Sent to Japan after WWII to work on the census

Deming

• Deming was asked by JUSE to lecture on statistical quality control to management

• Japanese adopted many aspects of Deming’s management philosophy

• Deming stressed “continual never-ending improvement”

• Deming lectured widely in North America during the 1980s; he died 24 December 1993

Deming’s 14 Points

1. Create constancy of purpose toward improvement

2. Adopt a new philosophy, recognize that we are in a time of change, a new economic age

3. Cease reliance on mass inspection to improve quality

4. End the practice of awarding business on the basis of price alone

5. Improve constantly and forever the system of production and service

6. Institute training

7. Improve leadership, recognize that the aim of supervision is help people and equipment to do a better job

8. Drive out fear

9. Break down barriers between departments

10. Eliminate slogans and targets for the workforce such as zero defects

11. Eliminate work standards

12. Remove barriers that rob workers of the right to pride in the quality of their work

13. Institute a vigorous program of education and self-improvement

14. Put everyone to work to accomplish the transformation

12

Deming’s Deadly Diseases 1. Lack of constancy of purpose

2. Emphasis on short-term profits

3. Performance evaluation, merit rating, annual reviews

4. Mobility of management

5. Running a company on visible figures alone

6. Excessive medical costs for employee health care

7. Excessive costs of warrantees

Joseph M. Juran

• Born in Romania (1904), immigrated to the US

• Worked at Western Electric, influenced by Walter Shewhart

• Emphasizes a more strategic and planning oriented approach to quality than does Deming

• Juran Institute is still an active organization promoting the Juran philosophy and quality improvement practices

The Juran Trilogy

1. Planning

2. Control

3. Improvement

• These three processes are interrelated

• Control versus breakthrough

• Project-by-project improvement

Some of the Other “Gurus”

• Kaoru Ishikawa

– Son of the founder of JUSE, promoted widespread use of basic tools

• Armand Feigenbaum

– Author of Total Quality Control, promoted overall organizational involvement in quality,

– Three-step approach emphasized quality leadership, quality technology, and organizational commitment

• Lesser gods, false prophets

13

Total Quality Management (TQM) • Started in the early 1980s, Deming/Juran philosophy as the focal point

• Emphasis on widespread training, quality awareness

• Training often turned over to HR function

• Not enough emphasis on quality control and improvement tools, poor follow-through, no project-by-project implementation strategy

• TQM was largely unsuccessful

• TQM is “just another program”

• Value engineering

• Zero defects

• “Quality is free”

1.10 : Quality Systems and Standards

The International Standards Organization (founded in 1946 in Geneva, Switzerland), known as ISO, has developed a series of standards for quality systems. The first standards were issued in 1987. The current version of the standard is known as the ISO 9000 series. It is a generic standard, broadly applicable to any type of organization, and it is often used to demonstrate a supplier’s ability to control its processes. The three standards of ISO 9000 are:

• ISO 9000:2000 Quality Management System – Fundamental and Vocabulary

• ISO 9000:2000 Quality Management System – Requirements

• ISO 9000:2000 Quality Management System – Guidelines for Performance improvement

The ISO 9001:2000 standard has eight clauses: (1) Scope, (2) Normative References, (3) Definitions, (4) Quality Management Systems, (5) Management Responsibility, (6) Resource Management, (7) Product (or service) Realization, and (8) Measurement, Analysis, and Improvement. To become certified under the ISO standard, a company must select a register and prepare for a certification audit by this registrar. There is no single independent authority that license, regulates, monitors, or qualifies registrars. As we will discuss later, this is a serious problem with the ISO system. Preparing for the certification audit involved many activities including (usually) an initial or phase I audit that checks the present quality management system against the standard. This is usually followed by establishing teams to ensure that all components of the key clause are developed and implemented, training of personnel, developing applicable documentation, and developing and installing all new components of the quality system that may be required. Then the certification audit takes placed. If the company is certified, then periodic surveillance audits by the registrar continue, usually on an annual (or perhaps six months) schedule.

14

The ISO certification process focuses heavily on quality assurance, without sufficient weight given to quality planning and quality control and improvement

There is also evidence that ISO certification or certification under one of the other industry-specific standards does little to prevent poor quality products from being designed, manufactured, and delivered to t he customer. For example, in 1999-2000, there were numerous incidents of rollover accidents involving Ford Explorer vehicles equipped with Bridgestone / Firestone tires and there were nearly 300 deaths in the United States alone attributed to these accidents, which les to a recall by Bridgestone / Firestone of approximately 6.5 million tires. Apparently, many of the tires involved in these incidents were manufactured at the Bridgestone / Firestone plant in Dectur, Illionis. In an article on this story in Time magazine (Sept. 18, 2000), there was a photograph (p.38) of the sign at the entrance of the Decatur plant which stated that the plant was “QS 9000 Certifies” and ISO 14001 Certified” (ISO 14001 is an environmental standard). Although the assignable causes underlying these incidents have not been fully discovered, there are clear indicators that despite quality systems certification, Bridgestone / Firestone experienced significant quality problems

The Malcolm Baldrige National Quality Award

The Malcolm Baldrige National Quality Award (MBNQA) was created by the US Congress in 1987. It is given annually to recognize US corporations for performance excellence. Awards are given to organizations in five categories: manufacturing, service, small business, health care, and education. Three awards many be given each year in each category. Many organizations compete for the awards, and many companies use the performance excellence criteria for self-assessment. The award is administered by NIST (the National Bureau of Standards and Technology).

• The MBNQA process is a valuable assessment tool

• See Table 1-3 for Performance Excellence Criteria and point values

16

1.11 : Six Sigma

• Use of statistics & other analytical tools has grown steadily for over 80 years

– Statistical quality control (origins in 1920, explosive growth during WW II, 1950s)

– Operations research (1940s)

– FDA, EPA in the 1970’s

– TQM (Total Quality Management) movement in the 1980’s

– Reengineering of business processes (late 1980’s)

– Six-Sigma (origins at Motorola in 1987, expanded impact during 1990s to present)

Focus of Six Sigma is on Process Improvement with an Emphasis on Achieving Significant Business Impact

• A process is an organized sequence of activities that produces an output that adds value to the organization

• All work is performed in (interconnected) processes

– Easy to see in some situations (manufacturing)

– Harder in others

• Any process can be improved

• An organized approach to improvement is necessary

• The process focus is essential to Six Sigma

17

Why “Quality Improvement” is Important: A Simple Example

• A visit to a fast-food store: Hamburger (bun, meat, special sauce, cheese, pickle, onion, lettuce, tomato), fries, and drink.

• This product has 10 components - is 99% good okay?

1.12 : Six Sigma Focus

• Initially in manufacturing

• Commercial applications

– Banking

– Finance

– Public sector

– Services

• DFSS – Design for Six Sigma

18

– Only so much improvement can be wrung out of an existing system

– New process design

– New product design (engineering)

Some Commercial Applications

• Reducing average and variation of days outstanding on accounts receivable

• Managing costs of consultants (public accountants, lawyers)

• Skip tracing

• Credit scoring

• Closing the books (faster, less variation)

• Audit accuracy, account reconciliation

• Forecasting

• Inventory management

• Tax filing

• Payroll accuracy

Six Sigma

• A disciplined and analytical approach to process and product improvement

• Specialized roles for people; Champions, Master Black belts, Black Belts, Green Belts

• Top-down driven (Champions from each business)

• BBs and MBBs have responsibility (project definition, leadership, training/mentoring, team facilitation)

• Involves a five-step process (DMAIC) :

• Define

• Measure

• Analyze

• Improve

• Control

What makes it Work?

• Successful implementations characterized by:

– Committed leadership

– Use of top talent

19

– Supporting infrastructure

• Formal project selection process

• Formal project review process

• Dedicated resources

• Financial system integration

• Project-by-project improvement strategy (borrowed from Juran)

1.13: The Process Improvement Triad: DFSS, Lean, and DMAIC

DFSS Matches Customer Needs with Capability

• Mean and variability affects product performance and cost

– Designers can predict costs and yields in the design phase

• Consider mean and variability in the design phase

– Establish top level mean, variability and failure rate targets for a design

– Rationally allocate mean, variability, and failure rate targets to subsystem and component levels

– Match requirements against process capability and identify gaps

– Close gaps to optimize a producible design

– Identify variability drivers and optimize designs or make designs robust to variability

OVERALL PROGRAMS

LEAN Variation Reduction

• Predictability

• Feasibility • Efficiency • Capability • Accuracy

• Flow Mapping • Waste Elimination • Cycle Time • WIP Reduction • Operations and Design

Lean

Lead-time Capable

DMAIC

ELIMINATE WASTE, IMPROVE

CYCLE TIME

DESIGN PREDICTIVE

QUALITY INTO PRODUCTS

ELIMINATE DEFECTS, REDUCE

VARIABILITY

DFSS

Robust

• Requirements allocation • Capability assessment • Robust Design • Predictable Product Quality

Design for Six Sigma

The “I” in DMAIC may become DFSS

20

• Process capability impact design decisions

DFSS enhances product design methods.

Lean Focuses on Waste Elimination

• Definition

– A set of methods and tools used to eliminate waste in a process

– Lean helps identify anything not absolutely required to deliver a quality product on time.

• Benefits of using Lean

– Lean methods help reduce inventory, lead time, and cost

– Lean methods increase productivity, quality, on time delivery, capacity, and sales

DMAIC Solves Problems by Using Six Sigma Tools

• DMAIC is a problem solving methodology

• Use this method to solve problems:

– Define problems in processes

– Measure performance

– Analyze causes of problems

– Improve processes−remove variations and non value-added activities

– Control processes so problems do not recur

Six Sigma

• DMAIC is closely related to the Shewhart cycle (variously called the Deming cycle, or the PDCA cycle)

21

Legal Aspects of Quality • Product liability exposure

• Concept of strict liability

1. Responsibility of both manufacturer and seller/distributor

2. Advertising must be supported by valid data

Implementing Quality Improvement

• A strategic management process, focused along the eight dimension of quality

22

��'�"(� ��

��

23

Session 2 : Quality Costs : 2.1 : Introduction :

One measure of the performance of the total quality system is the cost associated with it. Careful identification, measurement, and analysis of cost as a function of time aids in tracking the impact of an effective quality control system. Remember that the benefits of a quality system, as measured by the total quality costs, may be realized in the long run rather than in the short run. The full impact of a particular change in the process is usally only felt later.

The American Society for Quality Control has defined four major categories for Quality Costs :

2.2 : Prevention Costs : Prevention costs are incurred in planning, implementing, and maintaining a quality system. They include salaries and developmental costs for product design, process and equipment design, process control techniques (through such means as control charts), information systems design, and all other costs associated with making the product right the first time.

• Quality planning and engineering

• New Products review

• Product / Process design

• Process control

• Burn-in

• Training

• Quality data acquisition and analysis

2.3 : Internal Failure Costs : Internal failure costs are incurred when products, components, materials and services to fail to meet quality requirements prior to the transfer of ownership to the customer. These costs would disappear if there were no non-conformities in the product. Internal failure costs include scrap and rework costs for the materials, labor and overhead associated with production. The cost of correcting nonconforming units, as in rework, can include such additional manufacturing operations as regrinding the outside diameter of an oversized part.

• Scrap

• Rework

• Retest

• Failure Analysis

• Downtime

24

• Yield losses

• Downgrading (off-spacing)

2.4 : Appraisal Costs : Appraisal costs are those associated with measuring, evaluating, or auditing products, components, or purchases materials to determine their degree of conformance to the specified standards. Such costs include dealing with the inspection and test of incoming materials as well as product inspection and testing at various phases of manufacturing and at final acceptance. Other costs in this category include the cost of calibrating and maintaining measuring instruments and equipment and the cost of materials and products consumed in a destructive test or devalued by reliability tests.

• Inspection and test of incoming material

• Product inspection and test

• Materials and services consumed

• Maintaining accuracy of test equipment

2.5 : External Failure Costs :

External Failure costs are incurred when the product does not perform satisfactorily after ownership is transferred to the customer. If no nonconforming units were produced, this costs of investigation and adjustments, and those associated with receipt, handling, repair and replacement of nonconforming products.

• Complaint adjustment

• Returned product / material

• Warranty charges

• Liability costs

• Indirect costs

The Management of Quality Costs :

How large are quality costs ? The answer, of course, depends on the type of organization and the success of their quality improvement effort. In some organizations quality costs are 4% or 5% of sales, while in others they can be as high as 35% or 40% of sales. Obviously, the cost of quality will be very different for a high technology computer manufacturer than for a typical service industry, such as a department store or hotel chain. In most organizations, however, quality costs are higher than necessary, and management should make continuing efforts to appraise, analyze, and reduce these costs.

The usefulness of quality costs stems from the leverage effect ; that is, dollars invested in prevention and appraisal have a payoff in reducing dollars incurred in internal and external failures that exceeds the original investment. For example, a dollar invested in

25

prevention may return $10 or $100 (or more) in savings from reduced internal and external failures.

Quality cost analyses have as their principal objective cost reduction through identification of improvement opportunities. This is often done with a Pareto Analysis. The Pareto analysis consists of identifying quality costs by category, or by product, or by type of defect or nonconformity. For example, inspection of the quality cost information in Table 1-3 concerning defects or nonconformities in the assembly of electronic components onto printed circuit boards reveals that insufficient solder is the highest quality cost incurred in this operation. Insufficient solder accounts for 42% of the total defects in this particular type of board, and for almost 52% of the total scrap and rework costs. If the wave solder process can be improved, then there will be dramatic reductions in the cost of quality.

How much reduction in quality costs is possible? While the cost of quality in many organizations can be significantly reduced, it is unrealistic to expect it can be reduced to zero. Before that level of performance is reached, the incremental costs of prevention and appraisal will rise more rapidly than the resulting cost reductions. However, a quality cost program applied in conjunction with a good quality improvement effort has the capability of reducing quality costs by 50% or 60% provided that no organized effort has previously existed. This cost reduction also follows the Pareto principle; that is, most of the cost reductions will come from attacking the few problems that are responsible for the majority of quality costs.

Monthly Quality Costs Information for Assembly of Printed Circuit Boards

Type of Defect Percent of Total Defects

Scrap and Rework Costs

Insufficient Solder 42 $37,500.00 (52%)

Misaligned Components

21 12,000.00

Defective Components

15 8,000.00

Missing Components 10 5,100.00

Cold solder joints 7 5,000.00

All other causes 5 4,600.00

Totals 100 $72,200.00

26

��'�")� ��

��

27

Session 3 : Principles of Quality 3.1 : Sporadic vs. Chronic Quality Problems : Sporadic problems : Short term with generally dramatic, identifiable results Addressed by traditional quality “control” methods - control charts, Pareto analysis, etc. - sampling inspection methods

Solutions are usually already in the arsenal

Chronic problems : Systematic “waist” in the system Requires traditional and more complex analysis - time and resources (people involved) Requires new approaches (DOE, failure mode analysis, etc.)

3.2 : Quality Function Deployment :

• A quality assurance tool for profit and non-profit organizations aimed at locating customer needs and transcending those needs into product/service production stages, ensuring that customer needs are delivered in the end.

Quality Function Deployment :

Purpose

• Translate consumer’s voice into technical design requirements

• Determine & prioritize customer needs

• Translate customer needs to product design parameters

• Coordinate efforts and skills of an organization from a project’s inception to its completion

• Ensure customer expectations

• Avoid manufacturing catastrophe

28

Building the House of Quality : Step 1: Prepare customer requirements list

Step 2: Prioritize customer requirements list

Step 3: Translate Requirements to quantifiable measures

Step 4: Determine “How” Measurement

Step 5: Prepare correlation matrix

Step 6: Determine What and How relationships

Step 7: Determine design characteristics importance

Step 8: Evaluate current competitors

Step 9: Identify benchmarks

Step 10: Determine target values

Step 11: New design evaluation

29

��'�"*� ��

�� $��

30

Session 4 : Quality Assurance Systems : 4.1 : Quality planning is a strategic activity, and it is just as vital to an organization’s long-term business success as the product development plan, the financial plan, the marketing plan, and plans for the utilization of human resources. Without a strategic quality plan, an enormous amount of time, money, and effort will be wasted by the organization dealing with faulty designs, manufacturing defects, field failures, and customer complaints. Quality planning involves identifying customers, both external and those that operate internal to the business, and identifying their needs (this is sometimes called listening to the voice of the customer). Then product or services that meet or exceed customer expectations must be developed. The Organizations must then determine how these products and services will be realized. Planning for quality improvement on a specific, systematic basis is also a vital part of this process.

4.2 : Quality assurance is the set of activities that ensures the quality levels of products and services are properly maintained and that supplier and customer quality issues are properly resolved. Documentation of the quality system is an important component. Quality system documentation involved four components: policy, procedures, work instructions and specifications, and records. Policy generally deals with what is to be done and why, while procedures focus on the methods and personnel that will implement policy. Work instructions and specifications are usually product-, department-, tool-, or machine-oriented. Records are a way of documenting the policies, procedures, and work instruction that have been followed. Records are also used to track specific units or batches of products, so that it can be determine exactly how they were produced. Records are often vital in providing data for dealing with customer complaints, corrective actions, and, it necessary, product recalls. Development, maintenance, and control of documentation are important quality assurance functions. One example of document control is ensuring that specifications and work instructions developed for operating personnel reflects the latest design and engineering changes.

4.3 : Quality control and improvement involve the set of activities used to ensure that the products and services meet requirements and are improved on a continuous basis. Since variability is often a major source of poor quality, statistical techniques, including SPC and designed experiments, are the major tools of quality control and improvement. Quality improvement is often done on a product-by-project basis and involved teams led by personnel with specialized knowledge of statistical methods and experience in applying them. Projects should be selected so that they have significant business impact and are linked with the overall business goals for quality identified during the planning process. The techniques in this book are integral to successful quality control and improvement.

TQM : Policy deployment, involve supplier & customers, involve all operations, process management, performance measurement, team work, employee involvement. Management Aspects of Quality Improvement Effective management of quality requires the execution of three activities:

1. Quality Planning

31

2. Quality Assurance

3. Quality Control and Improvement

4.4: QUALITY CONTROL – QUALITY ASSURANCE

• Quality Control is REACTIVE whereas Quality Assurance is PROACTIVE

• Quality Control deals with DETECTION Quality Assurance deals with PREVENTION

i.e. All the planned and systematic actions necessary to prevent problems and ensure confidence that the product will satisfy the requirements for quality

4.5 : QUALITY ASSESSMENT

Comparison of a Quality Management System with the requirement system with the requirements of a standard or standards to determine the degree of compliance with the specified requirements

4.6 : QUALITY ASSURANCE

Part of Quality Management, focused on providing confidence that Quality requirements will be fulfilled ISO 9000: 2000

4.7 : QUALITY MANAGEMENT SYSTEMS

Management System to direct and control an Organization with regard to Quality

ISO 9000 : 2000

32

��'�"+� ��

Quality Audit

33

Session 5 : Quality Audit 5.1 : QUALITY AUDIT

systematic, independent and documented process for obtaining audit evidence and evaluating it objectively to determine the extent to which the audit criteria are fulfilled

ISO 19011 : 2002

AUDIT CRITERIA

Set of policies, procedures or requirements

AUDIT EVIDENCE

Records, statements of fact or other information, which are relevant to the audit criteria and verifiable

AUDITS

Objectives

• Determination of Compliance with specified Requirements

• Identification of Weakness

• Management Tool for Improvement

Planned and Independent

Defined Standards and / or Procedures

5.2 : AUDIT OBJECTIVES

• To determine Compliance or Non-Conformity of the Quality System elements with specified requirements

• To determine the effectiveness of the implemented Quality System in meeting Quality objectives

• To afford an opportunity to improve the Quality System

• To meet regulatory Requirements

• To Permit the listing of the Audited Organization in the Register of Audited Companies

AUDITS

1st PARTY INTERNAL

2nd PARTY EXTERNAL

3rd PARTY EXTRINSIC

34

PRODUCT PROCESS

SERVICE SYSTEM

QUALITY FINANCIAL

ENVIRONMENTAL

1st PARTY INTERNAL

• Required by ISO and Other Standards

• Any Trained personnel can be used

• Documentation Awareness

• Timing / Timescales easily adjusted to suit individuals

• Advice / Assistance with corrective actions

• Must not replace responsibility for Quality

2nd PARTY EXTERNAL

• Supplier or Sub-Contractor approval

• Quality Personnel-Role

• Choice of Standards

• Timing / Timescales more important

• Team Leader’s Authority

• The power of the contract

3rd PARTY EXTRINSIC

• Totally Independent

• International / National Standards

• Qualified or Registered Assessors

• Timing / Timescales very important

• Team Leader only Recommends

5.3 : CONDUCT OF THE AUDIT

• Enter the area

• Introductions by guide

• Explain what you want to see

35

• Investigate to the depth necessary

• No problems found, move on

• Don’t keep on auditing until problems are found

SPECIFIED REQUIREMENTS

• Customer requirements

• Quality system requirements

– Manuals

– Procedures / work instructions

• Quality standard

• Legal requirements – statutory, regulatory or industry body

• Regulations of registration body

5.4 : AUDIT PROGRAMME RESPONSIBILITIES

Those assigned the responsibility for managing the audit programme should

• Establish the objective and extent of the audit programme

• Establish the responsibilities and procedures, and ensure resources are provided

• Ensure the implementation of the audit programme

• Ensure that appropriate audit programme records are maintained, and

• Monitor, review and improve the audit programme

AUDIT PROGRAMME RESOURCES

When identifying resources for the audit programme, consideration should be given to

• Financial resources necessary to develop, implement, manage and improve audit activities

• Audit techniques

• Process to achieve and maintain the competence of auditors, and to improve auditor performance

• The availability of auditors and technical experts having competence appropriate to the particular audit programme objectives

• The extent of the audit programme and

• Travelling time, accommodation and other auditing needs

AUDIT PROGRAMME PROCEDURES

Audit programme procedures should address the following

36

• Planning and scheduling audits

• Assuring the competence of auditors and audit team leaders

• Selecting appropriate audit teams and assigning their roles and responsibilities

• Conducting audits

• Conducting audit follow-up, if applicable

• Maintaining audit programme records

• Monitoring the performance and effectiveness of the audit programme

• Reporting to top management on the overall achievements of the audit programme

5.5 : AUDIT PROGRAMME IMPLEMENTATION

The implementation of an audit programme should address the following:

• Communicating the audit programme to relevant parties

• Coordinating and scheduling audits and other activities relevant to the audit programme

• Establishing and maintaining a process for the evaluation of the auditors and their continual professional development

• Ensuring the selection of audit teams

• Providing necessary resources to the audit teams

• Ensuring the conduct of audits according to the audit programme

• Ensuring the control of records of the audit activities

• Ensuring review and approval of the audit reports, and ensuring their distribution to the audit client and other specified parties

• Ensuring audit follow-up, if applicable

5.6 : AUDIT PROGRAMME RECORDS

Records should be maintained to demonstrate the implementation of the audit programme and should include the following:

• Records related to individual audits, such as

– Audit plans

– Audit reports

– Nonconformity reports

– Corrective and preventive action reports, and

– Audit follow-up reports, if applicable

• Results of audit programme review

37

• Records related to audit personnel covering subjects such as

– Auditor competence and performance evaluation

– Audit team selection, and

– Maintenance and improvement of competence

5.7 : AUDIT PROGRAMME MONITORING AND REVIEWING

The audit programme review should consider, for example

• Results and trends from monitoring

• Conformity with procedures

• Evolving needs and expectations of interested parties

• Audit programme records

• Alternative or new auditing practices, and

• Consistency in performance between audit teams in similar situations

5.8 : AUDITOR ATTRIBUTES : The following are the attributes that must be possessed by an Auditor of Quality Systems :

• Must be proficient in sector

• Proficient in auditing Top Management

• Proficient in legal requirements

• Understand the process

• Understand the interaction of process

• Team player

Local Requirements

• Culture

• Practices

• Approach

Auditors must be flexible to -

• Changing situations

• Differing Management styles

• Differing Management / Employee levels

Auditors must be competent in -

• Reasoning of Non-Conformities

38

• Evaluating effectiveness of corrective action

• Open minded

• Tenacious

• Diplomatic

• Decisive

• Observant

• Self reliant

• Perceptive

• Ethical

5.9 : AUDITORS RESPONSIBILITIES

• Developing the audit schedule

• Ensure team is always punctual

• The agreed programme is adhered to

• Valid restrictions are observed

• Team members complete designated tasks

• Confidentiality is preserved

• Arguments are avoided

• No criticism is levelled at individuals

• Chairs all meetings:- opening, review, team and closing

• Summarize findings

• Makes recommendation

• Files audit report

5.10 : AUDITOR DUTIES

• Support the team leader

• Prepare checklist

• Arrive on time

• Participate at opening meeting

• Carry out assigned tasks

• Keep to the timetable

• Document all findings

• Keep auditee informed

• Assist team leader with reports

39

• Safeguard all documents

• Maintain confidentiality

5.11 : AUDITOR TRAINING

Auditor Training should consider the following:

• Knowledge & Understanding of the standards used to Audit Quality Systems

• Audit Techniques such as Examining, Questioning, Evaluating and Reporting

• Additional skills needed to manage an audit

E.g.: Planning, Organizing, Communicating and Directing

5.12 : COMMUNICATION

� The imparting, conveying or exchanging of ideas, knowledge etc. whether by speech, writing or sings.

� Ensure that the message given is received……. and understood

� Message content

� Words spoken

� Verbal style and sound

� Non-verbal

Facial expression

Body language

5.13 : THE AUDIT CYCLE

PREPARATIONS

� Documentation Review

� Preliminary visit

� Audit Planning

PERFORMANCE

� Opening Meeting

� Gathering Information

� Team Meetings

� Non-Conformity Reporting

� Closing Meeting

FOLLOW-UP ACTIONS

40

� Audit Report

� Corrective Action Verification

� Surveillance

THE OPENING MEETING

• Introductions

• Confirm Standard, Scope and Audit Authority

• Confirm Audit Plan and Other arrangements

• Outline Audit Method

• Confirm Guides and their Authority

• Confirm Confidentiality

• Staff / Employee Issues

• Any Relevant Questions

• Close Meeting

TEAM MEETINGS

• Discuss the Findings of Team

• Team Leader Agrefs:

– Non-Conformities

– Wording

– Categorization

• Resolve any Issues

• Identify any modifications to the programme as a result of the findings to Date

OBJECTIVE

Ensure that the Team presents a unified response at the wash-up meeting

WASH-UP MEETINGS

• Presentation of findings to Date

• Resolution of any issues

• Agree Non-Conformity Categorization

• Obtain signatures and possible corrective action completion dates

• Monitor Audit Progress

• Monitor Auditor / Company interrelationships

41

• Keep everyone informed. No surprises at the closing meeting

CLOSING MEETING AGENDA

• Thank Company and Guides

• Confirm Standard and Scope

• Disclaimer

• Confirm Confidentiality

• Define Categories of Non-Conformities

• Questions Deferred

• Findings Presented

• Team Leaders Summary

• Recommendations

• Questions Answered

• Corrective Action Dates Agreed

• Close Meeting

RECOMMENDATIONS

The Company’s Quality System:

• Meets the Requirements of ISO 9001:2000 Registration to the agreed scope will be recommended

• Will meet the requirements of ISO 9001:2000 Registration will be deferred until the completion and verification of the necessary corrective actions

• Does not meet the requirements of ISO 9001: 2000 Registration cannot be recommended

FOLLOW-UP ACTIONS

• Deferred Registration

Close out or Down rate all outstanding Major / Hold point Non-Conformities. Clear as many Minor / On-Going improvements as possible

• Routine Surveillance visits

• Re-Registration

AUDIT REPORT

• Report Identification

• Purpose, Objective and Scope of the Audit

• Details of Auditors, Dates etc

42

• Reference documents (e.g. Quality Manual, Procedures)

• Summary of Audit Results as declared at the Closing Meeting

• Details of all Non-Conformities and Observations

• Reference to any additional supporting Evidence

• Recommendations

• Conclusions

• Distribution

NONCONFORMITY

A situation where there is likelihood that nonconforming product or service will occur, or where the benefits of the management standard are not being realized, because of the absence of, or lack of adherence to a procedure

• Non fulfillment of a requirement

• Specified requirements

– conditions of contract

– quality standard

– quality manual

– procedures

– legal regulatory requirements

• Manual is not conforming with the quality standard …(intent)

• Practice is not in line with the intent …(implementation)

• Practice is not effective ….(effectiveness)

OBJECTIVE EVIDENCE

• Data supporting the existence or verity of something – ISO 9000 : 2000

• May be obtained through observation, measurement, test or other means

• May be stated or (preferably) documented

• Can be verified

ESTABLISH THE FACTS

• Get help form the auditee

• Discuss concerns

• Verify the findings

43

• Record all the evidence:

– exact observation

– where, what, etc…

• Establish why a nonconformity or otherwise

• State who (if relevant) – preferably by job title

• Use auditee’s terminology

• Make it retrievable

• Make it helpful

• Make it concise

CONSIDER THE SERIOUSNESS

Two questions to be answered -

• What could go wrong if the nonconformity remains uncorrected

• What is the likelihood of such a thing going wrong

THE PURPOSE OF NCR’S

� To convey your findings to the company in a clear, concise and accurate way so that they know exactly what needs to be done

� To provide a record that gives an accurate picture which can subsequently be reviewed remotely from the company

� To ensure that another auditor can follow up the corrective action on your findings just as easily as you would yourself

NCR WORDING

� Report exactly what you observed

� Give a factual report, not a commentary or opinion

� Write legibly – If you can’t – then print

� Choose your words with care for easy reading

� Avoid the use of adjectives and adverbs

� Try to use words and phrases taken from the chosen paragraph of the standard

� Choose the requirement paragraph with care as a guide to corrective action

� Establish “TRACEABILITY” in your report. Be specific – Quote Details

� Report accurately – But no personal criticism

� Be sure that your report is based on “UNSHAKEABLE” facts

44

CERTIFICATION

2000 by an accredited certification body which approves then registers or certifies the supplier resulting in:

Issue of a Certificate

Entry in the DTI Register

Use of LOGO on Literature

NOTE

CERTIFICATION BODIES DO NOT ACCREDITATE SUPPLIERS

ACCREDITATION

The term Accreditation in the context of Quality Systems is used to denote certification bodies who’s ability to audit against the requirements of ISO 9000 has been independently audited by a National Authority using agreed criteria

5.14 : ISO Brief - International Standards for sustainable World

• A German company wins a huge contract to sell components to a factory in North Carolina.

• A Swiss firm becomes the leading supplier of power line filters in the U.S.

• A Japanese electronics conglomerate outbids several European manufacturers for a project in South America.

• These are not isolated events, but rather an indication that we have entered a new age in commerce.

• Today, more and more business and industry leaders realize that in order to thrive, or even survive, in the new global economy, their companies must become truly world-class.

• And that means quality.

• Quality in your products and services. Quality in your practices and procedures. Quality you maintain and you can prove - because it is documented.

• Quality as a competitive weapon.

• And that is the reason for the growing move to ISO 9000 certification.

• The best companies are starting to insist on it. Your competitors may already be pursuing it. And if you plan to do business in Europe or Japan, it is absolutely essential.

• The race for ISO certification has already started. In the first half of 2003, it is estimated that over 60,000 European companies are registered in compliance with

45

the ISO 9000 standards. In the U.S., over 1000 companies have been certified. (In 2005, the number of certified companies more than doubled.)

• The term ISO stands for the International Organization for Standardization. You would reasonably assume that it ought to be IOS, but it isn't. Apparently, the term ISO was chosen (instead of IOS), because iso in Greek means equal, and ISO wanted to convey the idea of equality - the idea that they develop standards to place organizations on an equal footing.

5.15 : History of ISO :

The International Standards Organization (ISO), in Geneva, Switzerland, was founded in 1946 to develop a common set of standards in manufacturing, trade and communications.

• It is composed of the national standards institutes and organizations of 97 countries worldwide, including the American National Standards Institute (ANSI).

• The ISO publishes thousands of standards, but the ISO 9000 series is having a major impact on international trade.

• First published in 1987, the standards have been rapidly adopted by organizations in Europe, Asia and North America. In addition, there is a movement by several industries in the EEC where ISO certification is now a prerequisite to product certification. And that trend is growing.

• The standards have been endorsed by the American Society of Quality Control, the European Standards Institutes, and by the Japanese Industrial Standards Committee.

• In the U.S., the American Society for Quality Control runs the Registrar Accreditation Board (RAB), which is accountable to ISO when it comes to certification. The RAB has recognized over 40 certification bodies that have trained certified auditors.

5.16 : ISO : Definition

ISO is the world’s leading developer of International Standards

ISO standards are designed to be implemented worldwide.

ISO standards specify the requirements

• for state-of-the-art products, services,

• processes, materials and systems,

• and for good conformity assessment,

• managerial and organizational practice

47

5.17 : Documentation is at the core of ISO 9000 conformance. In fact, the standards have been described as this:

• "Say what you do. Do what you say. Write it down."

• ISO 9000 is a set of international standards for both quality management and quality assurance that has been adopted by over 90 countries worldwide.

• The ISO 9000 standards apply to all types of organizations, large and small, and in many industries.

• The standards require:

• A standard language for documenting quality practices.

• A system to track and manage evidence that these practices are instituted throughout the organization.

• A third-party auditing model to review, certify and maintain certification of organizations.

• The ISO 9000 series classifies products into generic product categories: hardware, software, processed materials and services.

• ISO 9000 - Explains fundamental quality concepts and provides guidelines for the selection and application of each standard.

• ISO 9001 - Model for quality assurance in design, development, production, installation and servicing.

• ISO 9004 - Guidelines for the applications of standards in quality management and quality systems.

48

• The ISO 9000 series classifies products into generic product categories: hardware, software, processed materials and services.

• ISO 9000 - Explains fundamental quality concepts and provides guidelines for the selection and application of each standard.

• ISO 9001 - Model for quality assurance in design, development, production, installation and servicing.

• ISO 9004 - Guidelines for the applications of standards in quality management and quality systems.

• Simply stated, the ISO 9000 standards define "quality" in ways that have been recognized and accepted worldwide.

• The goal is to increase customer confidence in the quality system used by their suppliers. The standards are designed to:

• Establish consistent language and terminology

• Provide baseline quality practices that are accepted internationally

• Reduce the need for costly on-site supplier assessments

• It doesn't matter what size they are or what they do.

• It can help both product and service oriented organizations achieve standards of quality that are recognized and respected throughout the world.

• ISO 9000 standards don't tell you how to run your business. They only define the critical documented elements that must be taken into consideration to produce a quality product.

5.18 : Purpose of ISO :

• ISO's purpose is to facilitate international trade by providing a single set of standards that people everywhere would recognize and respect.

• The purpose of ISO 9001 is to assure customers that suppliers can provide quality products and services.

• You need to control the quality of your products and services.

• You need to reduce the costs associated with poor quality.

• Your customers want you to become certified.

• Your markets expect you to be certified.

• Your competitors are already certified

49

Standards and guidelines Purpose

ISO 9000:2000, Quality management systems - Fundamentals and vocabulary

Establishes a starting point for understanding the standards and defines the fundamental terms and definitions used in the ISO 9000 family which you need to avoid misunderstandings in their use.

ISO 9001:2000, Quality management systems - Requirements

This is the requirement standard you use to assess your ability to meet customer and applicable regulatory requirements and thereby address customer satisfaction.

It is now the only standard in the ISO 9000 family against which third-party certification can be carried.

ISO 9004:2000, Quality management systems - Guidelines for performance improvements

This guideline standard provides guidance for continual improvement of your quality management system to benefit all parties through sustained customer satisfaction.

ISO 19011, Guidelines on Quality and/or Environmental Management Systems Auditing (currently under development)

Provides you with guidelines for verifying the system's ability to achieve defined quality objectives. You can use this standard internally or for auditing your suppliers.

ISO 10005:1995, Quality management - Guidelines for quality plans

Provides guidelines to assist in the preparation, review, acceptance and revision of quality plans.

ISO 10006:1997, Quality management - Guidelines to quality in project management

Guidelines to help you ensure the quality of both the project processes and the project products.

ISO 10007:1995, Quality management - Guidelines for configuration management

Gives you guidelines to ensure that a complex product continues to function when components are changed individually.

50

ISO/DIS 10012, Quality assurance requirements for measuring equipment - Part 1: Metrological confirmation system for measuring equipment

Give you guidelines on the main features of a calibration system to ensure that measurements are made with the intended accuracy.

ISO 10012-2:1997, Quality assurance for measuring equipment - Part 2: Guidelines for control of measurement of processes

Provides supplementary guidance on the application of statistical process control when this is appropriate for achieving the objectives of Part 1.

ISO 10013:1995, Guidelines for developing quality manuals

Provides guidelines for the development, and maintenance of quality manuals, tailored to your specific needs.

NOTE : Most people assume Accreditation and Certification to be the same thing – they are not

51

5.19 : A Systematic Approach To Quality Auditing

(3) Plus 2nd check on documentation

Repeat cycle as necessary

SELECT (1)

DOCUMENTED?

DOC’N SATISFACTORY?

(2)

PRACTICE SATISFACTORY?

(3)

COMPLETE?

END

RAISE NC FORM

(1) A Process or an element of Q. system

(2) 1st check only

No

No

No

Yes

52

NO

NO

NCR IDENTIFIED

NCR ISSUED

PROBLEM INVESTIGATED CORRECTIVE ACTION PLANNED

CORRECTIVE ACTION IMPLEMENTED

CORRECTIVE ACTION VERIFIED BY AUDIT

NOTIFY CERTIFICATION BODY

CORRECTIVE ACTION VERIFIED BY CERTIFICATION BODY

OK NCR ISSUED

YES

YES

3rd Party Audit

53

5.20 : NON – COMPLIANCE REPORT

STANDARD: AREA: NCR NO. NON COMPLIANCE: (TO BE FILLED BY ASSERSSOR)

PROPOSED CORRECTIVE ACTION: (TO BE FILLED BY ASSESSEE)

ASSESSOR ASSESSEE MR DATE

IMPLEMENTED CORRECTIVE ACTION: (TO BE FILLED BY ASSESSOR)

ROOT CAUSE ANALYSIS BY: (TO BE FILLED BY ASSESSEE)

ASSESSOR ASSESSEE MR DATE FOLLOW UP COMMENTS: (TO BE FILLED BY ASSESSOR)

Six Sigma Focus

• Initially in manufacturing

• Commercial applications

– Banking

– Finance

– Public sector

– Services

• DFSS – Design for Six Sigma

– Only so much improvement can be wrung out of an existing system

– New process design

54

– New product design (engineering)

Some Commercial Applications

• Reducing average and variation of days outstanding on accounts receivable

• Managing costs of consultants (public accountants, lawyers)

• Skip tracing

• Credit scoring

• Closing the books (faster, less variation)

• Audit accuracy, account reconciliation

• Forecasting

• Inventory management

• Tax filing

• Payroll accuracy

55

Session No.6:

Method and Philosophy of Statistical Process Control

56

Session 6 : Method and Philosophy of Statistical Process Control 6.1 : Basic SPC Tools

SPC can be applied to any process. Its seven major tools are

1. Histogram or stem-and –leaf plot

2. Check sheet

3. Pareto chart

4. Cause-and-effect diagram

5. Defect concentration diagram

6. Scatter diagram

7. Control chart

In any production process, regardless of how well designed or carefully maintained it is, a certain amount of inherent or natural variability will always exist. This natural variability or “background noise” is the cumulative effect of many small, essential unavoidable causes.

A process that is operating with only chance cause of variation present is said to be in statistical control.

A process that is operating in the presence of assignable cause is said to be out of control.

e.g. improperly adjusted or controlled machines, operator errors, or defective raw material.

6.2 : Chance and Assignable causes of Quality Variation

• A process is operating with only chance causes of variation present is said to be in statistical control.

• A process that is operating in the presence of assignable causes is said to be out of control.

57

6.3 : Statistical Basis of the Control Chart

• A control chart contains

– A center line

– An upper control limit

– A lower control limit

• A point that plots within the control limits indicates the process is in control

– No action is necessary

• A point that plots outside the control limits is evidence that the process is out of control

– Investigation and corrective action are required to find and eliminate assignable cause(s)

• There is a close connection between control charts and hypothesis testing

58

Photolithography Example

• Important quality characteristic in hard bake is resist flow width

• Process is monitored by average flow width

– Sample of 5 wafers

– Process mean is 1.5 microns

– Process standard deviation is 0.15 microns

• Note that all plotted points fall inside the control limits

– Process is considered to be in statistical control

The process mean is 1.5 microns, and the process standard deviation is σ = 0.15 microns. Now if sample of size n = 5 are taken, the standard deviation of the sample average � is

0671.05

15.0 ===nx

σσ

59

Therefore, if the process is in control with a mean flow width of 1.5 microns, then by using the central limit theorem to assume that � is approximately normally distributed, we would expect 100 (1-α)% of the sample mean � to fall between

)0671.0(5.1 2αZ+ and )0671.0(5.1 2αZ− . We will arbitrarily choose the constant

2αZ to be 3, so that the upper and lower control limits become

UCL = 1.5 + 3(0.0671) = 1.7013

and

LCL = 1.5 - 3(0.0671) = 1.2987

As shown on the control chart. These are typically called “three-signma”2 control limits. Shewhart Control Chart Model. We may give a general model for a control chart. Let w be a sample statistic that measures some quality characteristic of interest, and suppose that the mean of w is µw and the standard deviation of w is σw. Then the centre line, the upper control limit, and the lower control limit become

UCL = µw + Lσw

Centre line = µw

LCL = µw - Lσw

Where L is the “distance” of the control limits from the centre line, expressed in standard deviation units. This general theory of control charts was first proposed by Walter A. Shewhart, and control charts developed according to these principles are often called Shewhart control charts.

The most important use of a control chart is to improve the process. We have found that, generally,

1. Most processes do not operate in a state of statistical control.

60

2. Consequently, the routine and attentive use of control charts will identify assignable causes. If these causes can be eliminated from the process, variability will be reduced and the process will be improved.

This process improvement activity using the control chart is illustrated

3. The control chart will only detect assignable causes. Management, operator and engineering action will usually be necessary to eliminate the assignable causes.

61

More Basic Principles

• Charts may be used to estimate process parameters, which are used to determine capability

• Two general types of control charts

– Variables (Chapter 5)

• Continuous scale of measurement

• Quality characteristic described by central tendency and a measure of variability

– Attributes (Chapter 6)

• Conforming/nonconforming

• Counts

• Control chart design encompasses selection of sample size, control limits, and sampling frequency

62

6.3 : Typical control chart

• Points plot within the control limits & no nonrandom pattern : process is in control, no action is necessary.

• A point plots outside of the control limits or random pattern exists : process is out of control, investigation and correction action are required to eliminate the assignable cause.

• Type I error of the control chart : the process is out of control when it is really in control.

• Type II error of the control chart : the process is in control when it is really out of control.

6.4 : Types of Process Variability

• Stationary and uncorrelated − data vary around a fixed mean in a stable or predictable manner

• Stationary and autocorrelated − successive observations are dependent with tendency to move in long runs on either side of mean

• Nonstationary − process drifts without any sense of a stable or fixed mean

6.5 : Reasons for Popularity of Control Charts

1. Control charts are a proven technique for improving productivity.

2. Control charts are effective in defect prevention.

3. Control charts prevent unnecessary process adjustment.

4. Control charts provide diagnostic information.

5. Control charts provide information about process capability.

63

��'�",� ��

Control Chart Theory

64

Session 7 : Control Chart Theory : 7.1 : Basic Principles

• Charts may be used to estimate process parameters, which are used to determine capability

• Two general types of control charts

– Variables (Chapter 5)

• Continuous scale of measurement

• Quality characteristic described by central tendency and a measure of variability

– Attributes (Chapter 6)

• Conforming/nonconforming

• Counts

• Control chart design encompasses selection of sample size, control limits, and sampling frequency

7.2 : Typical control chart

• Points plot within the control limits & no nonrandom pattern: process is in control, no action is necessary.

• A point plots outside of the control limits or random pattern exists: process is out of control, investigation and correction action are required to eliminate the assignable cause.

• Type I error of the control chart: the process is out of control when it is really in control.

• Type II error of the control chart : the process is in control when it is really out of control.

7.3 : Types of Process Variability

• Stationary and uncorrelated − data vary around a fixed mean in a stable or predictable manner

• Stationary and auto correlated − successive observations are dependent with tendency to move in long runs on either side of mean

• Nonstationary − process drifts without any sense of a stable or fixed mean

65

7.4 : Reasons for Popularity of Control Charts

1. Control charts are a proven technique for improving productivity.

2. Control charts are effective in defect prevention.

3. Control charts prevent unnecessary process adjustment.

4. Control charts provide diagnostic information.

5. Control charts provide information about process capability.

7.5 : Choice of Control Limits

• 3-Sigma Control Limits

– Probability of type I error is 0.0027

• Probability Limits

– Type I error probability is chosen directly

– For example, 0.001 gives 3.09-sigma control limits

• Warning Limits

– Typically selected as 2-sigma limits

66

Another way to evaluate the decisions regarding sample size and sampling frequency is through the average run length (ARL) of the control chart. Essentially, the ARL is the average number of points that must be plotted before a point indicates an out-of-control condition. If the process observations are uncorrelated, then for any Shewhart control chart, the ARL can be calculated easily from

PARL

1=

Where p is the probability that any point exceeds the control limits. This equation can be used to evaluate the performance of the control chart.

To illustrate, for the � chart with three-sigma limits, p = 0.0027 is the probability that a single point falls outside the limits when the process is in control. Therefore, the average run length of the � chart when the process is in control (called ARL0) is

3700027.011

0 ===P

ARL

That is, even if the process remains in control, an out-of-control signal will be generated every 370 samples, on the average.

The use of average run lengths to describe the performance of control charts has been subjected to criticism in recent years. The reasons for this arise because the distribution of run length for a Shewhart control chart is geometric distribution. Consequently, there are two concerns with ARL: (1) the standard deviation of the run length is very large, and (2) the geometric distribution is very skewed, so the mean of the distribution (the ARL) is not necessarily a very “typical” value of the run length.

For example, consider the Shewhart � control chart with three-sigma limits. When the process is in control, we have noted the p = 0.0027 and the in-control ARL0 is ARL0 = 1/p = 1/0.0027 = 370. This is the mean of the geometric distribution. Now the standard deviation of the geometric distribution is

67

( ) ( ) 3700027.00027.011 ≅−=− pp

That, is the standard deviation of the geometric distribution in this case is approximately equal to its mean. As a result, the actual ARL0 observed in practice for the Shewhart � control chart will likely vary considerably. Furthermore, for the geometric distribution with p = 0.0027, the 10th and 50th percentiles of the distribution are 38 and 256, respectively. This mean that approximately 10% of the time the in-control run length will be less than or equal to 38 samples and 50% of the time it will be less than or equal to 256 samples. This occurs because the geometric distribution with p = 0.0027 is quite skewed to the right.

It is also occasionally convenient to express the performance of the control chart in terms of its average time to signal (ATS). If samples are taken at fixed intervals of time that are h hours apart, then

ATS = ARL.h

Consider the piston-ring process discussed earlier, and suppose we are sampling every hour. Equation 4-3 indicates that we will have a false alarm about every 370 hours on the average. .

Now consider how the control chart performs in detecting shifts in the mean. Suppose we are using a sample size of n = 5 and that when the process goes out of control the mean shifts to 74.015 mm. From the operating characteristic curve, we find that if the process mean is 74.015 mm, the probability of � falling between the control limits, is approximately 0.50. 'Therefore, p in equation 4-2 is 0.50, and the out-control ARL (called ARL1) is

25.0

111 ===

PARL

This is, the control chart will require two samples to detect the process shift, on the average, and since the time interval between samples is h = 1 hour, the average time required to detect this shift is

ATS = ARL1h = 2(1) = 2 hours

Suppose that this is unacceptable, because production of piston rings with mean flow width of 1.725 microns results in excessive scrap costs and can result in further upstream manufacturing problems. How can we reduce the time needed to detect the out-of-control condition? One method is to sample more frequently. For example, if we sample every half hour, then the average time to signal for this scheme is ATS = ARL1 h = 2(½) = 1; that is, only one will elapse (on the average) between the shift and its detection. The second possibility is to increase the sample size. For example, if we use n = 10, then Fig. shows that the probability of � falling between the control limits when the process mean is 1.725 microns is approximately 0.1, so that p = 0.9, and from equation 4-2 the out-of-control ARL or ARL1 is

11.19.0

111 ===

PARL

and, if we sample every hour, the average time to signal is

68

ATS = ARL1 h = 1.11(1) = 1.11 hours

Thus, the larger sample size would allow the shift to be detected about twice as quickly as the old one. If it became important to detect the shift in the (approximately) first hour after it occurred, two control chart designs would work:

Design 1 Design 2

Sample Size: n = 5 Sample Size: n = 10

Sampling Frequency: every half hour Sampling Frequency: every hour

7.6 : Rational Subgroups

• The rational subgroup concept means that subgroups or samples should be selected so that if assignable causes are present, chance for differences between subgroups will be maximized, while chance for difference due to assignable causes within a subgroup will be minimized.

• Two general approaches for constructing rational subgroups:

1. Sample consists of units produced at the same time − consecutive units

– Primary purpose is to detect process shifts

2. Sample consists of units that are representative of all units produced since last sample − random sample of all process output over sampling interval

– Often used to make decisions about acceptance of product

– Effective at detecting shifts to out-of-control state and back into in-control state between samples

– Care must be taken because we can often make any process appear to be in statistical control just by stretching out the interval between observations in the sample.

70

��'�"-� ��

Interpretation of Control Charts

71

Session No.8 : Interpretation of Control Charts 8.1 : Analysis of Patterns on Control Charts

• Pattern is very nonrandom in appearance

• 19 of 25 points plot below the center line, while only 6 plot above

• Following 4th point, 5 points in a row increase in magnitude, a run up

• There is also an unusually long run down beginning with 18th point

72

The Western Electric Handbook (1956) suggests a set of decision rules for detecting nonrandom patterns on control charts. Specifically, it suggests concluding that the process is out of control if either

1. One point plots outside the three-sigma control limits;

2. Two out of three consecutive points plot beyond the two-sigma warning limits;

3. Four out of five consecutive points plot at a distance of one-sigma or beyond from the center line;

4. Eight consecutive points plot on one side of the centre line.

8.2 : Discussion of Sensitizing Rules for Control Charts

Some Sensitizing Rules for Shewhart Control Charts

Standard Action Signal

1. One or more points outside of the control limits.

2. Two of three consecutive points outside the two-sigma warning limits but still inside the control limits.

3. Four of five consecutive points beyond the one-sigma limits.

4. A run of eight consecutive points on one side of the center line.

5. Six points in a row steadily increasing or decreasing.

6. Fifteen points in a row in zone C (both above and below the center line).

7. Fourteen points in a row alternating up and down.

8. Eight points in a row on both sides of the center line with none in zone C.

9. An unusual or nonrandom pattern in the data.

Western Electric Rules

73

10. One or more points near a warning or control limit.

In general, care should be exercised when using several decision rules simultaneously. Suppose that the analyst uses k decision rules and that criterion i has type I error probability αi. Then the overall type I error or false-alarm probability for the decision based on all k tests is

( )∏=

−−=k

ii

1

11 αα

provided that all k decision rules are independent. However, the independence assumption is not valid with the usual sensitizing rules. Furthermore, the value of a; is not always clearly defined for the sensitizing rules, because these rules involve several observations.

Champ and Woodall (1987) investigated the average run length performance for the Shewhart control chart with various sensitizing rules. They found that the use of these rules does improve the ability of the control chart to detect smaller shifts, but the in control average run length can be substantially degraded. For example, assuming inde-pendent process data and using a Shew-bart control chart with the Western Electric rules results in an in-control ARL of 91.25, in contrast to 370 for the Shewhart control chart alone.

Some of the individual Western Electric rules are particularly troublesome. An illustration is the rule of several (usually seven or eight) consecutive points which either increase or decrease. This rule is very ineffective in detecting a trend, the situation for which it was designed. It done, however, greatly increase the false-alarm rate. See Davis and Woodall (1988) for more details.

8.2 : Phase I and Phase II of Control Chart Application

• Phase I is a retrospective analysis of process data to construct trial control limits

– Charts are effective at detecting large, sustained shifts in process parameters, outliers, measurement errors, data entry errors, etc.

– Facilitates identification and removal of assignable causes

• In phase II, the control chart is used to monitor the process

– Process is assumed to be reasonably stable

– Emphasis is on process monitoring, not on bringing an unruly process into control

Choice of Control Limits

• 3-Sigma Control Limits

– Probability of type I error is 0.0027

• Probability Limits

74

– Type I error probability is chosen directly

– For example, 0.001 gives 3.09-sigma control limits

• Warning Limits

– Typically selected as 2-sigma limits

Another way to evaluate the decisions regarding sample size and sampling frequency is through the average run length (ARL) of the control chart. Essentially, the ARL is the average number of points that must be plotted before a point indicates an out-of-control condition. If the process observations are uncorrelated, then for any Shewhart control chart, the ARL can be calculated easily from

PARL

1=

Where p is the probability that any point exceeds the control limits. This equation can be used to evaluate the performance of the control chart.

To illustrate, for the � chart with three-sigma limits, p = 0.0027 is the probability that a single point falls outside the limits when the process is in control. Therefore, the average run length of the � chart when the process is in control (called ARL0) is

3700027.011

0 ===P

ARL

That is, even if the process remains in control, an out-of-control signal will be generated every 370 samples, on the average.

The use of average run lengths to describe the performance of control charts has been subjected to criticism in recent years. The reasons for this arise because the distribution of run length for a Shewhart control chart is geometric distribution. Consequently, there

75

are two concerns with ARL: (1) the standard deviation of the run length is very large, and (2) the geometric distribution is very skewed, so the mean of the distribution (the ARL) is not necessarily a very “typical” value of the run length.

For example, consider the Shewhart � control chart with three-sigma limits. When the process is in control, we have noted the p = 0.0027 and the in-control ARL0 is ARL0 = 1/p = 1/0.0027 = 370. This is the mean of the geometric distribution. Now the standard deviation of the geometric distribution is

( ) ( ) 3700027.00027.011 ≅−=− pp

That, is the standard deviation of the geometric distribution in this case is approximately equal to its mean. As a result, the actual ARL0 observed in practice for the Shewhart � control chart will likely vary considerably. Furthermore, for the geometric distribution with p = 0.0027, the 10th and 50th percetiles of the distribution are 38 and 256, respectively. This mean that approximately 10% of the time the in-control run length will be less than or equal to 38 samples and 50% of the time it will be less than or equal to 256 samples. This occurs because the geometric distribution with p = 0.0027 is quite skewed to the right.

It is also occasionally convenient to express the performance of the control chart in terms of its average time to singal (ATS). If samples are taken at fixed intervals of time that are h hours apart, then

ATS = ARL.h

Consider the piston-ring process discussed earlier, and suppose we are sampling every hour. Equation 4-3 indicates that we will have a false alarm about every 370 hours on the average. .

Now consider how the control chart performs in detecting shifts in the mean. Suppose we are using a sample size of n = 5 and that when the process goes out of control the mean shifts to 74.015 mm. From the operating characteristic curve, we find that if the process mean is 74.015 mm, the probability of � falling between the control limits, is approximately 0.50. 'Therefore, p in equation 4-2 is 0.50, and the out-control ARL (called ARL1) is

25.0

111 ===

PARL

This is, the control chart will require two samples to detect the process shift, on the average, and since the time interval between samples is h = 1 hour, the average time required to detect this shift is

ATS = ARL1h = 2(1) = 2 hours

Suppose that this is unacceptable, because production of piston rings with mean flow width of 1.725 microns results in excessive scrap costs and can result in further upstream manufacturing problems. How can we reduce the time needed to detect the out-of-control condition? One method is to sample more frequently. For example, if we sample every half hour, then the average time to signal for this scheme is ATS = ARL1 h = 2(½) = 1; that is, only one will elapse (on the average) between the shift and its detection. The

76

second possibility is to increase the sample size. For example, if we use n = 10, then Fig. shows that the probability of � falling between the control limits when the process mean is 1.725 microns is approximately 0.1, so that p = 0.9, and from equation 4-2 the out-of-control ARL or ARL1 is

11.19.0

111 ===

PARL

and, if we sample every hour, the average time to signal is

ATS = ARL1 h = 1.11(1) = 1.11 hours

Thus, the larger sample size would allow the shift to be detected about twice as quickly as the old one. If it became important to detect the shift in the (approximately) first hour after it occurred, two control chart designs would work:

Design 1 Design 2

Sample Size: n = 5 Sample Size: n = 10

Sampling Frequency: every half hour Sampling Frequency: every hour

Rational Subgroups

• The rational subgroup concept means that subgroups or samples should be selected so that if assignable causes are present, chance for differences between subgroups will be maximized, while chance for difference due to assignable causes within a subgroup will be minimized.

• Two general approaches for constructing rational subgroups:

1. Sample consists of units produced at the same time − consecutive units

– Primary purpose is to detect process shifts

2. Sample consists of units that are representative of all units produced since last sample − random sample of all process output over sampling interval

– Often used to make decisions about acceptance of product

– Effective at detecting shifts to out-of-control state and back into in-control state between samples

– Care must be taken because we can often make any process appear to be in statistical control just by stretching out the interval between observations in the sample.

78

��'�".� ��

SEVEN QUALITY CONTROL TOOLS

79

Session No. 9 : SEVEN QUALITY CONTROL TOOLS : The Seven Quality Control tools as proposed by Dr.Kaoru Ishikawa, Professor at Tokyo University & Father of QC in Japan are:

1. Histogram or stem-and-leaf plot

2. Check sheet

3. Pareto chart

4. Cause-and-effect diagram

5. Defect concentration diagram

6. Scatter diagram

7. Control chart

Dr.Kaoru Ishikawa, Professor at Tokyo University & Father of QC in Japan further specified the following approach to Quality Problem solving.

1. Cause Analysis Tools are Cause and Effect diagram, Pareto analysis & Scatter diagram.

2. Evaluation and decision making tools are decision matrix and multivoting

3. Data Collection and analysis tools are check sheet, control charts, DOE, scatter diagram, stratification, histogram, survey.

4. IDEA CREATION TOOLS are Brainstorming, Benchmarking, Affinity diagram, Normal group technique.

5. Project Planning and Implementation tools are Gantt Chart and PDCA cycle.

Cause and effect diagram (also called Ishikawa or fishbone chart)

Description : The fishbone diagram identifies many possible causes for an effect or problem. It can be used to structure a brainstorming session. It immediately sorts ideas into useful categories.

When to Use : When identifying possible causes for a problem.

Especisally when a teams thinking tends to fall into ruts

80

Procedure for constructing Cause and Effect diagram :

Materials required : Flipchart (or) White Board, Marking Pens

Agree on a problem statement (effect). Write it at the center right of the flipchart or whiteboard. Draw a box around it and draw a horizontal arrow running to it.

Brainstorm the major categories of causes of the problem. If this is difficult use generic headings : Methods Machines (equipment) People (manpower) Materials Measurement Environment

Write the categories of causes as branches from the main arrow.

Brainstorming all the possible causes of the problem. Ask: “Why does this happen?” As each idea is given, the facilitator writes it as a branch from the appropriate category. Causes can be written in several places if they relate to several categories.

Again ask “Why does this happen?” About each cause. Write sub-causes branching off the causes. Continue to ask “Why?” And generate deeper levels of causes. Layers of branches indicate causal relationships.

When the group runs out of ideas, focus attention to places on the chart where ideas are few.

Example : This fishbone diagram was drawn by a manufacturing team to try to understand the source of periodic iron contamination. The team used the six generic headings to prompt ideas. Layers of branches show thorough thinking about the causes of the problem.

81

For example, under the heading “Machines,” the idea “materials of construction” shows four kinds of equipment and then several specific machine numbers.

Note that some ideas appear in two different places. “Calibration” shows up under “Methods” as a factor in the analytical procedure, and also under “Measurement” as a cause of lab error. “Iron tools” can be considered a “Methods” problem when taking samples or a “Manpower” problem with maintenance personnel.

Check Sheet (or) Defect Concentration Diagram :

Description : A check sheet is a structured, prepared form for collecting and analyzing data. This is a generic tool that can be adapted for a wide variety of purposes.

When to Use :

When data can be observed and collected repeatedly by the same person or at the same location.

When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes etc.

When collecting data from a production process.

Procedure :

Decide what event or problem will be observed. Develop operational definitions.

Decide when data will be collected and for how long.

82

Design the form. Set it up so that data can be recorded simply by making check marks or Xs or similar symbols and so that data do not have to be recopied for analysis.

Label all spaces on the form.

Test the check sheet for a short trial period to be sure it collects the appropriate data and is easy to use.

Each time the targeted event or problem occurs, record data on the check sheet.

Example : The figure below shows a check sheet used to collect data on telephone interruptions. The tick marks were added as data was collected over several weeks.

Histogram : The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs. The data are numerical values.

To see the shape of the data’s distribution, especially when determining whether the output of a process is distributed approximately normally.

Analyzing whether a process can meet the customers requirements.

Analyzing whether a process can meet the customer’s requirements

Analyzing what the output from a supplier’s process looks like. Whether a process change has occurred from one time period to another.

To determine whether the outputs of two or more processes are different.

To communicate the distribution of data quickly and easily to others.

83

Histogram Shapes and Meaning

Normal : A common pattern is the bell shaped curve known as the “normal distribution” In a normal distribution, points are as likely to occur on one side of the average as on the other.

Skewed : The skewed distribution is asymmetrical because a natural limit prevents outcomes on one side. The distribution’s peak is off center toward the limit and a tail stretches away from it.

Double Peaked or bimodal : The bimodal distribution looks like the back of a two humped camel. The outcomes of two processes with different distributions are combined in one set of data. A two shift operation might be bimodal.

84

Plateau : The plateau might be called a “multimodal distribution”. Several processes with normal distributions are combined. Because there are many peaks close together, the top of the distribution resembles a plateau.

Dog food : The dog food distribution is missing something – results near the average. If a customer receives this kind of distribution, someone else is receiving a heart cut, and the customer is left with the “dog food”, the odds and ends left over after the masters

meal.

85

Pareto Chart

86

Cause-and-Effect Diagram

87

How to Construct a Cause-and-Effect Diagram

1. Define the problem or effect to be analyzed.

2. Form the team to perform the analysis. Often the team will uncover potential causes through brainstorming.

3. Draw the effect box and the center line.

4. Specify the major potential cause categories and join them as boxes connected to the center line.

5. Identify the possible causes and classify them into the categories in step 4. Create new categories, if necessary.

6. Rank order the causes to identify those that seem most likely to impact the problem.

7. Take corrective action.

88

Defect Concentration Diagram

89

Scatter Diagram

Elements of a Successful SPC Prouam

1. Management leadership

2. A team approach

3. Education of employees at all levels

4. Emphasis on reducing variability

5. S. Measuring success in quantitative (economic) terms

6. A mechanism for communicating successful results throughout the organization

Nonmanufacturing Applications of Statistical Process Control

• Nonmanufacturing applications do not differ substantially from industrial applications, but sometimes require ingenuity

1. Most nonmanufacturing operations do not have a natural measurement system

2. The observability of the process may be fairly low

• Flow charts and operation process charts are particularly useful in developing process definition and process understanding. This is sometimes called process mapping.

1. Used to identify value-added versus nonvalue-added activity

90

Ways to Eliminate Nonvalue-Add Activities 1. Rearranging the sequence of work steps

2. Rearranging the physical location of the operator in the system

3. Changing work methods

4. Changing the type of equipment used in the process

5. Redesigning forms and documents for more efficient use

6. Improving operator training

7. Improving supervision

8. Identifying more clearly the function of the process to all employees

9. Trying to eliminate unnecessary steps

10. Trying to consolidate process steps

Operation Process Chart Symbols

= Operation

= Inspection

= Movement or transportation

= Delay

= Storage

91

Important Terms and concepts

• Assignable causes of variation

• Average run length (ARL)

• Average time to signal

• Cause-and-effect diagram

• Chance causes of variation

• Control Chart

• Control limits

• Defect concentration diagram

• Designed experiments

• Flow charts and operations process charts

• Histogram

92

• In-control process

• “Magnificent Seven”

• Out-of-control-action plan (OCAP)

• Out-of-control process

• Pareto Chart

• Patterns no control charts

• Phase I and Phase II application of control charts

• Rational subgroups

• Sample size for control charts

• Sampling frequency for control charts

• Scatter diagram

• Sensitizing rules for control charts

• Shewhart control charts

• Statistical Control of a process

• Statistical process control (SPC)

• Steam-and-leaf plot

• Three sigma control limits

• Warning limits

Mod1 9-ns4

Technology

Transcript of Mod1 9-ns4