Topic-1 Introduction to SQC

Lecture Notes of Statistical Quality Control (IM‐511)

© Dr. Muhammad Wasif, PMP (Assistant Professor ‐ IMD, NED UET) 1

Resource PersonDr. Muhammad Wasif, PMP Assistant ProfessorDepartment of Industrial and Manufacturing Engineering,NED University of Engineering and Technology.

IM 511

Statistical Quality Control

Resource Person

Dr. Muhammad Wasif, PMP

Assistant Professor

Department of Industrial and Manufacturing Engineering,

NED University of Engineering and Technology.

Communications • Computing • Services • Manufacturing • Defense & Aerospace • Medical • Automotive



Qualification

2003 – B.E. in Mechanical Engineering from NED University.

2007 – M. Engg. In Industrial & Manufacturing Engineering from NED University.

2013 – Ph.D. in Mechanical Engineering from Concordia University, Montreal (Quebec) Canada.

2016 – Project Management Professional (PMP)

Experience

2004 ‐2006 – Worked in Assembly Operations Plant of Hinopak Motors Ltd.

Developed the Vehical Inspection Department (VID) on Main Assembly Line

2008‐2012 – Research Project for the accurate manufacturing of Hypoid Gears.

2006 ‐ to date – Worked as “Lecturer” and “Asst. Professor” in IMD, NED UET.

Area Coordinator & Auditor for ISO Management.

Member, Board of Review, Quality Management Cell.

Resource Person

3© Dr. Muhammad Wasif, PMP ‐ Asst. Professor (IMD ‐NED UET)

Optimization of milling parameters for various types of fibers

reinforced composite materials (FRP) (SUPARCO, 2015).

Optimal parameters for the drilling of carbon fiber reinforced (FRP)

composite material (SUPARCO, 2015).

Influence & Impact of Vendor Performance System for Automobile

Supply Chain Industry. (Pak‐Suzuki Motors Limited, 2014).

Optimization of parameters for the plasma coating of aerospace alloys

(Pakistan Air Force – PAF, 2014,).

Processes /parameter optimization for deep‐hole drilling using

coated/un‐coated HSS drills on three different materials such as MS,

AL Alloy (AA‐2024) & Titanium. (SUPARCO, 2013).

Projects




Reverse Engineering of the 250cc engine of a multi‐purpose vehicle, to

be developed and manufacture in Pakistan, in collaboration with the

DICE Foundation, USA. (3 projects NED UET, DICE Foundation USA

and an entrepreneur/investor, 2015).

Study the behavior of Spring‐back of high tensile Hot Rolled Steel.

(Pak‐Suzuki Motors Limited, 2014).

Productivity increase by Optimization of Investment Casting Process.

(Precision Engineering Complex ‐ PEC, PIA, 2014).

Development of an Automatic Identification & Data Capture (AIDC)

system using Radio Frequency Identification Device (RFID) for a

Warehouse (2014).

Projects


Project Management class is an open discussion forum, where students

can add their experiences or raise queries.

During discussions, resource person will act as moderator.

Punctuality of time is necessary to validate the attendance, else it will be

marked absent.

One Break will be allowed for Maghreb prayer and refreshment.

Mobile phone ringtones should be on silent.

Food, smoking and Drinks not allowed.

Submission of assignments and conduction of tests will be on prescribed

dates.

Assignments must be submitted with the “Assignment Form“ uploaded

on one‐drive.

Class Room Decorum




Class contact hours

Consulting hours Before and after class or by appointment

Consulting Office Room 2, Ground floor, Department of Industrial

and Manufacturing Engineering Building.

e‐mail [email protected]

Sent your information http://goo.gl/forms/JKRBxEt07h

Once form is filled, you will receive google

drive link to access the lecture slides.

Course Contact

Class Day Timings

MEM (IM) Thursday 18:00pm to 21:00pm


Recommended BooksBook : Statistical Quality ControlAuthor : Douglas C. MontgomeryEdition : 6th

Publishers : Wiley & Sons

Book : Fundamentals of Quality Control And ImprovementAuthor : Amitava MitraEdition : 2nd or 3rd

Publishers : Wiley & Sons

Book : Statistical Process Control And Quality ImprovementAuthor : Gerald M. SmithEdition : 5th

Publishers : Pearson International




Sessional Marks

Final Examination Marks 60

Sessional Marks 40

Quiz (Mid-Term) 15

Assignments 15

Class participation 5

Attendance 5


1. Review of Probability & Statistics,

2. Probability Distributions,

3. Hypothesis Testing (One‐Tail and Two‐Tail Tests),

4. Sampling Distributions,

5. Quality Control & Assurance,

6. Causes of Variation,

7. Control Charts (for attributes and variables),

8. EWMA Chart and CUSUM Chart,

9. Metrology & Gauging,

10. Gauge Capability Analysis,

11. Gauge Repeatability and Reproducibility,

12. Process Capability Indices,

13. Acceptance Sampling (for attributes and variables).

Course Contents




Develop clear understanding of the use of modern

statistical methods for quality control and improvement

To develop the knowledge of principles and the basis for

applying them in a variety of situations (mostly

engineering and management)

To understand the analysis and use to computer‐aided

tool for the quality control and imrpovement

Course Objectives


Resource PersonDr. Muhammad Wasif, PMPAssistant ProfessorDepartment of Industrial and Manufacturing Engineering,NED University of Engineering and Technology.

Topic # 1

Introduction to Statistical Quality Control



Statistics and Quality

Use of statistical methods to improvethe quality of the products

How : to Monitor and Control a Process

Statistics: is the study of the Collection,Organization, Analysis, Interpretation,and Presentation of Quantitative data

Manufactured goods: such asautomobiles, computers, and clothing,appliances

Services such as the generation anddistribution of electrical energy, publictransportation, banking, retailing, andhealth care.

Statistical Quality Control




What is quality ?

Fitness for use: conformance‐to‐specifications (Juran)

Quality of design: various grades or levels of quality

Safe and smooth transportation but with various size, appointments,

appearance, and performance

E.g. Toyota, Lexus, Hino are different brand of Toyota

Group.

Quality of conformance: how well the product conforms to

the specifications required by the design (Crosby)

This definition does not address “fit‐for use” by the

customer

Definition of Quality


What is quality ?

Quality is inversely proportional to variability

A comparative study of a transmission that was manufactured in a domestic

plant and by a Japanese supplier

Modern Definition of Quality


Warranty costs for transmissions Distributions of criticaldimensions for transmissions.



Dimensions of Quality


Dimensions of Quality (Garvin 1987)


Dimension Meaning & Example

Performance Primary Product Characteristics, such as the BRIGHTBNESS of the Picture.(will the product do the intended job?)

Reliability Consistency of Performance over Time, average time for the unit to fail.(How often does the product fail?)

Durability Useful life, includes Repair.(How long does the product last?)

Serviceability Resolution of problems and Complaints, ease of repair.(How easy is it to repair the product?)

Aesthetic Sensory Characteristics, such as EXTERIOR FINISH.(What does the product look like?)

Features Secondary Characteristic, added Features, such as REMOTE CONTROL.(What does the product do?)

Perceived Quality (Reputation)

Past Performance and other Intangibles such as being Ranked 1st.(What is the reputation of the company or its products?)

Conformance to Standards

Meeting Specifications or Industry Standards, Workmanship.(Is the product made exactly as the designer intended?)

Response Human‐to‐human interface, such as Courtesy of the dealer.



It is the reduction of variability in

processes and products

Excessive variability in process performance

often results in waste.

Quality improvement is the elimination of

waste

Particularly effective in service industries,

where there may not be as many things that

can be directly measured

Quality improvement


A characteristics of products that describe the user or consumer

thinks of as quality is called quality characteristics (critical‐

to‐quality (CTQ) characteristics)

Structural (Length, Weight, Strength etc.)

Sensory ( Taste, Smell, Color etc.)

Time Oriented (Warranty, Reliability, Durability etc.)

Ethical Characteristics (Honesty, Courtesy, Friendliness etc.)

Quality Engineering Terminology




Quality Characteristics fall into TWO broad classes;

Variables : Characteristic that are Measurable and are

expressed on a Numerical Scale are called Variables.

For example: Diameter, Length, Density, Resistance of Coil

Attributes: (Countable Characteristic) A Quality

Characteristic is said to an Attribute (Countable) if it is

classified as either Conforming of Nonconforming to a

stipulated Specification.

For example: Smell of Cologne, Color, Go/no‐go, Pass/Fail



Standard or Specification: Quality characteristics are oftenevaluated relative to specifications. E.g.

In manufacturing diameter is shaft 25±0.5 means 24.5mm to 25.5mm In service maximum time at checkout counter 90seconds.

Target or nominal values: desired value for that qualitycharacteristic (25mm)

Lower specification limit (LSL): Smallest allowable value for aquality characteristic (24.5mm)

Upper specification limit (USL): Largest allowable value for aquality characteristic (25.5mm)

Non Conformity: Defect (26mm or 24.4mm)

Nonconforming Unit : Defective

Not all products containing a defect are necessarily defective





Quality of Design: (Should be Simple &Least Expensive) It implies that theProduct or Service must be Designed tomeet at least minimally the needs of theConsumer.

Quality of Conformance: Quality ofConformance implies that theManufactured Product or the Servicerendered must meet the Standards selectedin the Design phase.

Quality of Performance: It is concernedwith how well the Product Functions orService performs when put to use.



QUALITYQUALITY

Quality of Performance

Quality of Performance

Quality of Design

Quality of Design

Quality of Conformance

Quality of Conformance

Voice Of Customer (VoC): The ʺvoice ofthe customerʺ is the term to describe thestated and unstated customer needs orrequirements.

Voice Of Process (VoP): It results of thehistorical performance of the process (orsystem). The VoP details, what the processis capable of producing.

Concurrent engineering: a team approachto design, with specialists inmanufacturing, quality engineering, andother disciplines working together with theproduct designer at the earliest stages of theproduct design process.





Quality Circle: It is typically an informal group of people

that consists of Operators, Supervisors, Managers, and so on,

who get together to improve ways to make the product or

deliver the service.





QUALITY CONTROL

Quality Control may generally bedefined as a system to maintain a desired level in a

Product or Service. (Amitva Mitra)

A System that is used to maintain a desired level of Quality in a Product or Service.

(Amitva Mitra)

QC is the Operational Techniques & Activities which sustain a Quality of Product or Service that will given needs.

(William J. Kalorik)

QUALITY ASSURANCE

All those Planned or Systematic Actions necessary to provide confidences that a Product or Service Satisfy given needs.

(Amitva Mitra)

QUALITY ENGINEERING

Quality Engineering is the Set of Operational, Managerial & Engineering Activities that a company uses to ensure that a Quality Characteristics of a Product are at the

Nominal or Required level. (Amitva Mitra)

QUALITY PLANNING

Is a Strategic Activity, and it is just an vital to an organization’s long term business success as the product development Plan, the Financial Plan, the Marketing Plan , and the Plan for

utilization of Human Resources.(Douglas C. Montgomery)





History of Quality Improvement




Statistical Methods for Quality Control and Improvement


ProcessInput

Raw Material,Components,

Sub-assemblies,and/or

Information

OutputY=Quality

Characteristics(CTQs)

Controllable Inputs:Temperature, Pressure

X1, X2, . . . . . . , Xn

Uncontrollable Inputs:Environmental Factors,

Properties of Raw Material provided by External Customer

Z1, Z2, . . . . . . , Zn

Measurement Evaluation Monitoring & Control

Product

[Production Process Inputs and Outputs]

Process is a series of activities that takes an Input, adds value to it and produces an Output for a Customer

Statistical process control (SPC):

Control charts, plus other problem‐solving tools

Useful in monitoring processes, reducing variabilitythrough elimination of assignable causes

On‐line technique

Designed experiments (DOE)

Discovering the key factors that influence processperformance

Process optimization

Off‐line technique

Acceptance Sampling

It is the Inspection and classification of a sample of unitsselected at random from a larger batch or lot and theultimate decision about disposition of the lot, usuallyoccurs at two points: incoming raw material, or finalproduction.

Statistical Methods


ProcessProcessInput Output

Search for input that vary the output


Input is optimized for desired output


Input is sampled to analyzed for desired output

scrap



Statistical Methods


Quality Philosophy & Management Strategies


Walter A. Shewhart (1891-1967) : (Some times referred as Father of SQC)• worked at the Hawthorne Plant of Western Electric, where he developed

(1924) and used Control Charts.• He describes the basic Principles of SQC in his book “Economic Control of

Quality of Manufactured Product (1931).• He was the first honorary member of ASQ.

W. Edward Deming: • Developed a list of 14 Points.• Deming Cycle (PDSA Cycle)• Deming's Seven Deadly Diseases of Management

Joseph M. Juran (1904-2008): • Developed the Juran Trilogy.• Deming and Juran worked in both the US and Japan to help businesses

to understand the importance of Continuous Improvement.



Quality Philosophy & Management Strategies


Philip B. Crosby:•Originated the Zero Defect Concept.• Was an ASQ honorary member and Past President.

Armand V. Feigenbaum : • Originated the concept of Total Quality Control.• He is an ASQ honorary member and served as ASQ President for Two

consecutive terms.

Kaoru Ishikawa: • Developed Cause and Effect Diagram.• He worked with Deming through the Union of Japanese Scientists and

Engineers (JUSE)Genichi Taguchi:

• Taught that any departure from Nominal or Target value for a characteristicrepresents a Loss to Society.

• He is also popularized the use Fractional Factorial Experiments.

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

Deming’s Deadly Diseases




Shewart Cycle (PDCA cycle)


Shewart Cycle (PDCA cycle)


Other Short Topics just define them:

TQM (Total Quality Management)

Deming/Juran Value engineeringZero defect philosphy

Quality Systems & Standards ISO Generic standard for Quality systems

Six Sigma Motorola InvariabilityMoving mean



Quality Systems and Standards


Quality Systems and Standards


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



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)

Six Sigma


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



Six Sigma


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

New product design (engineering)



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

New product design (engineering)

Six Sigma


A disciplined and analytical approach to process and productimprovement

Specialized roles for people; Champions, Master Black belts, BlackBelts, 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



Lean Systems


Focuses on elimination of waste

Long cycle times

Long queues – in‐process inventory

Inadequate throughput

Rework

Non‐value‐added work activities

Makes use of many of the tools of operations research and

industrial engineering

Quality Cost




Managing Quality Cost


Managing Quality Cost


Topic-1 Introduction to SQC

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Transcript of Topic-1 Introduction to SQC