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D. Anthony Chevers Quality Management & Statistical Quality Control SBCO 6240 - Production and Operations Management

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Page 1: SBCO 6240Quality&StarQualControl HB Student

D. Anthony Chevers

Quality Management

& Statistical Quality Control

Quality Management

& Statistical Quality Control

SBCO 6240 - Production and Operations Management

Page 2: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

Lecture #2 - Quality

Definitions; Purpose & Profitability Quality Inspection Total Quality Management (TQM) Continuous Improvement Tools Process Capability & Statistical QC

• Process Capability; Process Capability Ratio

• Process Capability Index; Six-Sigma

International Standard Organization Customer Care & Key Performance Indicators Exercises/Case Analysis

2

Page 3: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

Paradigm Shift Made in Japan

• Period – Early 1960’s• Responses – Junk, cheap, low quality, poor quality, imitation, low

technology & toys Made in Japan

• Period – Early 1990’s and beyond• Responses – Excellence, Premium price, high quality, innovation,

high technology & leadership Reason – Paradigm Shift to “Zero defect production”-

Deming 1950’s [Sturn Ruger & Swiss]

Paradigm – The accepted way of doing a task or accepted behavior; the norm

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Lecture 2 - Quality Management & Statistical Quality Control |

Only Survivors

“The only survivors at the end of two decades will be companies with constancy of purpose for quality, productivity and service.”

W. Edward Deming

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Lecture 2 - Quality Management & Statistical Quality Control |

Quality - Defined The American Society for Quality Control –

“The totality of features and characteristics of a product or service that bear on its ability to satisfy stated or implied needs.”

A product or service free of deficiencies In general, quality means different things to

different people. • Conformance to requirement; Utility• Fitness for purpose; Reliability • Value for money; Cost-effectiveness

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Lecture 2 - Quality Management & Statistical Quality Control |

The Meaning of Quality

Page 7: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

Eight Dimensions of Quality …(Garvin)

Performance – What are the basic operating characteristics of the product or service?

Features – What extra characteristics does the product or service have, beyond the basic performance operating characteristics?

Reliability – How long can a product go between failures or the need for maintenance?

Conformance – Was the product made or service performed to specifications?

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Lecture 2 - Quality Management & Statistical Quality Control |

Eight Dimensions of Quality../2

Durability – What is the useful life for a product? How will the product hold up under extended or extreme use?

Serviceability – How easy is it to repair, maintain or support the product or service?

Aesthetics – How well does the product or service appeal to the senses?

Perceived quality – What is the reputation or image of the product or service? [Lawn mower, car door, SSTP, sweet non sense]

Page 9: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

Market Gain[Quality & Profitability]

PerformanceFeatures

Reliability, etc.

This model is well supported by empirical evidence

Reputation for quality

Market Share

Higher Price

Experience based scale economies

Profits

Page 10: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

Quality And Productivity

Productivity = output / input

Fewer defects increase output

Quality improvement reduces inputs

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Lecture 2 - Quality Management & Statistical Quality Control |

The Deming Chain Reaction[Quality & Productivity & Sustainability]

Improve Quality

Costs decreases because of less rework, fewer mistakes, fewer delays, fewer snags, better use of machine time and materials

Productivity improves

Capture the market with better quality

Stay in business

Provide jobs and more jobs

Source: Reprinted from out of the Crisis by W. Edward Deming by permission of MIT and W. Edward DemingPublished MIT, Center for Advanced Engineering Study, Cambridge, Mass 02139, Copyright 1966 by W. Deming

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Lecture 2 - Quality Management & Statistical Quality Control |

Quality Control Along the Production System & ISO

INPUTS CONVERSION OUTPUTS

Raw materials, Parts and Supplies

Production Processes Product and Services

! ! !! ! !! ! !

Control Charts & Acceptance Tests

Control ChartsControl Charts &

Acceptance Tests

Quality of InputsQuality of partially

completed productsQuality of Outputs

Page 13: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

International Standard Organization (ISO) ….

Origin – European Certifications – ISO9000/1/2 & 14000 Purpose – All organizations must be ISO certified

to compete in the global marketplace. Statement – ISO certification, a statement that you

are a quality organization with standard systems through:• Policies• Procedures• Instructions• Records

Page 14: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

ISO …../2

Motto • Say what you do • Do what you say• Prove it • Improve it

Jamaican firms – Grace Kennedy, J.F.Mills, Cable & Wireless, Alpart, Windalco, Jamalco, FedEx, Pegasus, Sigma Unit Trust, Berger, Jamaica Boilers, JWN, etc

Benefits – Consistently produce quality products through quality systems.

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Lecture 2 - Quality Management & Statistical Quality Control |

Quality along the Production System

Quality inspection must be done along the production system.• Input

• Entrance test –Acceptance school & work• Acceptance test of in-coming raw materials

• Transformation• Mid module test• Laboratory test along conversion

• Output• Final exam• Performance evaluation of lecturer• Quality inspection of finished goods/services

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Lecture 2 - Quality Management & Statistical Quality Control |

Total Quality Management (TQM)

A managerial approach in which the entire organization is managed so that it excels in all quality dimensions that are important to customers

TQM is a business philosophy centered around seven core ideas or principles• Customer focus; Leadership involvement• Continuous improvement; Employee

empowerment• Quality assurance; Supplier partnerships• Strategic quality plan

o

Page 17: SBCO 6240Quality&StarQualControl HB Student

Lecture 2 - Quality Management & Statistical Quality Control |

Total Cost of Quality

Internal Failure Costs• Costs caused by defects that occur prior to delivery to

customer, including money spent on repairing or reworking defective products, as well as time wasted on these activities (during production of service or product)

External Failure Costs• Costs incurred by defects that are not detected until a

product or service reaches the customer Appraisal Costs

• Costs a company incurs to assess its quality levels Prevention Costs

• The costs an organization incurs to actually prevent defects from occurring to begin with

Warranty – A written guarantee that the producer will replace or repair defective parts or perform the service to the customer’s satisfaction (Ritzman, 2005)

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Lecture 2 - Quality Management & Statistical Quality Control |

Continuous Improvement Tools

Process mapping/Flow charts• An activity that uses graphical symbols to document the physical and

information flows of a process Control charts Root cause analysis

• A process by which organizations brainstorm about possible causes of problems and then, through structured analysis and data gathering efforts, gradually narrow the focus to a few root causes

Five whys• An approach used during the narrow phase of root cause analysis, in which

teams brainstorm successive answers to the question “Why is this a cause of the original problem? [5 rounds]

Cause-and-effect diagram/Fishbone diagram• A graphical tool used to categorize the possible causes for a particular

result Pareto chart

• A special form of bar chart that shows frequency counts from highest to lowest

Benchmarking

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Lecture 2 - Quality Management & Statistical Quality Control |

PDCA Cycle (Deming Wheel)

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Lecture 2 - Quality Management & Statistical Quality Control |

Benchmarking

Identify those processes needing improvement

Identify competitor performing ‘best practices’

Visit the facility and interview key players at all levels

Analyze dataCustomize and adapt if applicable

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Lecture 2 - Quality Management & Statistical Quality Control | 22

Definitions

Statistical quality control (SQC)• The application of statistical techniques to quality

control• We want to keep the process in control• Small variation of the process – products that meet

standard

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Lecture 2 - Quality Management & Statistical Quality Control | 23

Definitions Process capability [1 SQC technique]

• The ability to meet design specifications

Process capability ratio (Cp)• A mathematical determination of a process’s

capability to meet certain quality standards. A Cp > 1 means the process is capable of meeting the standard being measured

Process capability index (Cpk)• A mathematical determination of a process’s

capability of meeting certain tolerance limits

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Lecture 2 - Quality Management & Statistical Quality Control | 24

UCL

LCL

Samples over time

1 2 3 4 5 6

UCL

LCL

Samples over time

1 2 3 4 5 6

UCL

LCL

Samples over time

1 2 3 4 5 6

Normal BehaviorNormal Behavior

Possible problem, investigatePossible problem, investigate

Possible problem, investigatePossible problem, investigate

Statistical Process Control (SPC) Charts

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Lecture 2 - Quality Management & Statistical Quality Control | 25

Control Limits: Normal Curve

x

0 1 2 3-3 -2 -1z

Standard deviation units or “z” units.

Standard deviation units or “z” units.

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Lecture 2 - Quality Management & Statistical Quality Control |

Normal Curve – Student Grades

X

65 70 75 85 90 95

Z

-3 -2 -1 +1 +2 +3

Total of 6 Standard Deviations ( σ )

µ0

80%

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Lecture 2 - Quality Management & Statistical Quality Control | 27

Control Limits

We establish the Upper Control Limits (UCL) and the Lower Control Limits (LCL) with plus or minus 3 standard deviations from some x-bar or mean value.

xLCL UCL

99.7%

Based on this we can expect 99.7% of our sample observations to fall within these limits.

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Lecture 2 - Quality Management & Statistical Quality Control | 28

Process Capability

Upper tolerance limit (UTL)• The highest acceptable value for some measure of

interest Lower tolerance limit (LTL)

• The lowest acceptable value for some measure of interest

Cp = (UTL – LTL)/6σCpk = min[(µ - LTL)/3σ , (UTL - µ)/3σ]

Where µ is average and σ is standard deviation (Cp) - Process Capability Ratio (Cpk) - Process Capability Index

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Lecture 2 - Quality Management & Statistical Quality Control | 29

Process Capability Ratio (Cp)

For a process to be capable, its values must fall within upper and lower specifications

This typically means the process capability is within +/- 3 standard deviations from the process mean

Since this range of values is 6 standard deviations, a capable process tolerance, which is the difference between the upper and the lower specifications, must be greater than or equal to 6

Capable process has Cp of at least 1.0 If the Cp is less than 1.0, the process yields products or services

that are outside their allowable tolerance With a Cp of 1.0, 2.7 parts in 1,000 can be expected to be “out of

spec” [Standard Given] The higher the Cp, the greater the likelihood the process will be

within design specifications Many firms have chosen a Cp of 1.33 as a target for reducing

process variability. This means only 64 parts per million can be expected to be out of spec.

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Lecture 2 - Quality Management & Statistical Quality Control | 30

Normal Distribution

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Lecture 2 - Quality Management & Statistical Quality Control | 31

Cp Values for Different Tolerance Limits

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Lecture 2 - Quality Management & Statistical Quality Control | 32

Exercise - Cp

Big Ford Machine Shop has a customer that requires shafts with a diameterof 25 cm., +/- 0.02 cm. The customer has stated that Big Ford must be ableto meet these requirements 99.7% percent of the time in order to keep thebusiness. Currently, Big Ford is able to make shafts with a process mean (µ)of exactly 25 cm and a standard deviation (σ) of 0.005 cm. Is Big Ford capable of meeting the customer's needs? Notice that the UTL and LTL are 25.02 cm and 24.98 cm respectively. Therefore, the process capability ratio is:

Cp = UTL - LTL = 25.02 - 24.98 = 0.04 = 1.336σ 6(0.005) 0.03

Because the process capability ratio is greater than 1.0, Big Ford'sprocess is more than capable of providing 99.7% defect-free shafts.

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Lecture 2 - Quality Management & Statistical Quality Control | 33

Process Capability Index -Cpk

In some cases, the process mean, µ, is not exactly centered on the target value

In these cases, we use the process capability index, Cpk, to determine whether or not the process is capable of meeting the tolerance limits 99.7% of the time.

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Lecture 2 - Quality Management & Statistical Quality Control | 34

Process Capability Index, Cpk

3

X-UTLor

3

LTLXmin=C pk

Shifts in Process Mean

Capability Index shows how well parts being

produced fit into design limit specifications.

Capability Index shows how well parts being

produced fit into design limit specifications.

As a production process produces items small shifts in equipment or

systems can cause differences in

production performance from differing samples.

As a production process produces items small shifts in equipment or

systems can cause differences in

production performance from differing samples.

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Lecture 2 - Quality Management & Statistical Quality Control | 35

Exercise - Cpk

Engineers at Milburn Textiles have developed the following specificationsfor a key dyeing process:

Target value = 140 degreesUpper tolerance limit (ULT) = 148 degreesLower tolerance limit (LTL) = 132 degrees

At Milburn Textiles, the dyeing process must be controlled to ensure thatfabric colors are correct.The UTL and LTL are based on the engineer's observations that resultsare acceptable as long as the temperature remains between 132 and 148 degrees. Currently, the dyeing process has a mean temperature of 139.8degrees, with a standard deviation of 2.14 degrees. Because the processmean is slightly off from the target value of 140 degrees, the quality teamuses the process capability index to evaluate the process's capability.

Cpk = min µ - LTL, UTL - µ = 139.8 - 132, 148 - 139.8

3σ 3σ 3(2.14) 3(2.14)

= min [1.21, 1.28] = 1.21

Even with the process mean being off center, the process is stillcapable of meeting the tolerance limits more than 99.7% of the time.

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Lecture 2 - Quality Management & Statistical Quality Control | 36

Six-Sigma Quality

(UTL – LTL)/12σ

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Lecture 2 - Quality Management & Statistical Quality Control | 37

Exercise – Six-Sigma

Milburn Textiles has recalibrated its dyeing process so that the processmean is now exactly 140 degrees, with a new, lower standard deviationof 1.40 degrees. Given upper and lower tolerance limits of 148 and 132degrees, does the dyeing process provide six-sigma quality levels?

Calculating the process capability ratio for six-sigma levels:

Six-sigma Cp = UTL - LTL = 148 - 132 = 0.9512σ 12(1.40)

Because Cp < 1.0, the process is still not capable of providing six-sigma

quality. To achive six-sigma quality, Milburn will have to reduce thestandard deviation even further.

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Lecture 2 - Quality Management & Statistical Quality Control | 38

Service Quality #1

Time & Timeliness• Customer waiting time, completed

on time Correct & Accuracy

• Conduct the right transaction• Performed right every time

Completeness• Customer gets all they asked for

Courtesy• Treatment by employees

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Lecture 2 - Quality Management & Statistical Quality Control | 39

Service Quality #2

Consistency• Same level of service for all customers

Accessibility & Convenience• Ease of obtaining service

Responsiveness• Reactions to unusual situations

Others?

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Lecture 2 - Quality Management & Statistical Quality Control | 40

Motto – Customer Service

Ford – “Customer 1st”

U.S. Distributor – “It is not our intention to satisfy our customers. Its our intention to amaze them”

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Lecture 2 - Quality Management & Statistical Quality Control |

“Customer Satisfaction is Worthless, Customer Loyalty is Priceless”

- Jeffery Gitomer

Motto – Customer Service

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Lecture 2 - Quality Management & Statistical Quality Control |

Motto – Customer Service

Rule #1 – The customer is always right

Rule #2 – If the customer is wrong, kindly read rule #1

[It is imperative that the customer

is happy]

“Only the customer, and the customer alone, will pay our costs and provide our profits”.

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Lecture 2 - Quality Management & Statistical Quality Control | 43

Quality Standards – KPI’s

OrganizationWhat is Inspected Standard

Jones Law Offices Receptionist Phone answered by the second ring

Billing Accurate, timely and correct formatAttorney Promptness in returning calls

Norton's Department Store Display areas Attractive, well organized, stocked, good lighting

Stockrooms Rotation of goods, organized, cleanStorekeeper Maximum waiting time (issues) be 5 minutes max.Sales Rep. Neat, courteous, very knowledgeable

Hard Rock Hotel Receptionist Uses customer's name

Doorman Greets guest in less than 30 secondsRoom All lights & A/C working, spotless bathroomMinibar Restocked and charges accuraely posted to bill

Hard Rock Café Busboy Serves water and bread within 1 minute

Busboy Clears all crumbs prior to dessertWaiter Knows and suggests specials, desserts

Bayfield Community Hospital Billing Accurate, timely and correct format

Pharmacy Prescription accuracy, inventory accuracyLab Audit for lab-test accuracyNurses Charts immediately updatedAdmissions Data entered correctly and completely

Note: Let's strive to exceed customer's expectation instead of merely meeting requirements

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Lecture 2 - Quality Management & Statistical Quality Control | 44

Discussion Questions #1

• Different customers can perceive the value of the same product or service very differently. Explain how this can occur. What are the implications for developing successful operations and supply chain strategies?

• Why can two people perceive the same product or service as having different quality levels? From a business perspective, why is it important then to “know your customers”?

• Give at least three reasons why it is important for organizations to continuously improve the quality of their products and services.

• What are the advantages of using tools such as process maps, root cause analysis and pareto charts to structure a firm’s continuous improvement efforts? What are the risks associated with not following such a thorough process?

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Lecture 2 - Quality Management & Statistical Quality Control | 45

Exercise - Calculation In a local Insurance Company claims department, the claims

process mean is 210 minutes and the standard deviation is 0.516 minutes. The design specification to meet customer expectations is +/- 3 standard deviation. Is the process capable to meet customer’s expectation?

You are the process improvement manager and have developed a new machine to cut insoles for the company’s top-of-the-line running shoes. You are excited because the company’s goal is no more than 3.4 defects per million and this machine may be the innovation you need. The insoles cannot be more than +/- 0.001 of an inch from the required thickness of 0.250”. You want to know if you should replace the existing machine, which has a Cpk of 1.0. The estimated standard deviation is 0.0005 inches. You decide to determine the Cpk for the new machine and make a decision on that basis.

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Solution – Local Insurance Co.

Given: µ = 210 σ = 0.516

Design spec. to meet customer expectation is 210 +/- 3 minutesUpper specs. = 213 minutesLower specs. = 207 minutes

Cp = Upper Specs - Lower Specs. = 213 - 207

6σ 6(0.516)1.938

Since a ratio of 1.0 means that 99.7% of a process's output arewithin specifications, this ratio suggest a very capable process,with nonconformance of less than 4 claims per million.

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Lecture 2 - Quality Management & Statistical Quality Control | 47

Solution – Improvement Manager

Upper Specs. Limit = 0.251 inchesLower Specs. Limit = 0.249 inches

Mean of the new process (µ) = 0.250 inchesEstimated std. dev. (σ) of the new process = 0.0005 inches

Cpk = min Upper Specs. Limit - µ , µ - Lower Specs. Limit3σ 3σ

min 0.251 - 0.250 , 0.250 - 0.2493(0.0005) 3(0.0005)

Both calculations result in: 0.001 = 0.670.0015

Because the new machine has a Cpk of only 0.67, the new

machine should not replace the existing machine.

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Lecture 2 - Quality Management & Statistical Quality Control | 48

Case Studies

Quality at the Ritz-Carlton Hotel CompanyDittenhoefer’s Fine ChinaSouthwestern University: (C)*

Page 49: SBCO 6240Quality&StarQualControl HB Student

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NEXT LECTURE:Process Analysis & Productivity

D. Anthony Chevers

[email protected], Room #28