Chapter 12

Managing Production Operations

Advanced Organizer

Decision Making

Planning

Organizing

Leading

Controlling

Management Functions

Research

Design

Production

Quality

Marketing

Project Management

Managing Technology

Time Management

Ethics

Career

Personal Technology

Managing Engineering and Technology

Chapter Objectives

• Explain and be able to use the statistics of quality

• Describe the quality revolution• Recognize the methods of work measurement

What Is Quality?

• “The degree of excellence of a thing” (Webster’s Dictionary)

• “The totality of features and characteristics that satisfy needs” ( ASQC)

• Fitness for use

Definitions of Quality

Fitness for use, or customer satisfaction

• Quality of design

• Quality of conformance ( or Quality of production)

The Meaning of Quality

The Meaning of Quality

Producer’s Perspective Consumer’s Perspective

Fitness for Consumer Use

Quality of Design • Quality Char. • Price

Production Marketing Quality of Conformance •Conformance to Spec. • Cost

Quality Of Conformance

• Ensuring product or service produced according to design

• Depends on–design of production process–performance of machinery–materials–training

Dimensions of Product Quality

1. Performance -- basic operating characteristics2. Features --“extra” items added to basic features3. Reliability -- probability product will operate over time4. Conformance --meeting pre-established standards5. Durability -- life span before replacement6. Serviceability -- ease of getting repairs, speed &

competence of repairs7. Aesthetics -- look, feel, sound, smell or taste8. Safety --freedom from injury or harm9. Other perceptions--subjective perceptions based on brand

name, advertising, etc

Service Quality

1. Time & Timeliness -- customer waiting time, completed on time

2. Completeness -- customer gets all they asked for3. Courtesy -- treatment by employees4. Consistency -- same level of service for all customers 5. Accessibility & Convenience -- ease of obtaining service6. Accuracy -- performed right every time7. Responsiveness -- reactions to unusual situations

The Cost of Quality

Cost of Achieving Good Quality– Prevention costs

• Quality planning costs• Product design costs• Process costs• Training costs• Information costs

– Appraisal costs • Inspection and testing• Test equipment costs• Operator costs

Cost of Poor Quality– Internal failure costs

• Scrap costs• Rework costs• Process failure costs

(Diagnostic)• Process downtime costs• Price-downgrading costs

– External failure costs • Customer complaint costs• Product return costs• Warranty claims costs• Product liability costs• Lost sales costs

• Break-even charts

Increasing Quality

$

Failure Cost

Appraisal Cost

Total Quality Cost

Quality Improvement and Quality Cost

Prevention Cost

Quality Control Approaches

• Statistical process control (SPC)– Monitors production process to prevent poor quality

• Acceptance sampling–Inspects random sample of product to determine if a lot is acceptable

Statistical Process Control

• Take periodic samples from process

• Plot sample points on control chart

• Determine if process is within limits

• Prevent quality problems

Variation

• Common Causes– Variation inherent in a process– Can be eliminated only through

improvements in the system

• Special Causes– Variation due to identifiable factors– Can be modified through operator or

management action

Probability Distribution

• Central tendency– Mean, Mode, Median

• Dispersion– Std. deviation, Variance

• Frequency function– Normal, Binomial, Poisson

Types Of Data

• Attribute data– Product characteristic evaluated with a

discrete choice• Good/bad, yes/no

• Variable data– Product characteristic that can be measured

• Length, size, weight, height, time, velocity

SPC Applied To Services

• Nature of defect is different in services

• Service defect is a failure to meet customer requirements

• Monitor times, customer satisfaction

Service Quality Examples

• Hospitals –Timeliness, responsiveness, accuracy

• Grocery Stores–Check-out time, stocking, cleanliness

• Airlines–Luggage handling, waiting times, courtesy

• Fast food restaurants–Waiting times, food quality, cleanliness

Control Charts

Commonly based on 3• Sample mean: x-bar-charts

• Sample range: R-charts

• Sample std. deviation: s-charts

• Fraction defective: p-charts

• Number of defects: c-charts

The Normal Distribution

=0 1 2 3

95%

99.73%

-1-2-3

Z Values in Control Charts

• Smaller Z values make more sensitive charts (Type I error)

• Z = 3.00 is standard

• Compromise between sensitivity and Type II errors

Process Control Chart

1 2 3 4 5 6 7 8 9 10

Sample number

Uppercontrollimit

CentralLine

Lowercontrollimit

Interpretation of Control Charts

No evidence of out-of-control, if

• No sample points outside limits

• Most points near process average

• About equal number of points above & below centerline

• Points appear randomly distributed

Development of Control Charts

1. Based on in-control data

2. If non-random causes present, discard data

3. Correct control chart limits

Control Charts For Attributes

• p Charts–Calculate percent defectives in sample

• c Charts–Count number of defects in item

p-Chart

n

)p1(pp

p

p

zpLCL

zpUCL

size sample=n

sample in defective % averagep

p-Chart Example

20 samples of 100 pairs of jeans

Sample # # Defects

Proportion Defective

1 6 0.06

2 0 0.00

3 4 0.04

…. …. ….

20 18 0.18

200 0.10

p-Chart Calculations

10.0

20(100)

200nsobservatio total

defectives totalp

190.0100

)10.01(10.0310.0

n

)p1(pzpUCL

010.0100

)10.01(10.0310.0

n

)p1(pzpLCL

Example p-Chart

Sample number

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

Pro

port

ion

defe

ctiv

e

002 4 6 8 10 12 14 16 18 200 2 4 6 8 10 12 14 16 18 200

c-Chart

cz+cUCL

c=deviation standard Samplec

samples #

defects #Totalcaverage Process

cz-cLCL

c-Chart Example

Count # of defects in 15 rolls of denim fabric

Sample # # Defects

1 12

2 8

3 16

…. …

15 15

Total 190

c-Chart Calculations

99.167.12367.12z-cLCL

35.2367.12367.12z+cUCL

67.1215

190c

c

c

Example c-Chart

0 2 4 6 8 10 12 14

Sample number

3

6

9

12

15

18

21

24

Num

ber

of d

efec

ts

Control Charts for Variables

• Mean chart (X-Bar Chart)– Monitors central tendency

• Dispersion chart – R-Chart– s-Chart– Monitors amount of variation

Range (R) Chart

RDUCL 4

samples of numberk

sample each of rangeRk

RR

RDLCL 3

R-Chart Example

Slip-ring diameter (cm) (sample size =5)

0.105.034.995.075.084.985.0110

50.09

4.97

5.00

4.98

1.15

: :::::::

0.084.994.924.935.004.993

0.122

0.084.964.994.945.015.021

4.964.955.075.035.01

X RObs. 5Obs. 4Obs. 3Obs. 2Obs. 1Sample

3 Control Chart Factors

Sample size -chart R-chart

n A2 D3 D4

2 1.88 0 3.27

3 1.02 0 2.57

4 0.73 0 2.28

5 0.58 0 2.11

6 0.48 0 2.00

7 0.42 0.08 1.92

8 0.37 0.14 1.86

X

R-Chart Calculations

115.010

15.1

k

RR

0)115.0(0RDLCL

243.0)115.0(11.2RDUCL

3

4

Example R-Chart

1 2 3 4 5 6 7 8 9 10

Sample

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Ran

ge

X-bar Chart Calculations

cm01.510

09.50

kx xxx k21

94.4115.58.001.5RAxLCL

08.5115.58.001.5RAxUCL

2

2

value range averageR

means sample of averagex

Example X-bar Chart

4.850

4.900

4.950

5.000

5.050

5.100

1 2 3 4 5 6 7 8 9 10

Sample

X-bar

Using X-bar and R-Charts Together

• Each measures process differently

• Process average and variability must be in control

Indications of “Process out of Control”

• Sample data fall outside control limits

• Theory of runs– 2 out of 3 beyond the warning limits– 4 out of 5 beyond the 1 limits– 8 consecutive on one side

• Patterns

Zones For Pattern Tests

Zone C

Zone C

Zone A

Zone A

RA3

1xsigma1 2

x

RA3

1xsigma1 2

Zone B

Zone B

RA3

2xsigma2 2

RA3

2xsigma2 2

RAxsigma3 2

RAxsigma3 2

UCL

LCL

CL

Control Chart Patterns

• 8 consecutive points on one side of the center line.

• 8 consecutive points up or down across zones.• 14 points alternating up or down.• 2 out of 3 consecutive points in zone A but still

inside the control limits.• 4 out of 5 consecutive points in zone A or B.

LCL

UCL UCL

LCL

Sample observationsconsistently below thecenter line

Sample observationsconsistently above thecenter line

Control Chart Patterns

Control Chart Patterns

LCL

UCL

LCL

UCL

Sample observationsconsistently increasing

Sample observationsconsistently decreasing

Inspection & Sampling

• 100% inspection– only with automated inspection

• Sampling inspection– Single sampling– Double sampling– Multiple sampling

Acceptance Sampling

• Accept/reject entire lot based on sample results

• Measures quality in percent defective

• Not consistent with TQM of Zero Defects

• Not suitable for JIT

Sampling Plan

• Guidelines for accepting lot• Single sampling plan

N = lot size n = sample size (random) c = acceptance number d = number of defective items in sample

• If d <= c, accept lot; else reject

Producer’s & Consumer’s Risk

• TYPE I ERROR = Prob(reject good lot) or producer’s risk – 5% is common

• TYPE II ERROR = Prob(accept bad lot) or consumer’s risk– 10% is typical value

Quality Definitions in Acceptance Sampling

• Acceptance quality level (AQL)–Acceptable fraction defective in a lot

• Lot tolerance percent defective (LTPD)–Maximum fraction defective accepted in a lot

Operating Characteristic (OC) Curve

• Shows probability of lot acceptance

• Based on – sampling plan – quality level of lot

• Indicates discriminating power of plan

Operating Characteristic Curve

AQL LTPD

Probability of acceptance, Pa

= 0.10 {0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20

= 0.05 {

Proportion defective

OC curve for n and c0.60

0.40

0.20

0.80

1.00

0.00

Ideal OC Curve

AQL

Probability of acceptance, Pa

0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20Proportion defective

0.60

0.40

0.20

0.80

1.00

0.00

Average Outgoing Quality (AOQ)

• Expected number of defective items passed to customer

• Average outgoing quality limit (AOQL) is the maximum point on AOQ curve

AOQ Curve

AverageOutgoingQuality

(Incoming) Percent DefectiveAQL LTPD

AOQL

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10

0.015

0.010

0.005

0.000

Double Sampling Plans

• Take small initial sample–If # defective < lower limit, accept–If # defective > upper limit, reject–If # defective between limits, take second sample

• Accept or reject based on 2 samples• Less costly than single-sampling plans

Multiple (Sequential) Sampling

• Uses smaller sample sizes

• Take initial sample–If # defective < lower limit, accept–If # defective > upper limit, reject–If # defective between limits, resample

• Continue sampling until accept or reject lot based on all sample data

Choosing a Sampling Plan

• An economic decision

• Single sampling plans– high sampling costs, low administration

• Double/Multiple sampling plans– low sampling costs, high administration

Taguchi Methods

LSL USLm LSL USLm LSL USLm LSL USLmLSL USLm LSL USLm LSL USLm

Taguchi Methods

• Deviation from ideal value => “loss of society”L = k (y – T)2

• Use ANOVA to identify the sources of variation

Loss

yT USLLSL

Total Quality Management

• Evolution of Total Quality Management– W. Edwards Deming– Joseph M. Juran– Philip Crosby – Armand V. Feigenbaum

• TQM and Continuous Process Improvement

• Principles of Total Quality Management• TQM Throughout the Organization

Deming's 14 points

1. Create a constancy of purpose toward product improvement to achieve long-term organizational goals.

2. Adopt a philosophy of preventing poor-quality products instead of acceptable levels of poor quality as necessary to compete internationally.

3. Eliminate the need for inspection to achieve quality by relying instead on statistical quality control to improve product and process design.

4. Select a few suppliers or vendors based on quality commitment rather than competitive prices.

Deming's 14 points

5. Constantly improve the production process by focusing on the two primary sources of quality problems, the system and workers, thus increasing productivity and reducing costs.

6. Institute worker training that focuses on the prevention of quality problems and the use of statistical quality control techniques.

7. Instill leadership among supervisors to help workers perform better.

8. Encourage employee involvement by eliminating the fear of reprisal for asking questions or identifying quality problems.

Deming's 14 points

9. Eliminate barriers between departments, and promote cooperation and a team approach for working together.

10.Eliminate slogans and numerical targets that urge workers to achieve higher performance levels without first showing them how to do it.

11.Eliminate numerical quotas that employees attempt to meet at any cost without regard for quality.

Deming's 14 points

12. Enhance worker pride, artisanry and self-esteem by improving supervision and the production process so that workers can perform to their capabilities.

13. Institute vigorous education and training programs in methods of quality improvement throughout the organization, from top management down, so that continuous improvement can occur.

14. Develop a commitment from top management to implement the previous thirteen points.

Deming Wheel (PDCA Cycle)

1. PlanIdentify the problem & develop the plan for improvement

2. DoImplement the plan on a test basis

3. Check/StudyAssess the plan: Is it working?

4. ActInstitute the improvement: continue the cycle

Total Quality Management

1. Customer defined quality2. Top management leadership3. Quality as a strategic issue4. All employees responsible for quality5. Continuous improvement6. Shared problem solving7. Statistical quality control8. Training & education for all

employees

TQM Throughout The Organization

• Marketing, sales, R&D• Engineering• Purchasing• Personnel• Management• Packing, storing, shipping• Customer service

Strategic Implications Of TQM

• Quality is key to effective strategy• Clear strategic goal, vision, mission• High quality goals• Operational plans & policies• Feedback mechanism• Strong leadership

TQM In Service Companies

• Inputs similar to manufacturing• Processes & outputs are different• Services tend to be labor intensive• Quality measurement is harder• Timeliness is important measure• TQM principles apply to services

Quality And Productivity

• Productivity= Output produced per unit of resources= output / input

• Fewer defects increase output

• Quality improvement reduces inputs

Manufacturing Productivity

• Rapid spread of manuf. capabilities => intense competition on a global scale.

• Advanced manuf. Tech. => changes both products & processes

• Changes in traditional management & labor practices, organizational structures, & decision making criteria.

Work Measurement

• “Fair day’s work” concept– The amount of work that can be produced by a

qualified operator working at a normal pace and effectively using his/her time when the work is not restricted by process limitations.

• Time Standard– The time required for a qualified employee

working at a normal pace under capable supervision experiencing normal fatigue and delay to do a defined amount of work of specified quality when following the prescribed method.

– Estimating costs – Estimating equipment needs– Scheduling– Line Balancing– Capacity Analysis– Evaluating automation costs– Planning staffing level– Methods comparison– Pricing– Revealing production problems– Evaluating employees– Setting piece rates– Compliance with contractual requirements

Uses of Time Standards

Work Measurement

Informal Time Standards– Estimates and educated guesses– Historical Data– Time of one whole cycle– Work Sampling

• Observe an operation to determine frequencies of work components

• Measure actual output• Determine performance standard

Work Measurement

Engineered Time Standards– Basic Time-Study Method

• Define work cycle• Take time measurements• Apply rating & allowance

– Methods-time Measurement (MTM)

Work Measurement

Criticism:– Direct labor only– Productivity, not quality

Maintenance

Types of Maintenance• Corrective maintenance• Preventive maintenance• Predictive maintenance

– preventive maintenance that use sensitive instruments to predict trouble

Total Productive Maintenance (TPM)

1. Promotes the overall effectiveness and efficiency of equipment in the factory.

2. Establishes a complete preventive maintenance program for factory equipment based on life-cycle criteria.

3. ”Team" basis involving various departments to include engineering, production operations, and maintenance.

4. Involves every employee in the company, from the top management to the workers on the shop floor. Even equipment operators are responsible for maintenance of the equipment they operate.

5. Based on the promotion of preventive maintenance through "motivational management"

Human Resources Management

• Recruiting & employment• Equal Employment Opportunity• Industrial relations• Compensation• Education & training• Employee benefits

Safety Engineer

• Identify & analyze hazards• Recommend protective devices & warning

signs• Provide safety training• Interpret OSHA (Occupational Safety &

Health Act) codes• Involve in workers’ compensation

insurance activities

Purchasing Engineer

• Recognition of need• Description of requirement• Selection of possible source of supply• Determination of price & availability• Placement of the order• Follow-up and expediting of the order• Verification of the invoice• Processing of discrepancies & rejections• Closing of completed orders• Maintenance of records & files

Packaging Engineering

• Material & form• Specification• Machinery• Methods of unitizing secondary tertiary

packaging• Delivery system

Materials Management

• Purchasing• Inventory Control• Traffic & Transportation• Receiving

– Warehousing– Production control