Transcript Engineering Mangement

Chapter 12
Managing Production Operations
1
Advanced Organizer
Managing Engineering and Technology
Management Functions
Planning
Decision Making
Organizing
Leading
Controlling
Managing Technology
Personal Technology
Research
Time Management
Design
Ethics
Production
Career
Quality
Marketing
Project Management
2
Chapter Objectives
• Explain and be able to use the statistics of
quality
• Describe the quality revolution
• Recognize the methods of work measurement
3
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
4
Definitions of Quality
Fitness for use, or customer satisfaction
• Quality of design
• Quality of conformance ( or Quality of
production)
5
The Meaning of Quality
The Meaning of Quality
Producer’s Perspective
Production
Quality of Conformance
• Conformance to Spec.
• Cost
Consumer’s
Perspective
Quality of Design
• Quality Char.
• Price
Marketing
Fitness for Consumer
Use
6
Quality Of Conformance
• Ensuring product or service produced
according to design
• Depends on
–design of production process
–performance of machinery
–materials
–training
7
Dimensions of Product Quality
1. Performance -- basic operating characteristics
2. Features --“extra” items added to basic features
3. Reliability -- probability product will operate over time
4. Conformance --meeting pre-established standards
5. Durability -- life span before replacement
6. Serviceability -- ease of getting repairs, speed &
competence of repairs
7. Aesthetics -- look, feel, sound, smell or taste
8. Safety --freedom from injury or harm
9. Other perceptions--subjective perceptions based on brand
name, advertising, etc
8
Service Quality
1. Time & Timeliness -- customer waiting time, completed on
time
2. Completeness -- customer gets all they asked for
3. Courtesy -- treatment by employees
4. Consistency -- same level of service for all customers
5. Accessibility & Convenience -- ease of obtaining service
6. Accuracy -- performed right every time
7. Responsiveness -- reactions to unusual situations
9
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
10
Quality Improvement
and Quality Cost
$
Total Quality Cost
Failure Cost
Appraisal Cost
Prevention Cost
Increasing Quality
11
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
12
Statistical Process Control
•
•
•
•
Take periodic samples from process
Plot sample points on control chart
Determine if process is within limits
Prevent quality problems
13
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
14
Probability Distribution
• Central tendency
– Mean, Mode, Median
• Dispersion
– Std. deviation, Variance
• Frequency function
– Normal, Binomial, Poisson
15
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
16
SPC Applied To Services
• Nature of defect is different in services
• Service defect is a failure to meet
customer requirements
• Monitor times, customer satisfaction
17
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
18
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
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The Normal Distribution
95%
99.73%
-3
-2
-1
=0 1
2
3
20
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
21
Process Control Chart
Upper
control
limit
Central
Line
Lower
control
limit
1
2
3
4
5
6
7
8
9
10
Sample number
22
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
23
Development of Control Charts
1. Based on in-control data
2. If non-random causes present, discard
data
3. Correct control chart limits
24
Control Charts For Attributes
• p Charts
–Calculate percent defectives in sample
• c Charts
–Count number of defects in item
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p-Chart
UCL  p  z  p
LCL  p  z  p
p 
p(1  p )
n
p  average % defective in sample
n = sample size
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p-Chart Example
20 samples of 100 pairs of jeans
Proportion
Defective
Sample #
1
# Defects
6
2
0
0.00
3
4
0.04
….
….
….
20
18
0.18
200
0.10
0.06
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p-Chart Calculations
total defectives
total observatio ns
200

20(100)
 0.10
p
p(1  p )
0.10(1  0.10)
UCL  p  z
 0.10  3
 0.190
n
100
p(1  p )
0.10(1  0.10)
LCL  p  z
 0.10  3
 0.010
n
100
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Example p-Chart
0.20
0.18
Proportion defective
0.16
0.14
0.12
0.10
0.08
0.06
0.04
0.02
00
0
2
4
6
8
10
12
14
16
18
20
Sample number
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c-Chart
Total # defects
Process average  c 
# samples
Sample standard deviation =  c  c
UCL  c + z c
LCL  c - z c
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c-Chart Example
Count # of defects in 15 rolls of denim fabric
Sample #
1
# Defects
12
2
3
….
8
16
…
15
Total
15
190
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c-Chart Calculations
190
c
 12.67
15
UCL  c + z c  12.67  3 12.67  23.35
LCL  c - z c  12.67  3 12.67  1.99
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Example c-Chart
Number of defects
24
21
18
15
12
9
6
3
0
2
4
6
8
10
12
14
Sample number
33
Control Charts for Variables
• Mean chart (X-Bar Chart)
– Monitors central tendency
• Dispersion chart
– R-Chart
– s-Chart
– Monitors amount of variation
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Range (R) Chart
R

R
k
R  range of each sample
k  number of samples
UCL  D4 R
LCL  D3 R
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R-Chart Example
Slip-ring diameter (cm) (sample size =5)
Sample Obs. 1
Obs. 2
Obs. 3
Obs. 4
Obs. 5
X
R
1
5.02
5.01
4.94
4.99
4.96
4.98
0.08
2
5.01
5.03
5.07
4.95
4.96
5.00
0.12
3
4.99
5.00
4.93
4.92
4.99
4.97
0.08
:
:
:
:
:
:
:
:
10
5.01
4.98
5.08
5.07
4.99
5.03
0.10
50.09
1.15

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3 Control Chart Factors
Sample size
n
2
3
4
5
6
7
8
X -chart
A2
1.88
1.02
0.73
0.58
0.48
0.42
0.37
R-chart
D3
0
0
0
0
0
0.08
0.14
D4
3.27
2.57
2.28
2.11
2.00
1.92
1.86
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R-Chart Calculations
R 1.15

R

 0.115
k
10
UCL  D4 R  2.11(0.115)  0.243
LCL  D3 R  0(0.115)  0
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Example R-Chart
0.30
Range
0.25
0.20
0.15
0.10
0.05
0.00
1
2
3
4
5
6
7
8
9
10
Sample
39
X-bar Chart Calculations
x
x
x
1
2
   xk
k
50.09

 5.01cm
10
UCL  x  A 2 R  5.01  0.58.115  5.08
LCL  x  A 2 R  5.01  0.58.115  4.94
x  average of sample means
R  average range value
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Example X-bar Chart
5.100
5.050
5.000
X-bar
4.950
4.900
4.850
1
2
3
4
5
6
7
8
9
10
Sample
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Using X-bar and R-Charts Together
• Each measures process differently
• Process average and variability must be in
control
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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
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Zones For Pattern Tests
UCL
Zone A
3 sigma  x  A2 R
Zone B
Zone C
CL







x
Zone C
Zone B
Zone A
LCL

2
A2 R
3
1
1 sigma  x 
A2 R
3
2 sigma  x 
1 sigma  x 
1
A2 R
3
2 sigma  x 
2
A2 R
3
3 sigma  x  A2 R
44
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.
45
Control Chart Patterns
UCL
UCL
LCL
LCL
Sample observations
consistently below the
center line
Sample observations
consistently above the
center line
46
Control Chart Patterns
UCL
UCL
LCL
LCL
Sample observations
consistently increasing
Sample observations
consistently decreasing
47
Inspection & Sampling
• 100% inspection
– only with automated inspection
• Sampling inspection
– Single sampling
– Double sampling
– Multiple sampling
48
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
49
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
50
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
51
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
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Operating Characteristic (OC)
Curve
• Shows probability of lot acceptance
• Based on
– sampling plan
– quality level of lot
• Indicates discriminating power of plan
53
Operating Characteristic Curve
 = 0.05
{ 1.00
Probability of
acceptance, Pa
0.80
OC curve for n and c
0.60
0.40
0.20
 = 0.10
{
0.00
0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20
AQL
Proportion defective
LTPD
54
Ideal OC Curve
1.00
Probability of
acceptance, Pa
0.80
0.60
0.40
0.20
0.00
0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20
AQL
Proportion defective
55
Average Outgoing Quality (AOQ)
• Expected number of defective items
passed to customer
• Average outgoing quality limit (AOQL) is
the maximum point on AOQ curve
56
AOQ Curve
0.015
AOQL
Average 0.010
Outgoing
Quality
0.005
0.000
0.01 0.02
AQL
0.03 0.04 0.05
0.06
0.07
(Incoming) Percent Defective
0.08 0.09 0.10
LTPD
57
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
58
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
59
Choosing a Sampling Plan
• An economic decision
• Single sampling plans
– high sampling costs, low administration
• Double/Multiple sampling plans
– low sampling costs, high administration
60
Taguchi Methods
LSL m
USL
LSL m
USL
LSL m
USL
LSL m
USL
61
Taguchi Methods
• Deviation from ideal value => “loss of society”
L = k (y – T)2
• Use ANOVA to identify the sources of variation
Loss
y
LSL
T
USL
62
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
63
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.
64
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.
65
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.
66
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.
67
Deming Wheel (PDCA Cycle)
4. Act
Institute the
improvement:
continue the
cycle
3. Check/Study
Assess the
plan: Is it
working?
1. Plan
Identify the
problem &
develop the
plan for
improvement
2. Do
Implement
the plan on a
test basis
68
Total Quality Management
1. Customer defined quality
2. Top management leadership
3. Quality as a strategic issue
4. All employees responsible for quality
5. Continuous improvement
6. Shared problem solving
7. Statistical quality control
8. Training & education for all employees
69
TQM Throughout The Organization
•
•
•
•
•
•
•
Marketing, sales, R&D
Engineering
Purchasing
Personnel
Management
Packing, storing, shipping
Customer service
70
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
71
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
72
Quality And Productivity
• Productivity
= Output produced per unit of resources
= output / input
• Fewer defects increase output
• Quality improvement reduces inputs
73
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.
74
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.
75
Uses of Time Standards
–
–
–
–
–
–
–
–
–
–
–
–
–
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
76
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
77
Work Measurement
Engineered Time Standards
– Basic Time-Study Method
• Define work cycle
• Take time measurements
• Apply rating & allowance
– Methods-time Measurement (MTM)
78
Work Measurement
Criticism:
– Direct labor only
– Productivity, not quality
79
Maintenance
Types of Maintenance
• Corrective maintenance
• Preventive maintenance
• Predictive maintenance
– preventive maintenance that use sensitive
instruments to predict trouble
80
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"
81
Human Resources Management
•
•
•
•
•
•
Recruiting & employment
Equal Employment Opportunity
Industrial relations
Compensation
Education & training
Employee benefits
82
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
83
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
84
Packaging Engineering
•
•
•
•
Material & form
Specification
Machinery
Methods of unitizing secondary tertiary
packaging
• Delivery system
85
Materials Management
•
•
•
•
Purchasing
Inventory Control
Traffic & Transportation
Receiving
– Warehousing
– Production control
86