fvfdv

1. 1-1 Introduction to Operations Management
Introduction-
Operations as a Competitive
Weapon

2. 1-2 Introduction to Operations Management
Operations-A Process ViewOperations-A Process View
Inputs
Land
Labor
Capital
Transformation/
Conversion
process
Outputs
Goods
Services
Control
Feedback
FeedbackFeedback

3. 1-3 Introduction to Operations Management
Operations Management-Definition
• The operations function
– Consists of all activities directly related to
producing goods or providing services
The management of systems or processes
that create goods and/or provide services

4. 1-4 Introduction to Operations Management
Food ProcessorFood Processor
Inputs Processing Outputs
Raw Vegetables Cleaning Canned
vegetablesMetal Sheets Making cans
Water Cutting
Energy Cooking
Labor Packing
Building Labeling
Equipment
Table 1.2

5. 1-5 Introduction to Operations Management
Hospital ProcessHospital Process
Inputs Processing Outputs
Doctors, nurses Examination Healthy
patientsHospital Surgery
Medical Supplies Monitoring
Equipment Medication
Laboratories Therapy
Table 1.2

6. 1-6 Introduction to Operations Management
Manufacturing vs ServiceManufacturing vs Service
Characteristic Manufacturing Service
Output
Customer contact
Uniformity of input
Labor content
Uniformity of output
Measurement of productivity
Opportunity to correct
Tangible
Low
High
Low
High
Easy
High
Intangible
High
Low
High
Low
Difficult
Low
quality problems
High

7. 1-7 Introduction to Operations Management
Goods and Services-Key Differences
1. Customer contact
2. Uniformity of input
3. Labor content of jobs
4. Uniformity of output
5. Measurement of productivity
6. Production and delivery
7. Quality assurance
8. Amount of inventory

8. 1-8 Introduction to Operations Management
Business Operations OverlapBusiness Operations Overlap
Operations
FinanceMarketing

9. 1-9 Introduction to Operations Management
Adding Value-The Value ChainAdding Value-The Value Chain
The difference between the cost of inputs
and the value or price of outputs.
Inputs
Land
Labor
Capital
Transformation/
Conversion
process
Outputs
Goods
Services
Control
Feedback
FeedbackFeedback
Value added

10. 1-10 Introduction to Operations Management
Operations-The Supply Chain View
Copyright © 2010 Pearson Education,
Inc. Publishing as Prentice Hall.
Support Processes
Externalsuppliers
Externalcustomers
Supplier
relationship
process
Internal
processes
Customer
relationship
management
Figure 1.4

11. 1-11 Introduction to Operations Management
Business Operations OverlapBusiness Operations Overlap
Operations
CorporateMarketing

12. 1-12 Introduction to Operations Management
1-12
Flows in a Supply Chain
Customer
Information
Product
Funds

13. 1-13 Introduction to Operations Management
Global Environment and Challenges for
Operations Managers
• Global Competition
• Productivity Improvement-service sector
productivity gains much lower in comparison
with the manufacturing sector
• Rapid Technological Change
• Ethical, Workforce Diversity and
Environmental Issues

14. 1-14 Introduction to Operations Management
Operations Management Decisions
• Strategic
• Planning
• Tactical

15. 1-15 Introduction to Operations Management
Operations Management Tools and
Techniques
• Forecasting
• Lean Systems
• Operations Research

16. 1-16 Introduction to Operations Management
Forecasting

17. 1-17 Introduction to Operations Management
FORECAST:
• A statement about the future
• Used to help managers
– Plan the system
– Plan the use of the system

18. 1-18 Introduction to Operations Management
Forecast Uses
• Plan the system
– Generally involves long-range plans related to:
• Types of products and services to offer
• Facility and equipment levels
• Facility location
• Plan the use of the system
– Generally involves short- and medium-range plans related to:
• Inventory management
• Workforce levels
• Purchasing
• Budgeting

19. 1-19 Introduction to Operations Management
• Assumes causal system
past ==> future
• Forecasts rarely perfect because of
randomness
• Forecasts more accurate for
groups vs. individuals
• Forecast accuracy decreases
as time horizon increases
I see that you will
get an A this quarter.
Common Features

20. 1-20 Introduction to Operations Management
Elements of a Good Forecast
Timely
AccurateReliable
M
eaningful
Written
Easy
to
use
Cost effective

21. 1-21 Introduction to Operations Management
Steps in the Forecasting Process
Step 1 Determine purpose of forecast
Step 2 Establish a time horizon
Step 3 Select a forecasting technique
Step 4 Gather and analyze data
Step 5 Make the forecast
Step 6 Monitor the forecast
“The forecast”

22. 1-22 Introduction to Operations Management
Types of Forecasts
• Judgmental - uses subjective inputs (qualitative)
• Time series - uses historical data assuming the
future will be like the past (quantitative)
• Associative models - uses explanatory variables
to predict the future (quantitative)

23. 1-23 Introduction to Operations Management
Judgmental Forecasts
(Qualitative)
•Consumer surveys
•Delphi method
•Executive opinions
– Opinions of managers and staff
•Sales force.

24. 1-24 Introduction to Operations Management
Time Series Forecasts
• Trend - long-term movement in data
• Seasonality - short-term regular variations in
data
• Cycle – wavelike variations of more than one
year’s duration
• Irregular variations - caused by unusual
circumstances
• Random variations (Stable)- caused by
chance

25. 1-25 Introduction to Operations Management
Forecast Variations
Trend
Irregular
variation
Seasonal variations
90
89
88
Figure 3.1
Cycles
Random
variation

26. 1-26 Introduction to Operations Management
Time Series Forecasts-Methods
• Naive
• Averaging
• Trend
• Seasonality
• Exponential smoothing

27. 1-27 Introduction to Operations Management
Naive Method
Uh, give me a minute....
We sold 250 wheels last
week.... Now, next week
we should sell....
The forecast for any period equals
the previous period’s actual value.

28. 1-28 Introduction to Operations Management
Naïve Method
• Simple to use
• Virtually no cost
• Quick and easy to prepare
• Data analysis is nonexistent
• Easily understandable
• Cannot provide high accuracy
• Can be a standard for accuracy

29. 1-29 Introduction to Operations Management
Naïve Method
• Stable time series data
• Seasonal variations
– Next value in a series will equal the previous value in a
comparable period
• Data with trends
– F(t) = A(t-1) + (A(t-1) – A(t-2))

30. 1-30 Introduction to Operations Management
Averaging Method
• Simple moving average
• Weighted moving average

31. 1-31 Introduction to Operations Management
Moving Averages
• Simple Moving average – A technique that
averages a number of recent actual values,
updated as new values become available.
• Weighted moving average – More recent values in
a series are given more weight in computing the
forecast.
MAn =
n
Aii = 1
∑
n

32. 1-32 Introduction to Operations Management
Simple Moving Average
MAn =
n
Aii = 1
∑
n
35
37
39
41
43
45
47
1 2 3 4 5 6 7 8 9 10 11 12
Actual
MA3
MA5

33. 1-33 Introduction to Operations Management
Trend Method-Linear Trend Equation
• Ft = Forecast for period t
• t = Specified number of time periods
• a = Value of Ft at t = 0
• b = Slope of the line
Ft = a + bt
0 1 2 3 4 5 t
Ft

34. 1-34 Introduction to Operations Management
Calculating a and b
b =
n (ty) - t y
n t2 - ( t)2
a =
y - b t
n
∑∑∑
∑∑
∑∑

35. 1-35 Introduction to Operations Management
Linear Trend Equation Example
t y
W e e k t
2
S a le s ty
1 1 1 5 0 1 5 0
2 4 1 5 7 3 1 4
3 9 1 6 2 4 8 6
4 1 6 1 6 6 6 6 4
5 2 5 1 7 7 8 8 5
Σ t = 1 5 Σ t
2
= 5 5 Σ y = 8 1 2 Σ ty = 2 4 9 9
( Σ t)
2
= 2 2 5

36. 1-36 Introduction to Operations Management
Linear Trend Calculation
y = 143.5 + 6.3t
a =
812 - 6.3(15)
5
=
b =
5 (2499) - 15(812)
5(55) - 225
=
12495-12180
275-225
= 6.3
143.5

37. 1-37 Introduction to Operations Management
Seasonality
• Multiplicative Model
Demand=Trend x Seasonality (Seasonal Index)
Seasonality is the percentage of average (or
trend) amount

38. 1-38 Introduction to Operations Management
Exponential Smoothing
• Next forecast=α(Actual)+(1- α)(Previous
forecast)
• α is the Smoothing Constant

39. 1-39 Introduction to Operations Management
Associative Forecasting
• Predictor variables and variables of interest
• Simple Linear Regression – linear variation
between the two variables
• Correlation coefficient r gives an indication of
the strength of relationship between the two
variables.
• http://en.wikipedia.org/wiki/Pearson_product-m
• r2>0.8 good prediction;<0.25 poor prediction

40. 1-40 Introduction to Operations Management
Forecast Accuracy
• Error - difference between actual value and predicted
value
• Mean Absolute Deviation (MAD)
– Average absolute error
• Mean Squared Error (MSE)
– Average of squared error
• Mean Absolute Percent Error (MAPE)
– Average absolute percent error

41. 1-41 Introduction to Operations Management
MAD, MSE, and MAPE
MAD =
Actual forecast−∑
n
MSE =
Actual forecast)
-1
2
−∑
n
(
MAPE =
Actual forecast−
n
/ Actual*100)∑(

42. 1-42 Introduction to Operations Management
Example 10
Period Actual Forecast (A-F) |A-F| (A-F)^2 (|A-F|/Actual)*100
1 217 215 2 2 4 0.92
2 213 216 -3 3 9 1.41
3 216 215 1 1 1 0.46
4 210 214 -4 4 16 1.90
5 213 211 2 2 4 0.94
6 219 214 5 5 25 2.28
7 216 217 -1 1 1 0.46
8 212 216 -4 4 16 1.89
-2 22 76 10.26
MAD= 2.75
MSE= 10.86
MAPE= 1.28

43. 1-43 Introduction to Operations Management
Controlling the Forecast
• Control chart
• Tracking signal

44. 1-44 Introduction to Operations Management
Control chart
• Control chart
– A visual tool for monitoring forecast errors
– Used to detect non-randomness in errors
• Control limits:
UCL=0+z√MSE;LCL=0-z√MSE (z typically=2 or 3)
• Forecasting errors are in control if
– All errors are within the control limits
– No patterns, such as trends are present

45. 1-45 Introduction to Operations Management
Tracking Signal
Tracking signal =
(Actual-forecast)
MAD
∑
•Tracking signal
–Ratio of cumulative error to MAD
Bias – Persistent tendency for forecasts to be
Greater or less than actual values.
Value of zero would be ideal for Tracking signal.
Limits of +/-4 or +/- 5are often used for a range of
acceptable values of the tracking signal.

46. 1-46 Introduction to Operations Management
Sources of Forecast errors
• Model may be inadequate
• Irregular variations
• Incorrect use of forecasting technique

47. 1-47 Introduction to Operations Management
Choosing a Forecasting Technique
• No single technique works in every situation
• Two most important factors
– Cost
– Accuracy
• Other factors include the availability of:
– Historical data
– Computers
– Time needed to gather and analyze the data
– Forecast horizon

48. 1-48 Introduction to Operations Management
Operations Research

49. 1-49 Introduction to Operations Management
49
What is Operations Research?
• Operations Research is the scientific
approach to execute decision making, which
consists of:
– The art of mathematical modeling of
complex situations
– The science of the development of solution
techniques used to solve these models
– The ability to effectively communicate the
results to the decision maker

50. 1-50 Introduction to Operations Management
50
Operations Research Models
Deterministic Models Stochastic Models
• Linear Programming • Discrete-Time Markov Chains
• Network Optimization • Continuous-Time Markov Chains
• Integer Programming • Queuing Theory (waiting lines)
• Nonlinear Programming • Decision Analysis
• Inventory Models Game Theory
Inventory models
Simulation

51. 1-51 Introduction to Operations Management
CHAPTER
9
Management
of Quality

52. 1-52 Introduction to Operations Management
Agenda
• Insights on Quality Management
– Defining Quality
– Dimensions and Determinants
– The Consequences of Poor Quality
– Responsibility for Quality
– The Costs of Quality
– Ethics and Quality Management

53. 1-53 Introduction to Operations Management
Agenda Contd.
• The Evolution of Quality
• Total Quality Management (TQM)
– TQM Tools
– Quality Function Deployment (QFD)
• Six-Sigma Quality Control

54. 1-54 Introduction to Operations Management
Defining Quality-Dimensions of Quality
– Performance - main characteristics of the
product/service
– Aesthetics - appearance, feel, smell, taste
– Special Features - extra characteristics
– Conformance - how well product/service
conforms to customer’s expectations
– Reliability - consistency of performance

55. 1-55 Introduction to Operations Management
Dimensions of Quality (Cont’d)
– Durability - useful life of the product/service
– Perceived Quality - indirect evaluation of quality
(e.g. reputation)
– Serviceability - service after sale

56. 1-56 Introduction to Operations Management
Examples of Quality Dimensions
Dimension
1. Performance
2. Aesthetics
3. Special features
(Product)
Automobile
Everything works, fit &
finish
Ride, handling, grade of
materials used
Interior design, soft touch
Gauge/control placement
Cellular phone, CD
player
(Service)
Auto Repair
All work done, at agreed
price
Friendliness, courtesy,
Competency, quickness
Clean work/waiting area
Location, call when ready
Computer diagnostics

57. 1-57 Introduction to Operations Management
Examples of Quality Dimensions (Cont’d)
Dimension
5. Reliability
6. Durability
7. Perceived
quality
8. Serviceability
(Product)
Automobile
Infrequency of breakdowns
Useful life in miles, resistance
to rust & corrosion
Top-rated car
Handling of complaints and/or
requests for information
(Service)
Auto Repair
Work done correctly,
ready when promised
Work holds up over
time
Award-winning service
department
Handling of complaints

58. 1-58 Introduction to Operations Management
Defining Quality-Determinants of
Quality
Service
Ease of
use
Conforms
to design
Design

59. 1-59 Introduction to Operations Management
The Consequences of Poor Quality
• Loss of business
• Liability
• Productivity
• Costs

60. 1-60 Introduction to Operations Management
• Top management
• Design
• Procurement
• Production/operations
• Quality assurance
• Packaging and shipping
• Marketing and sales
• Customer service
Responsibility for Quality

61. 1-61 Introduction to Operations Management
Costs of Quality
• Failure Costs - costs incurred by defective
parts/products or faulty services.
• Internal Failure Costs
– Costs incurred to fix problems that are detected
before the product/service is delivered to the
customer.
• External Failure Costs
– All costs incurred to fix problems that are
detected after the product/service is delivered
to the customer.

62. 1-62 Introduction to Operations Management
Costs of Quality (continued)
• Appraisal Costs
– Costs of activities designed to ensure quality or
uncover defects
• Prevention Costs
– All TQ training, TQ planning, customer
assessment, process control, and quality
improvement costs to prevent defects from
occurring

63. 1-63 Introduction to Operations Management
• Substandard work
– Defective products
– Substandard service
– Poor designs
– Shoddy workmanship
– Substandard parts and materials
Ethics and Quality
Having knowledge of this and failing to correct
and report it in a timely manner is unethical.

64. 1-64 Introduction to Operations Management
1980–TotalQuality1980–TotalQuality
1970–QualityManagementPrograms1970–QualityManagementPrograms
1960–QualityWarranty1960–QualityWarranty
1930–StatisticalControl1930–StatisticalControl
1920–Inspection1920–Inspection
1900–Supervision1900–Supervision
1900–Manpowerpredominance1900–ManpowerpredominanceThe Evolution of Quality-Century of
Quality
2000-...2000-...

65. 1-65 Introduction to Operations Management
Total Quality Management (TQM)
A philosophy that involves everyone in an
organization in a continual effort to improve
quality and achieve customer satisfaction.
T Q M

66. 1-66 Introduction to Operations Management
TQM Tools
Purpose of the Tool Quality Control tools Management tools
Problem solving Control charts
Histograms
Check sheets
Pareto diagrams
Scatter diagrams
Graphs
Cause and Effect diagram
Operational Planning Arrow diagram
Poka yoke
Strategic Planning Quality function deployment
Plan-Do-Check-Act (PDCA)

67. 1-67 Introduction to Operations Management
QFD
 Identify customer wants
 Identify how the good/service will satisfy customer
wants
 Relate customer wants to product hows
 Identify relationships between the firm’s hows
 Develop importance ratings
 Evaluate competing products
 Compare performance to desirable technical attributes

68. 1-68 Introduction to Operations Management
QFD House of Quality
Relationship
matrix
How to satisfy
customer wants
Interrelationships
Competitive
assessment
Technical
evaluation
Target values
What the
customer
wants
CustomerCustomer
importanceimportance
ratingsratings
WeightedWeighted
ratingrating

69. 1-69 Introduction to Operations Management
House of Quality Example
Your team has been charged withYour team has been charged with
designing a new camera for Greatdesigning a new camera for Great
Cameras, Inc.Cameras, Inc.
The first action isThe first action is
to construct ato construct a
House of QualityHouse of Quality

70. 1-70 Introduction to Operations Management
House of Quality Example
CustomerCustomer
importanceimportance
ratingrating
(5 = highest)(5 = highest)
Lightweight 3
Easy to use 4
Reliable 5
Easy to hold steady 2
Color correction 1
What theWhat the
customercustomer
wantswants
What the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors

71. 1-71 Introduction to Operations Management
House of Quality Example
What the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors
Lowelectricityrequirements
Aluminumcomponents
Autofocus
Autoexposure
Paintpallet
Ergonomicdesign
How to Satisfy
Customer Wants

72. 1-72 Introduction to Operations Management
Lightweight 3
Easy to use 4
Reliable 5
Easy to hold steady 2
Color corrections 1
House of Quality Example
What the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors
High relationshipHigh relationship
Medium relationshipMedium relationship
Low relationshipLow relationship
Relationship matrixRelationship matrix

73. 1-73 Introduction to Operations Management
House of Quality Example
What the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors
Lowelectricityrequirements
Aluminumcomponents
Autofocus
Autoexposure
Paintpallet
Ergonomicdesign
RelationshipsRelationships
between thebetween the
things we can dothings we can do

74. 1-74 Introduction to Operations Management
House of Quality Example
WeightedWeighted
ratingrating
What the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors
Lightweight 3
Easy to use 4
Reliable 5
Easy to hold steady 2
Color corrections 1
Our importance ratings 22 9 27 27 32 25

75. 1-75 Introduction to Operations Management
House of Quality Example
CompanyA
CompanyB
G P
G P
F G
G P
P P
Lightweight 3
Easy to use 4
Reliable 5
Easy to hold steady 2
Color corrections 1
Our importance ratings 22 5
How well doHow well do
competing productscompeting products
meet customer wantsmeet customer wants
What the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors

76. 1-76 Introduction to Operations Management
House of Quality ExampleWhat the
Customer
Wants
Relationship
Matrix
Technical
Attributes and
Evaluation
How to Satisfy
Customer Wants
Interrelationships
Analysisof
Competitors
Target
values
(Technical
attributes)
Technical
evaluation
Company A 0.7 60% yes 1 ok G
Company B 0.6 50% yes 2 ok F
Us 0.5 75% yes 2 ok G
0.5A
75%
2’to∞
2circuits
Failure1per10,000
Panelranking

77. 1-77 Introduction to Operations Management
House of Quality Example
CompletedCompleted
House ofHouse of
QualityQuality
Lightweight 3
Easy to use 4
Reliable 5
Easy to hold steady 2
Color correction 1
Our importance ratings
Lowelectricityrequirements
Aluminumcomponents
Autofocus
Autoexposure
Paintpallet
Ergonomicdesign
CompanyA
CompanyB
G P
G P
F G
G P
P P
Target values
(Technical
attributes)
Technical
evaluation
Company A 0.7 60% yes 1 ok G
Company B 0.6 50% yes 2 ok F
Us 0.5 75% yes 2 ok G
0.5A
75%
2’to∞
2circuits
Failure1per10,000
Panelranking
22 9 27 27 32 25

78. 1-78 Introduction to Operations Management
House of Quality Sequence
Design
characteristics
Specific
components
House
2
Customer
requirements
Design
characteristics
House
1
Specific
components
Production
process
House
3
Production
process
Quality
plan
House
4
Figure 5.4Figure 5.4
Deploying resources through theDeploying resources through the
organization in response toorganization in response to
customer requirementscustomer requirements

79. 1-79 Introduction to Operations Management
Six Sigma Quality Control
• Application of statistical tools
• New approach to process control
• Enables organizations to improve their
quality to near-zero defect levels