Capacity and Location Planning

1
Chapter 5

• Capacity and Location Planning

2
Examples
3
Burger King

• Highly variable demand
• During lunch hour, demand can increase from 40 to
  800 hamburgers/hour
• Limited in ability to used inventory
• Facilities designed for flexible capacity
• During off peak times drive through staffed by
  one worker

4
Burger King continued

• During lunch hour drive through staffed by up to
  five workers who divide up the duties
• Second window can be used for customer with
  special orders
• Average transaction time reduced from 45 to 30
  seconds
• Sales during peak periods increased 50

5
Burger King continued

• Payroll costs as large as food costs
• Need to keep costs low but at same time meet
  highly variable demand
• BK-50 restaurant is 35 smaller and costs 27
  less to build, but can handle 40 more sales with
  less labor

6
Semiconductor Industry

• Learning from the steel industry
• Both industries require large and expensive
  factories
• 1980s steel industry started to abandon economies
  of scale justification and built minimills
• Chipmakers are now constructing smaller and more
  automated wafer fabs

7
Semiconductor Industry continued

• Short life cycles make it difficult to recoup 2
  billion it will cost to build wafer fab in 1998
• Payback time is 22-30 month to conventional wafer
  fab versus 10 months for minifab
• Processing time can be reduced from 60-90 days to
  7 days.

8
Mercedes-Benz

• Early 1990s investigated feasibility of producing
  luxury sports utility vehicle
• Project team established to find location for new
  plant
• Team charged with finding plant outside of
  Germany
• Team initially narrowed search to North America

9
Mercedes-Benz continued

• Team determined that North America location would
  minimize combined labor, shipping, and components
  cost
• Plans indicated production volume of 65,000
  vehicles per year and a breakeven volume of
  40,000 vehicles
• Sites further narrowed to sites within US
• Close to primary market

10
Mercedes-Benz continued

• Minimize penalties associated with currency
  fluctuations
• 100 sites in 35 state identified
• Primary concern was transportation cost
• Since half production was for export, focused on
  sites close to seaports, rail lines, and major
  highways

11
Mercedes-Benz continued

• Worker age and mix of skills also considered
• Sites narrowed to sites in NC, SC, and AL
• These sites relatively equal in terms of business
  climate, education level, transportation, and
  long-term costs
• AL chosen due to perception of high dedication to
  the project

12
Geographic Information Systems

• View and analyze data on digital maps
• Retail store in WI analyzed sales data on a map
• The map demonstrated that each store drew
  majority of sales from 20 mile radius
• Map highlighted area where only 15 of potential
  customers had visited one of its stores

13
Sport Obermeyer

• Highly volatile demand
• Combined costs of stockouts and markdowns can
  exceed manufacturing costs
• Determine which items can and cannot be predicted
  well
• Products that can be predicted produced furthest
  in advance
• Increased its sales of fashion skiwear 50 to
  100 over 3 year period in 1990s

14
Insights

• Capacity planning applies to both manufacturing
  and service organizations
• Capacity options can be categorized as short-term
  or long-term
• Changing staffing level is short-term
• Building new minifab is long-term

15
Insights continued

• Semiconductor industry illustrates the enormous
  cost often associated with expanding capacity
• Shorter product life cycles add further
  complications
• Volatile demand can further complicate capacity
  planning

16
Introduction

• Capacity needs determined on the basis of
  forecast of demand.
• In addition to determining capacity needed, the
  location of the capacity must also be determined.
• Mercedes-Benz example illustrates that location
  decisions are often made in stages.

17
Sport Obermeyer

• Highly volatile demand
• Combined costs of stockouts and markdowns can
  exceed manufacturing costs
• Determine which items can and cannot be predicted
  well
• Products that can be predicted produced furthest
  in advance
• Increased its sales of fashion skiwear 50 to
  100 over 3 year period in 1990s

18
Forecasting Purposes and Methods
19
Primary Uses of Forecasting

• To determine if sufficient demand exists
• To determine long-term capacity needs
• To determine midterm fluctuations in demand so
  that short-sighted decisions are not made that
  hurt company in long-run
• To determine short-term fluctuations in demand
  for production planning, workforce scheduling,
  and materials planning

20
Forecasting Methods

• Informal (intuitive)
• Formal
• Quantitative
• Qualitative

21
Forecasting Methods
22
Qualitative Methods

• Life cycle
• Surveys
• Delphi
• Historical analogy
• Expert opinion
• Consumer panels
• Test marketing

23
Quantitative Methods

• Causal
• Input-output
• Econometric
• Box-Jenkins
• Autoprojection
• Multiplicative
• Exponential smoothing
• Moving average

24
Choosing a Forecasting Method

• Availability of representative data
• Time and money limitations
• Accuracy needed

25
Long-Term Capacity/Location Planning
26
Terminology

• Maximum rate of output of the transformation
  system over some specified duration
• Capacity issues applicable to all organizations
• Often services cannot inventory output
• Bottlenecks
• Yield (or revenue) management

27
Long-term Capacity Planning

• Unit cost as function of facility size
• Economies of scale
• Economies of scope

28
Envelope of Lowest Unit Output Costs with
Facility Size
29
Demand and Life Cycles for Multiple Outputs

• Demand Seasonality
• Output Life Cycles

30
Anti-cyclic Product Sales
31
Forecast of Required Organizational Capacity from
Multiple Life Cycles
32
Timing of Capacity Increments
33
Location Planning Strategies
34
Capabilities and the Location Decision

• Often driven too much by short-term
  considerations
• wage rates
• exchange rates
• Better approach is to consider how location
  impacts development of long-term capabilities

35
Six Step Process

• Identify sources of value
• Identify capabilities needed
• Assess implications of location decision on
  development of capabilities
• Identify potential locations
• Evaluate locations
• Develop strategy for building network of locations

36
Stage 1 Regional-International

• Minimize transportation costs and provide
  acceptable service
• Proper supply of labor
• Wage rates
• Unions (right-to-work laws)
• Regional taxes, regulations, trade barriers
• Political stability

37
Stage 2 Community

• Availability of acceptable sites
• Local government attitudes
• Regulations, zoning, taxes, labor supply
• Tax Incentives
• Communitys attitude
• Amenities

38
Breakeven Location Model
39
Stage 3 Site

• Size
• Adjoining land
• Zoning
• Drainage
• Soil
• Availability of water, sewers, utilities
• Development costs

40
Weighted Score Model

• Wi importance of factor i
• Si score of location being evaluated on
• factor i
• i an index for the factors

41
Locating Pure Service Organizations

• Recipient to Facility
• facility utilization
• travel distance per citizen
• travel distance per visit
• Facility to Recipient

42
Short Term Capacity Planning
43
Bottlenecks in Sequential Operations
44
Efficiency and Output Increase when Machines are
Being Added
45
Product and Service Flows
46
Process Flow Map for a Service
47
Implementing the Theory of Constraints

• Identify the systems constraints
• Exploit the constraint
• Subordinate all else to the constraint
• Elevate the constraint
• If constraint is no longer a bottleneck, find the
  next constraint and repeat the steps.

48
Relationship between Capacity and Scheduling

• Capacity is oriented toward the acquisition of
  productive resources
• Scheduling related to the timing of the use of
  resources

49
Gantt Charts for Capacity Planning and Scheduling
(Infeasible)
50
Gantt Charts for Capacity Planning and Scheduling
(Feasible)
51
Short-Term Capacity Alternatives

• Increase resources
• Improve resource use
• Modify the output
• Modify the demand
• Do not meet demand

52
Increase Resources

• Overtime
• Add shifts
• Employ part-time workers
• Use floating workers
• Subcontract

53
Improve Resource Use

• Overlap or stagger shifts
• Schedule appointments
• Inventory output
• Backlog demand

54
Modify the Output

• Standardize the output
• Have recipient do part of the work
• Transform service operations into inventoriable
  product operations
• Cut back on quality

55
Demand Options

• Modify the Demand
• change the price
• change the promotion
• Do Not Meet Demand

56
Capacity Planning for Services

• Large fluctuations in demand
• Inventory often not an option
• Problem often is to match staff availability with
  customer demand
• May attempt to shift demand to off-peak periods
• Can measure capacity in terms of inputs

57
The Learning Curve
58
Background

• In airframe manufacturing industry observed that
  each time output doubled, labor hour per plane
  decreased by fixed percentage

59
Learning Curve Function

• M mNr
• M labor-hours for Nth unit
• m labor-hours for first unit
• N number of units produced
• r exponent of curve
• log(learning rate)/0.693

60
Typical Pattern of Learning and Forgetting
61
Queuing and the Psychology of Waiting
62
Waiting-Line Analysis

• Mechanism to determine several key performance
  measures of operating system.
• Trade-off two costs
• cost of waiting
• cost of service

63
Waiting Line Analysis
64
Principles of Waiting

• Unoccupied time feels longer than occupied time.
• Pre-service waiting feels longer than in-service
  waiting.
• Anxiety makes waiting seem longer.
• Uncertain waiting is longer than known, finite
  waiting.

65
Principles of Waiting continued

• Unexplained waiting is longer than explained
  waiting.
• Unfair waiting is longer than fair waiting.
• Solo waiting is longer than group waiting.
• The more valuable the service, the longer it is
  worth waiting for.

66
(No Transcript)