Chapter 5: Capacity and Location Planning 1
Chapter 5
Capacity and Location Planning
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Examples
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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
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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%
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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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
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Forecasting Purposes and Methods
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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
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Forecasting Methods
Informal (intuitive) Formal
Quantitative Qualitative
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Forecasting Methods
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Qualitative Methods
Life cycle Surveys Delphi Historical analogy Expert opinion Consumer panels Test marketing
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Quantitative Methods
Causal Input-output Econometric Box-Jenkins
Autoprojection Multiplicative Exponential smoothing Moving average
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Choosing a Forecasting Method
Availability of representative data Time and money limitations Accuracy needed
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Long-Term Capacity/Location Planning
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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
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Long-term Capacity Planning
Unit cost as function of facility size Economies of scale Economies of scope
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Envelope of Lowest Unit Output Costs with Facility Size
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Demand and Life Cycles for Multiple Outputs
Demand Seasonality Output Life Cycles
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Anti-cyclic Product Sales
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Forecast of Required Organizational Capacity from Multiple Life Cycles
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Timing of Capacity Increments
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Location Planning Strategies
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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
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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
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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
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Stage 2: Community
Availability of acceptable sites Local government attitudes Regulations, zoning, taxes, labor supply Tax Incentives Community’s attitude Amenities
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Breakeven Location Model
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Stage 3: Site
Size Adjoining land Zoning Drainage Soil Availability of water, sewers, utilities Development costs
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Weighted Score Model
Wi = importance of factor i
Si = score of location being evaluated on
factor i
i = an index for the factors
i
iiSW = score weightedTotal
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Locating Pure Service Organizations
Recipient to Facility facility utilization travel distance per citizen travel distance per visit
Facility to Recipient
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Short Term Capacity Planning
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Bottlenecks in Sequential Operations
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Efficiency and Output Increase when Machines are Being Added
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Product and Service Flows
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Process Flow Map for a Service
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Implementing the Theory of Constraints
Identify the system’s 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.
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Relationship between Capacity and Scheduling
Capacity is oriented toward the acquisition of productive resources
Scheduling related to the timing of the use of resources
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Gantt Charts for Capacity Planning and Scheduling (Infeasible)
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Gantt Charts for Capacity Planning and Scheduling (Feasible)
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Short-Term Capacity Alternatives
Increase resources Improve resource use Modify the output Modify the demand Do not meet demand
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Increase Resources
Overtime Add shifts Employ part-time workers Use floating workers Subcontract
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Improve Resource Use
Overlap or stagger shifts Schedule appointments Inventory output Backlog demand
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Modify the Output
Standardize the output Have recipient do part of the work Transform service operations into
inventoriable product operations Cut back on quality
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Demand Options
Modify the Demand change the price change the promotion
Do Not Meet Demand
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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
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The Learning Curve
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Background
In airframe manufacturing industry observed that each time output doubled, labor hour per plane decreased by fixed percentage
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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
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Typical Pattern of Learning and Forgetting
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Queuing and the Psychology of Waiting
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Waiting-Line Analysis
Mechanism to determine several key performance measures of operating system.
Trade-off two costs cost of waiting cost of service
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Waiting Line Analysis
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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.
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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.
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