Chapter 5: Capacity and Location Planning1 Chapter 5 Capacity and Location Planning

Chapter 5: Capacity and Location Planning 1

Chapter 5

Capacity and Location Planning


Examples


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


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%


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


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


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.


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


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



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



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


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


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


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


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


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.


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


Forecasting Purposes and Methods


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


Forecasting Methods

Informal (intuitive) Formal

Quantitative Qualitative


Forecasting Methods


Qualitative Methods

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


Quantitative Methods

Causal Input-output Econometric Box-Jenkins

Autoprojection Multiplicative Exponential smoothing Moving average


Choosing a Forecasting Method

Availability of representative data Time and money limitations Accuracy needed


Long-Term Capacity/Location Planning


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


Long-term Capacity Planning

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


Envelope of Lowest Unit Output Costs with Facility Size


Demand and Life Cycles for Multiple Outputs

Demand Seasonality Output Life Cycles


Anti-cyclic Product Sales


Forecast of Required Organizational Capacity from Multiple Life Cycles


Timing of Capacity Increments


Location Planning Strategies


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


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


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


Stage 2: Community

Availability of acceptable sites Local government attitudes Regulations, zoning, taxes, labor supply Tax Incentives Community’s attitude Amenities


Breakeven Location Model


Stage 3: Site

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


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


Locating Pure Service Organizations

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

Facility to Recipient


Short Term Capacity Planning


Bottlenecks in Sequential Operations


Efficiency and Output Increase when Machines are Being Added


Product and Service Flows


Process Flow Map for a Service


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.


Relationship between Capacity and Scheduling

Capacity is oriented toward the acquisition of productive resources

Scheduling related to the timing of the use of resources


Gantt Charts for Capacity Planning and Scheduling (Infeasible)


Gantt Charts for Capacity Planning and Scheduling (Feasible)


Short-Term Capacity Alternatives

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


Increase Resources

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


Improve Resource Use

Overlap or stagger shifts Schedule appointments Inventory output Backlog demand


Modify the Output

Standardize the output Have recipient do part of the work Transform service operations into

inventoriable product operations Cut back on quality


Demand Options

Modify the Demand change the price change the promotion

Do Not Meet Demand


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


The Learning Curve


Background

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


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


Typical Pattern of Learning and Forgetting


Queuing and the Psychology of Waiting


Waiting-Line Analysis

Mechanism to determine several key performance measures of operating system.

Trade-off two costs cost of waiting cost of service


Waiting Line Analysis


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.


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.


Documents

Chapter 5: Capacity and Location Planning1 Chapter 5 Capacity and Location Planning