Capacity Planning Study Notes
Operations Management: Processes and Supply Chains - Chapter 6: Capacity Planning
Learning Goals
6.1 Define long-term capacity and its relationship with economies and diseconomies of scale.
6.2 Understand the main differences between the expansionist and wait-and-see capacity timing and sizing strategies.
6.3 Identify a systematic four-step approach for determining long-term capacity requirements and associated cash flows.
6.4 Describe how the common tools for capacity planning, such as waiting-line models, simulation, and decision trees, assist in capacity decisions.
What is Capacity?
Capacity: The maximum rate of output of a process or a system.
What is Capacity Management?
Capacity Management: The process of planning for the utilization of capacity to ensure a balance between production efficiency and market demand.
Key Components:
Capacity Planning (Long-Term): Determines the long-term capability of an organization to meet sustained demand.
Economies and Diseconomies of Scale: Evaluates cost implications of scaling up operations.
Capacity Timing and Sizing Strategies: Strategies to decide when and how much capacity to add.
Systematic Approach to Capacity Decisions: A structured process for making decisions related to capacity.
Constraint Management (Short-Term): Focuses on managing bottlenecks in processes to optimize performance.
Theory of Constraints: A methodology for identifying the most important limiting factor (constraint) in a process.
Identification and Management of Bottlenecks: A key aspect of short-term capacity management.
Product Mix Decisions Using Bottlenecks: Consideration of how constraints affect the choice of products.
Managing Constraints in a Line Process: Ensuring efficiency in linear production workflows.
Measures of Capacity and Utilization
Output Measures of Capacity: Best utilized when applied to individual processes or in firms that provide a small number of standardized products and services.
Input Measures of Capacity: Generally used for low-volume, flexible processes.
Utilization: The degree to which equipment, space, or workforce is being used, defined as the ratio of average output rate to maximum capacity:
ext{Utilization} = rac{ ext{Average Output Rate}}{ ext{Maximum Capacity}} imes 100 ext{ ( ext{expressed as a percentage})}
Economies and Diseconomies of Scale
Economies of Scale: The average unit cost of a service or good can be reduced by increasing its output rate.
Reasons for economies of scale include:
Spreading Fixed Costs: As production increases, fixed costs are distributed over more units.
Reducing Construction Costs: Larger facilities might be built more economically.
Cutting Costs of Purchased Materials: Bulk purchasing can reduce material costs.
Finding Process Advantages: Larger operations may lead to more efficient processes.
Diseconomies of Scale: The average cost per unit increases as the facility’s size increases due to factors such as:
Complexity: Larger organizations may face coordination challenges.
Loss of Focus: As an organization grows, management focus may become diluted.
Inefficiencies: Greater size can lead to inefficiencies that increase costs.
Capacity Timing and Sizing Strategies
Key Considerations:
Sizing Capacity Cushions: The amount of reserve capacity a process uses to handle sudden increases in demand or temporary losses of production capacity.
Capacity Cushion Definition: Measures the amount by which average utilization falls below 100 percent.
Formula:
ext{Capacity Cushion} = 100 ext{ (Percent)} - ext{Average Utilization Rate ( ext{in percentage})}
Industry Variability: Capital intensive industries prefer cushions under 10%, while less capital-intensive industries, like hotels, might operate with cushions of 30-40%.
Timing and Sizing Expansion: Deciding the appropriate timing for expanding capacity relative to demand.
Linking Capacity with Other Decisions: Ensuring that capacity decisions are integrated with other strategic operational decisions.
A Systematic Approach to Long-Term Capacity Decisions
Estimate Future Capacity Requirements: Predict capacity needs based on demand forecasts.
Identify Gaps: Evaluate discrepancies between projected capacity requirements and current available capacity.
Develop Alternative Plans: Consider various strategies to bridge capacity gaps.
Evaluate Each Alternative: Analyze alternatives both qualitatively and quantitatively to reach a final decision.
Capacity Requirements
Capacity Requirement Definition: The capacity a process should have to meet future demand while considering desired capacity cushion.
Using Output Measures: Calculating capacity based on output expectations.
Using Input Measures: Calculating capacity based on expected resource inputs.
Step 1 - Estimate Capacity Requirements
For a service or product processed at one operation with a one-year timeframe, the formula for capacity requirement, M, is:
M = rac{D imes p}{N imes (1-C)}
Where:
D = Demand forecast for the year (units produced or customers served).
p = Processing time (in hours per customer served or unit produced).
N = Total operating hours per year.
C = Desired capacity cushion (expressed as a percent).
Setup Times: Additional time required to change from one service or product to another when multiple products are produced.
With Q being the number of units in each lot and s being the setup time in hours per lot:
Consideration of setup time will affect total capacity requirements.
Example 1
Scenario: A copy center prepares bound reports for two clients.
Client X Annual Demand: 2,000 copies; Processing time: 0.5 hours/copy; Lot Size: 20 copies; Setup Time: 0.25 hours.
Client Y Annual Demand: 6,000 copies; Processing time: 0.7 hours/copy; Lot Size: 30 copies; Setup Time: 0.40 hours.
Operational Information: Operates 250 days a year with one 8-hour shift; Capacity cushion set at 15%.
Determine Machines Needed: I.e., determine conditions resulting in the requirement for four machines based on demand and processing times.
Step 2 - Identify Gaps
Capacity Gap Definition: The positive or negative difference between projected capacity requirements ( ext{M}) and current capacity.
Steps 3 and 4 – Develop and Evaluate Alternatives
Base Case Assumption: Do nothing and face the consequences of not meeting demand.
Qualitative Concerns: Uncertainties regarding demand, reactions from competitors, technology changes, and cost uncertainties.
Quantitative Concerns: Cash flows and other numerical factors affecting capacity decisions.
Example 2
Scenario: Grandmother’s Chicken Restaurant anticipates serving 80,000 meals this year, but can handle 105,000 meals in their dining room.
Forecasted Demand: Starts at 90,000 meals next year, increasing by 10,000 meals each year following.
Expansion Plan: A proposed expansion would bring capacity to 130,000 meals with an initial investment of $200,000.
Cash Flow Calculation:
Year 0: Cash Flow = -$200,000 (initial investment).
Year 1: Incremental Cash Flow = (90,000 - 80,000) × $2 = $20,000.
Year 2: Demand = 100,000; Cash Flow = (100,000 - 80,000) × $2 = $40,000.
Year 3: Demand = 110,000; Cash Flow = (110,000 - 80,000) × $2 = $60,000.
Year 4: Demand = 120,000; Cash Flow = (120,000 - 80,000) × $2 = $80,000.
Year 5: Demand = 130,000; Cash Flow = (130,000 - 80,000) × $2 = $100,000.
Taking Time Value of Money into Account: Recommended to apply NPV or IRR methods, with an example NPV at a 10% discount rate yielding $13,051.76.
Tools for Capacity Planning
Waiting-line Models: Effective in high customer-contact environments.
Simulation: Utilized for complex scenarios that are difficult to model with waiting-line analysis.
Decision Trees: Helpful in scenarios involving uncertainty and sequential decision making.
Decision Trees
Illustration: A decision tree can outline various pathways for capacity expansion, factoring in potential future demands and investment decisions.