Chapter 9 Capacity Planning & Facility Location
Operations Management: Chapter 9 - Capacity Planning and Facility Location
Learning Objectives
Define capacity planning.
Explain the steps involved in capacity planning and location analysis.
Explain the usefulness of decision trees in decision making.
Identify key factors in location analysis.
Describe the decision-support tools used in location analysis.
Learning Objective 1: Define Capacity Planning
Capacity Definition
Capacity: The maximum output rate of a facility.
Capacity Planning: The process of establishing the output rate that can be achieved at a facility.
Capacity must be purchased in "chunks".
Strategic Issues: Concerns about how much capital to invest in additional facilities and equipment, and when to do so.
Tactical Issues: Involves managing workforce and inventory levels, and the day-to-day use of equipment.
Measuring Capacity
No single best method exists for measuring capacity.
Simplified output measures (e.g., kegs per day) are more comprehensible.
For multiple products, input measures (e.g., labor hours) are preferable.
Table 9.1: Examples of Different Capacity Measures
Type of Business | Input Measures of Capacity | Output Measures of Capacity |
|---|---|---|
Car manufacturer | Labor hours | Cars per shift |
Hospital | Available beds per month | Number of patients per month |
Pizza parlor | Worker hours per day | Number of pizzas per day |
Ice-cream manufacturer | Operational hours per day | Gallons of ice cream per day |
Retail store | Floor space in square feet | Revenues per day |
Two Types of Capacity Information
Amount of Available Capacity: Understanding how much capacity the facility has.
Effectiveness of Capacity Use: Understanding how effectively the available capacity is utilized.
Measuring Available Capacity
Design Capacity:
Definition: Maximum output rate under ideal conditions.
Example: A bakery can produce 30 pies per day during peak holiday times.
Effective Capacity:
Definition: Maximum output rate under normal (realistic) conditions; usually lower than design capacity.
Example: A bakery typically produces 20 pies per day.
Measuring Effectiveness of Capacity Use
Capacity Utilization: Measures the percentage of available capacity that is being utilized.
It reflects effectiveness and can use either effective or design capacity in the denominator.
Example: Computing Capacity Utilization
A bakery's design capacity is 30 pies per day.
Effective capacity is 20 pies per day, with current production at 28 pies per day.
Current utilization slightly below design capacity and significantly above effective capacity implies that the bakery can only maintain this output temporarily.
Capacity Considerations
The best operating level is where the output results in the lowest average unit cost.
Economies of Scale:
Definition: The cost per unit decreases as output volume increases due to spreading fixed costs over multiple units and enabling bulk purchasing.
Diseconomies of Scale:
Definition: The cost per unit rises as output increases due to factors like congestion and scheduling complexity.
Best Operating Level and Size
Two alternatives when expanding capacity:
Purchase one large facility, requiring substantial initial investment.
Incrementally add capacity in smaller chunks as necessary.
Other Capacity Considerations
Focused Factories: Specialize in limited objectives (e.g., small factories like The Limited).
Plant within a Plant (PWP): Segmenting larger operations into smaller units with specific goals.
Subcontractor Networks: Outsourcing non-core items to enhance capacity for main competencies, a growing trend.
Learning Objective 2: Steps Involved in Capacity Planning and Location Analysis
Making Capacity Planning Decisions
The three-step procedure:
Identify capacity requirements.
Develop capacity alternatives.
Evaluate capacity alternatives.
1. Identifying Capacity Requirements
Forecasting Capacity:
Long-term capacity needs based on anticipated future demand, utilizing qualitative forecast models such as executive opinion and the Delphi method.
Futures linked to strategic implications (e.g., competitor capacity and potential industry overcapacity).
Capacity Cushions: Planning for flexibility by maintaining added capacity.
2. Developing Capacity Alternatives
Types of alternatives include:
Doing nothing.
Expanding capacity in a large initial investment.
Expanding small now with options to add later.
3. Evaluating Capacity Alternatives
Decision support aids, such as decision trees, are used to evaluate options.
Managers must consider multiple inputs and use their judgment in decision-making.
Learning Objective 3: Usefulness of Decision Trees in Decision Making
Decision Trees
Decision trees consist of:
Decision Points: Where decisions are made, represented by squares (nodes).
Decision Alternatives: Branches or arrows leading from decision points.
Chance Events: Events that may affect decisions, represented by branches leading from circular chance nodes.
Outcomes: Each possible alternative listed.
Decision Tree Diagrams
Developed by:
Drawing from left to right.
Squares for decision points, circles for chance events.
Noting the probability of each chance next to respective nodes (total probabilities = 100%).
Writing outcomes in the right margin.
Example: Using Decision Trees
A restaurant owner must decide between a large immediate expansion versus a smaller expansion with future expansion options.
Evaluating the Decision Tree
Utilizes Expected Value (EV) analysis:
EV is calculated as the weighted average of chance events (Probability of occurrence × Chance event).
In an example, expanding to a large facility had an EV of $225,000, while a small expansion had an EV of $164,000.
Decision made to choose the large expansion although there is risk involved (30% chance it might be detrimental).
Learning Objective 4: Key Factors in Location Analysis
Location Analysis
Three primary factors in real estate: Location, Location, Location.
Facility location is the process of determining the best geographic site for a service or production facility, involving long-term commitments and significant financial investments.
Factors Affecting Location Decisions
Proximity to Supply Sources: Minimizes transportation costs of perishable or bulky raw materials.
Proximity to Customers: Importance of being situated in high population areas or near Just-In-Time (JIT) partners.
Proximity to Labor: Considering local wage rates, labor attitudes (union presence), and availability of special skills.
More Location Factors
Community Considerations: Local community attitudes towards facilities (e.g., prisons, power plants).
Site Considerations: Local zoning regulations, taxes, and access to utilities.
Quality of Life Issues: Climate, cultural attractions, commuting times.
Other considerations: Future expansion options, local competition, and transport access/congestion.
Globalization: Should the Firm Go Global?
Advantages:
Access to foreign markets, bypassing trade barriers, and cheaper labor.
Close proximity to suppliers and manufacturers.
Disadvantages:
Increased political risks, loss of control over proprietary technologies, inadequate local infrastructure, high inflation.
Other Issues:
Language barriers, legal variances, and differences in business cultures.
Learning Objective 5: Decision-Support Tools in Location Analysis
Making Location Decisions: Process
A three-step approach:
Identify dominant location factors.
Develop location alternatives.
Evaluate location alternatives.
Location Decisions: Procedures and Tools
Useful procedures and tools for evaluating alternatives:
Factor Rating Method: Evaluates multiple location alternatives based on selected factors.
Load-Distance Model: Based on distance evaluation of alternatives.
Center of Gravity Approach: Identifies locations minimizing load-distance by identifying the center of gravity of the target area.
Break-even Analysis: Calculates the volume of goods to be sold to cover financial costs.
Transportation Method: Evaluates potential location sites' costs against existing facility networks.
Examples and Techniques
Factor Rating:
Evaluates locations based on weighted scores derived from various factors (see Table 9.4 for details).
Load-Distance Model:
Calculates distances between potential sites and service locations, adjusted by the number of loads.
Example evaluation shows Springfield as the optimal warehouse location based on lower load-distance scores compared to Mansfield.
Center of Gravity Approach:
Calculates a central location considering existing customers and loads.
Break-Even Analysis:
A framework for computing fixed and variable costs for each potential location, determining options based on cost efficiency.
Essential equations:
Total cost: ext{Total Cost} = F + cQ
Total revenue: ext{Total Revenue} = pQ
Break-Even Quantity: Q = rac{F}{p - c}
(Where Q is the break-even quantity, p is the price per unit, c is the variable cost per unit, and F is fixed costs).
Transportation Method: Solves specific issues related to location optimization within existing networks.
Capacity Planning and Facility Location within Operations Management
Decisions related to capacity and location are influenced by demand forecasts (reference Chapter 8).
Capacity decisions are also linked to operational strategies incorporating structural elements.
Other affected operational decisions include job design, labor skills, technology choices, and automation (reference Chapters 2, 3, and 11).
Capacity Planning and Facility Location Across the Organization
Capacity planning and location analysis directly influence operation management and various departments:
Finance contributes to capacity decision-making.
Marketing influences capacity importance regarding production and location concerning customers.
Chapter Highlights
Capacity planning determines facility output limits, while location analysis focuses on optimal site selection. These two decisions are typically interconnected.
In both capacity planning and location analysis, managers should follow a structured three-step process: assessing needs, developing alternatives, and evaluating alternatives.
Decision trees serve as a modeling tool to navigate the sequential independent decisions necessary for evaluating capacity planning alternatives.
Key factors in location analysis include customer proximity, transportation decisions, labor sources, community attitudes, and raw material supply locations. Distinctions exist between the priorities of service and manufacturing sectors, as well as for profit and non-profit organizations.
Several analytical tools exist for effective location analysis, including the factor rating method, load-distance model, center of gravity approach, break-even analysis, and transportation method, providing comprehensive insights to facilitate decision-making.