Understanding Finite Capacity Planning in Production


In the dynamic world of manufacturing, organizations strive to optimize their production processes to meet customer demands efficiently. Finite Capacity Planning (FCP) is a valuable technique that helps organizations make informed decisions about production scheduling while considering the limitations and constraints of available resources. In this article, we explore the concept of Finite Capacity Planning, its benefits, and provide examples to illustrate its practical application.

What is Finite Capacity Planning? 

Finite Capacity Planning is a production planning technique that takes into account the finite capacity of resources such as labor, machines, equipment, and facilities when creating production schedules. Unlike traditional planning approaches that focus solely on meeting demand without considering resource limitations, FCP ensures that production plans are feasible and achievable within the available capacity.

The Importance of Finite Capacity Planning: 

By integrating capacity constraints into the planning process, organizations can avoid overloading resources, prevent bottlenecks, and improve overall production efficiency. FCP helps organizations make realistic and optimized production schedules, leading to improved customer satisfaction, reduced lead times, and enhanced resource utilization.

Example Scenario: 

Let’s consider an example to understand how Finite Capacity Planning works. Imagine a furniture manufacturing company that produces custom-made furniture. The company has a limited number of skilled workers, workstations, and machines. A customer places an order for a set of customized dining tables and chairs, and the company needs to determine the production schedule.

Without considering capacity constraints, the company might plan to manufacture all the furniture simultaneously. However, with Finite Capacity Planning, the company analyzes the available resources and their capacities to create a feasible schedule. They consider factors such as the number of workers, the time required for each task, and the available working hours per day.

Based on this analysis, the company may decide to schedule the production in batches, allocating specific time slots to each order to ensure that production stays within the available capacity. This approach helps prevent overloading the workforce or machines and ensures a smoother production flow.

Benefits of Finite Capacity Planning:

  1. Realistic Production Schedules: FCP provides a more accurate representation of production capabilities and enables the creation of realistic schedules that align with resource constraints.

  2. Improved Resource Utilization: By considering capacity limitations, FCP helps organizations optimize resource utilization, reducing idle time and maximizing productivity.

  3. Bottleneck Identification: FCP helps identify potential bottlenecks or resource constraints in advance, allowing organizations to take proactive measures to mitigate their impact.

  4. Enhanced Delivery Performance: By creating feasible schedules, FCP improves on-time delivery performance, reducing lead times and enhancing customer satisfaction.

  5. Effective Decision-Making: FCP provides valuable insights for decision-making, enabling organizations to evaluate different scenarios, prioritize orders, and allocate resources efficiently.


Let’s consider a simplified numerical example to illustrate Finite Capacity Planning (FCP) in action:

Scenario: A bakery receives orders for three different types of cakes: Chocolate, Vanilla, and Strawberry. The bakery has two bakers, two ovens, and a limited number of hours available for production each day. The time required to bake each cake is as follows:

  • Chocolate Cake: 2 hours
  • Vanilla Cake: 1.5 hours
  • Strawberry Cake: 2.5 hours

The bakery needs to determine the production schedule while considering the finite capacity of resources.

Solution: Step 1: Assess Resource Capacity:

  • Bakers: 2 bakers are available.
  • Ovens: 2 ovens are available.
  • Daily Production Hours: Let’s assume the bakery has 8 hours available for production each day.

Step 2: Calculate Resource Availability:

  • Total Baker Hours: 2 bakers * 8 hours = 16 baker hours
  • Total Oven Hours: 2 ovens * 8 hours = 16 oven hours

Step 3: Determine Feasible Production Schedule: To create a feasible production schedule, we need to consider the resource requirements for each cake type and the availability of resources.

  • Chocolate Cake:

    • Resource Requirement: 2 hours per cake
    • Maximum Number of Cakes: 16 baker hours / 2 hours per cake = 8 cakes (Considering baker capacity)
    • Maximum Number of Cakes: 16 oven hours / 2 hours per cake = 8 cakes (Considering oven capacity)
  • Vanilla Cake:

    • Resource Requirement: 1.5 hours per cake
    • Maximum Number of Cakes: 16 baker hours / 1.5 hours per cake ≈ 10.67 cakes (Considering baker capacity)
    • Maximum Number of Cakes: 16 oven hours / 1.5 hours per cake ≈ 10.67 cakes (Considering oven capacity)
  • Strawberry Cake:

    • Resource Requirement: 2.5 hours per cake
    • Maximum Number of Cakes: 16 baker hours / 2.5 hours per cake = 6.4 cakes (Considering baker capacity)
    • Maximum Number of Cakes: 16 oven hours / 2.5 hours per cake = 6.4 cakes (Considering oven capacity)

Step 4: Finalize the Production Schedule: Based on the above calculations, the bakery determines the feasible production schedule while considering resource constraints:

  • Chocolate Cake: Produce 8 cakes (maximum capacity allowed)
  • Vanilla Cake: Produce 10 cakes (rounded down to the nearest whole number)
  • Strawberry Cake: Produce 6 cakes (rounded down to the nearest whole number)


In this example, Finite Capacity Planning helped the bakery determine a feasible production schedule by considering the limited capacity of resources. By allocating the available resources based on their capacity constraints, the bakery ensured efficient production and avoided overloading the bakers and ovens. Implementing FCP enables organizations to optimize their resource utilization, make realistic production plans, and improve overall operational efficiency.