Capacity planning

Capacity planning is the process of determining the production capacity needed by an organization to meet changing demands for its products.[1] In the context of capacity planning, design capacity is the maximum amount of work that an organization is capable of completing in a given period. Effective capacity is the maximum amount of work that an organization is capable of completing in a given period due to constraints such as quality problems, delays, material handling, etc.

The phrase is also used in business computing and information technology as a synonym for capacity management. IT capacity planning involves estimating the storage, computer hardware, software and connection infrastructure resources required over some future period of time. A common concern of enterprises is whether the required resources are in place to handle an increase in users or number of interactions.[2] Capacity management is concerned about adding central processing units (CPUs), memory and storage to a physical or virtual server. This has been the traditional and vertical way of scaling up web applications, however IT capacity planning has been developed with the goal of forecasting the requirements for this vertical scaling approach.[3]

A discrepancy between the capacity of an organization and the demands of its customers results in inefficiency, either in under-utilized resources or unfulfilled customers. The goal of capacity planning is to minimize this discrepancy. Demand for an organization's capacity varies based on changes in production output, such as increasing or decreasing the production quantity of an existing product, or producing new products. Better utilization of existing capacity can be accomplished through improvements in overall equipment effectiveness (OEE). Capacity can be increased through introducing new techniques, equipment and materials, increasing the number of workers or machines, increasing the number of shifts, or acquiring additional production facilities.

Capacity is calculated as (number of machines or workers) × (number of shifts) × (utilization) × (efficiency).

Strategies

The broad classes of capacity planning are lead strategy, lag strategy, match strategy, and adjustment strategy.

Advantage of lead strategy: First, it ensures that the organization has adequate capacity to meet all demand, even during periods of high growth. This is especially important when the availability of a product or service is crucial, as in the case of emergency care or hot new product. For many new products, being late to market can mean the difference between success and failure. Another advantage of a lead capacity strategy is that it can be used to preempt competitors who might be planning to expand their own capacity. Being the first in an area to open a large grocery or home improvement store gives a retailer a define edge. Finally many businesses find that overbuilding in anticipation of increased usage is cheaper and less disruptive than constantly making small increases in capacity. Of course, a lead capacity strategy can be very risky, particularly if demand is unpredictable or technology is evolving rapidly.

Capacity

In the context of systems engineering, capacity planning[4] is used during system design and system performance monitoring.

Capacity planning is long-term decision that establishes a firm's overall level of resources. It extends over time horizon long enough to obtain resources. Capacity decisions affect the production lead time, customer responsiveness, operating cost and company ability to compete. Inadequate capacity planning can lead to the loss of the customer and business. Excess capacity can drain the company's resources and prevent investments into more lucrative ventures. The question of when capacity should be increased and by how much are the critical decisions. Failure to make these decisions correctly can be especially damaging to the overall performance when time delays are present in the system.[5]

Capacity – available or required?

From a scheduling perspective it is very easy to determine how much capacity (or time) will be required to manufacture a quantity of parts. Simply multiply the standard cycle time by the number of parts and divide by the part or process OEE %.

If production is scheduled to produce 500 pieces of product A on a machine having a cycle time of 30 seconds and the OEE for the process is 85%, then the time to produce the parts would be calculated as follows:

(500 parts × 30 seconds) / 85% = 17647.1 seconds The OEE index makes it easy to determine whether we have ample capacity to run the required production. In this example 4.2 hours at standard versus 4.9 hours based on the OEE index.

By repeating this process for all the parts that run through a given machine, it is possible to determine the total capacity required to run production.

Capacity available

When considering new work for a piece of equipment or machinery, knowing how much capacity is available to run the work will eventually become part of the overall process. Typically, an annual forecast is used to determine how many hours per year are required. It is also possible that seasonal influences exist within the machine requirements, so a quarterly or even monthly capacity report may be required.

To calculate the total capacity available, the volume is adjusted according to the period being considered. The available capacity is difference between the required capacity and planned operating capacity.

References

  1. "Terms & Definitions - Supply Chain Management". North Carolina State University. 2006. Retrieved 2008-10-26.
  2. Rouse, Margaret (April 2006), Building with modern data center design in mind, retrieved 23 September 2015
  3. Stamford, Conn (May 8, 2014), Gartner Says Major Organizations Will Need to Grow Capacity and Performance Management Skills That Are the Foundation of Web-Scale IT, retrieved 24 September 2015
  4. Gunther, Neil J. (2007). Guerrilla Capacity Planning,. Springer. ISBN 3-540-26138-9.
  5. Spicar, Radim (2014). "System Dynamics Archetypes in Capacity Planning". Procedia Engineering. 69 (C): 1350–1355. doi:10.1016/j.proeng.2014.03.128. Retrieved 29 May 2014.

Bibliography

See also

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