analyzing the differences between design capacity and effective capacity, as well as predicting challenges that may arise when using each method.

 

analyzing the differences between design capacity and effective capacity, as well as predicting challenges that may arise when using each method.

Analyze two or three differences between design capacity and effective capacity, then predict one or two challenges that you may encounter when using each method. Provide specific examples using additional sources, if necessary, to support your rationale.
This course requires the use of Strayer Writing Standards (SWS).
Be sure to respond to at least one of your classmates’ posts.
Classmate post: Toya
Hello Classmates and Professor,
According to Chapter 9 of the textbook, design capacity is the maximum output rate that can be achieved by a facility under ideal conditions. Design capacity can be sustained only for a relatively short period of time. A company achieves this output rate by using many temporary measures, such as overtime, overstaffing, maximum use of equipment, and subcontracting. Effective capacity is the maximum output rate that can be sustained under normal conditions. These conditions include realistic work schedules and breaks, regular staff levels, scheduled machine maintenance, and none of the temporary measures that are used to achieve design capacity. Note that effective capacity is usually lower than design capacity (1 Reid & Sanders pg. 295). Though these measurements of capacity may seem the same, they have many differences. Design capacity only considers the physical capabilities of the system or process, such as equipment capacity and design specifications typically. Effective capacity takes into account real-world factors that can affect productivity, such as machine breakdowns, scheduled maintenance, employee availability, and quality issues. Understanding both capacity measures, there are certainly challenges that will arise when utilizing the two methods.
One challenge with design capacity is the risk of overestimating the system’s capabilities. For example, a bakery might be designed to produce a certain number of cupcakes per hour, but in reality, achieving this output consistently may be disturbed by many factors such as the ovens may break down or there may be an ingredient shortage.
Another challenge is that design capacity may not be easily adjustable to suit changes in demand or changes in operating conditions. Not having flexibility can lead to inefficiencies and missed sales or opportunities. If the bakery only can produce to sell from the store, they may not be able to take on any side gigs, catering events, or special orders.
Determining the effective capacity requires accurate data collection and analysis of various factors influencing productivity. Challenges may come up with accurately measuring downtime, identifying stalls in production, and measuring the quality of impact of factors such as employee skills or equipment reliability. For example, in a bakery, as mentioned before effective capacity may take into consideration whether the head baker can bake under stress, how fast can the baker bake, and whether all the baking equipment is up to par for production purposes.
Adjusting effective capacity involves balancing resources and constraints to achieve the highest sustainable output. This can be difficult and may require continuous monitoring and adjustments to ensure that the system operates at its maximum potential without exceeding limitations.
Sources:
1. R. Dan Reid and Nada R Sanders. ND. Operations Management. An Integrated Approach. Seventh Edition. https://read.wiley.com/books/9781119497066/page/15/section/c09-sec-0003

 

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