Introduction

In this paper, we will focus on the case study, which discusses about the plant capacity and Beck Manufacturing. In addition, after reading the case study it becomes evident that we need to help Beck’s Manufacturing, president in making the best decision possible in regards to determining his facilities capacity. Therefore, we need to note that Beck’s Manufacturing is a major producer of steering gears in the auto industry. Nevertheless, we also need to know how the manufacturing process is being done, thus allowing us to answer and identify our case study questions. Thus, first, we must calculate both the capacity of the system, along with the capacity of each machine. Second, identify any alternative measures where, Beck can expand his capacity initiatives, in order to gain a positive capacity gain, without causing another bottleneck incident in the operations side.

Third, establishing a strategy where Mr. Beck does not have to buy more equipment in order to increase his capacity. Furthermore, let us answer these fundamental questions, while helping Mr. Beck feel confident in his new strategies to incorporate to Beck Manufacturing. In accordance, to our text, in order to be able to identify each machines center, along with calculating the system using the detailed data provided, we must connect other key factors before coming to any conclusions. Beck’s Manufacturing includes assembling, drilling, milling, grinding and boring.

Thus, we also need to know that each type of machine requires each finished product to adhere to one operation. Another, important key is knowing that each facility has a two 8-hour shifts per day, but this doesn’t include a maintenance shift which is postponed to in the third shift. “Capacity is a measure of an organization’s ability to provide customers with the demanded services or goods in the amount requested and in a timely manner. Capacity is also the maximum rate of production” (Vonderembse, & White, pp 8.1, 2013). The data table that we need is as follows:

The Milling Capacity

Moving forward, using the data above, now can allow us to calculate the capacity of each machine and system. Thus, to start let us begin by identifying the operating time into minutes. Since, we know that Beck runs a two 8-hour shift; it gives us a total of 16 hours daily. Therefore, there are 60 minutes in an hour, if we have a total of 16 hours daily; this gives us a total of 960 minutes. The Milling’s operation can produce in two minutes run time per piece, thus one machine can manufacture 480 units per machine.

Since, there are 5 machines total, a total of 2400 units can be manufactured combined. In the Milling’s case, there is a 3% reject rate, meaning that it might not be approved or it will be rejected in regards to following standards. This will drop the total to 2328, because the reject rate of 3% equals 72. “It is shown that demand and capacity decisions do indeed impact on each other – sometimes in ways that are not initially obvious. Results provide useful thought-starters for service managers striving to improve their operations” (Klassen, & Rohleder, 2002).

The Grinding Capacity

The next source includes, the Grinding Capacity, which its run time is 3 minutes per piece, giving us a total of 960 minutes, therefore per machine it can produce 320 units. In addition, let us keep in mind that there are a total of 7 machines, thus giving us a total of 2,240 units. In addition, the Grinding has a 5% reject rate, thus the total units are 112. Now, if we can subtract 2,240 units from all the 7 machines with the 112 units, then it will provide us with a new total of 2,128 units.

The Boring Capacity

The Boring Capacity’s run time is 1 minute per piece, thus providing us with production of 960 units per machine with a total of 960 minutes. Now, let us note that there are 3 machines, thus giving us a total of 2,880 units. In addition, the Boring represents a 25-reject rate, giving us 58 in units. Nevertheless, if we subtract 2,880 units produced by all three machines from 58 units, then we will get a new total of 2,822 units.

The Drilling Capacity

The following includes, the Drilling Capacity, which has a run time of 2.5 minutes per piece. Therefore, this produces a total of 384 units per machine, giving us a total of 960 minutes. In addition, providing that there are a total of 6 machines, thus giving us a total of 2,304 units. Moving forward, giving that we know that Drilling has a 75-reject rate, and thus providing us with a total of 162 units. Nevertheless, if we subtract the total amount of units produced from all 6 machines of 2,304 units with the 162 units, this will provide us with a new total of 2,142 units.

The System Capacity

In order to find the capacity system, we are able to take the lowest number in units, of course after the reject rate, which for this case is produced by the grinding with 2,128 units. Therefore, because we are unable to produce more units due to reaching the capacity mark, or for no more product to be allowed through in the completed cycle. Thus, the capacity system turns out to be 2,128 units. “Capacity utilization and machine scheduling also reflect tactical operating decisions taken by local managers to maximize short-run performance” (Anderson, 2001).

However, if Mr. Beck would like to expand the capacity of his system, then he should look into buying machines for grinding, because this in essence balances the other machines output. In addition, if Mr. Beck can somehow figure out how to increase a unit by 30 seconds faster on one of his machines, then Mr. Beck could raise the volume of units produced. Therefore, in order to avoid becoming another bottleneck incident from occurring, then Mr. Beck needs to embrace the extra capacity by limiting the amount in units produced with the lowest center, which for this case would be drilling giving us a total of 2,142 units. In conjunction, if Mr.

Beck wants to be able to expand his capacity without having to purchase any new equipment, then Mr. Beck needs to be able to reduce the percentage in rejection in production adhered to by the organization. Thus, when this occurs, the amount of produced units will increase, because the reject rate has gone down. “Managers should evaluate the competitive response of a capacity increase, especially with firms that will likely become new competitors, in order to gain an accurate picture of the likely post-increase scenario” (Bloodgood, & Katz, 2004).

In conclusion, after reading the case study it becomes evident that we need to help Beck’s Manufacturing, president in making the best decision possible in regards to determining his facilities capacity. Thus, first, we must calculate both the capacity of the system, along with the capacity of each machine. Second, identify any alternative measures where, Beck can expand his capacity initiatives, in order to gain a positive capacity gain, without causing another bottleneck incident in the operations side.

Third, establishing a strategy where Mr. Beck does not have to buy more equipment in order to increase his capacity. Therefore, because all the produced lowest output is in accordance to the capacity of the system from all the machines, because each unit has to pass through all machines in order to be completed within their process. It becomes evident that Mr. Beck should expand its capacity or simply buy more machines in order to expand his capacity.

Reference:

Anderson, S. W. (2001). Direct and indirect effects of product mix characteristics on capacity management decisions and operating performance. International Journal of Flexible Manufacturing Systems, 13(3), 241. Retrieved from http://search.proquest.com/docview/201484655?accountid=32521 Bloodgood, J. M., & Katz, J. P. (2004). MANUFACTURING CAPACITY, MARKET SHARE, AND COMPETITIVENESS. Competitiveness Review, 14(1), 60-71. Retrieved from http://search.proquest.com/docview/213035530?accountid=32521 Klassen, K. J., & Rohleder, T. R. (2002). Demand and capacity management decisions in services: How they impact on one another. International Journal of Operations & Production Management, 22(5), 527. Retrieved from http://search.proquest.com/docview/232328850?accountid=32521 Vonderembse, M.A. & White, G.P. (2013). Operations Management . San Diego, CA: Bridgepoint Education, Inc.