Beck Manufacturing produces steering gears for automobile manufacturers, and Al Beck, the company’s president, wants to determine the capacity of the company’s machine centers and the whole system. Al Beck is concerned about ways of increasing the capacity of the system. He wants to know where he should focus the firm’s efforts to increase capacity and how it can be increased without purchasing new machines. This paper aims to provide answers to Al Beck’s questions regarding the capacity of the system and ways of expanding it.
The Capacity of Machine Centers and the System
The case study provides all the data necessary for calculating the production capacity, including the number of machines, the run time per piece, the reject rate, and the number of shifts per day. According to Vonderembse and White (2013), to calculate the capacity of a machining center, it is necessary to convert its operating time to minutes. Since each machine center operates two 8-hour shifts per day, the total operating time is 16 hours. To convert this time to minutes, one should multiply 16 hours by 60 minutes and get 960 minutes.
Next, it is possible to calculate the capacity of each machine center. According to the case study, milling machines process one piece for 2 minutes, which means that one milling machine can process 480 pieces per day. This number is calculated by dividing 960 minutes by 2 minutes. The milling machine center has 5 machines, so the daily output of this center equals 2,400 pieces. However, milling machines have a 3% reject rate, which means that 3% of pieces are excluded from the total output because of inappropriate quality. To calculate the number of rejected pieces, one should multiply 2,400 by 0.03, which equals 72 pieces. Thus, the capacity of the milling center is 2,400 minus 72, that is, 2,328 pieces.
The capacity of the other three machine centers is calculated similarly. In the grinding center, the run time per piece is 3 minutes, meaning that one grinding machine can produce 320 pieces per day. There are 7 grinding machines, so the daily output should be 2,240 pieces. However, with the reject rate of 5%, which is 112 pieces, the grinding center can produce only 2,128 pieces per day. A boring machine processes one piece for one minute, so it can produce 960 pieces a day. Since there are 3 boring machines, they produce 2,880 pieces daily. The reject rate at the boring center is 2%, which is 58 pieces, so the capacity of the center is 2,822 pieces per day. Finally, the run time per piece in the drilling center is 2.5 minutes, so one drilling machine can produce 384 pieces a day. There are 6 drilling machines, which means that the total output of the drilling center is 2,304 pieces. The reject rate is 7% or 162 pieces, so the capacity of the drilling center is 2,142 pieces.
When the capacities of all machine centers are known, the capacity of the system can be determined. According to Vonderembse and White (2013), the capacity of the system is defined by its bottleneck, that is, the slowest department. In Beck Manufacturing, the bottleneck is the grinding center because it produces the lowest number of pieces. So, the capacity of the system is equal to the capacity of the grinding center, which is 2,128 pieces per day.
The Focus of the Company’s Efforts to Expand Capacity
As was identified, the bottleneck of the system in Beck Manufacturing is the grinding center. Therefore, the company should focus its efforts on the grinding center to increase the system’s capacity. However, it is important to note that the drilling center is at risk of becoming a new bottleneck of the system in case the company increases the capacity of the grinding center. The capacity of the drilling center is 2,142 pieces, and the capacity of the grinding center is 2,128 pieces per day. Consequently, the company can get the extra capacity of only 14 pieces per day without causing the drilling operation to become the bottleneck.
Capacity Expansion without Purchasing New Equipment
Purchasing new equipment is, perhaps, the most evident way of increasing the capacity of the system, but not the most cost-effective one. According to Vonderembse and White (2013), an alternative to purchasing new machines is operating existing machines more effectively. If management decides not to buy new equipment, they should focus their efforts on introducing technological changes, such as reducing the operating time (Kolinska & Domanski, 2017). For Beck Manufacturing, the longest run time per piece is in the grinding and drilling centers. Reducing the operating time of grinding and drilling machines would increase the system’s capacity.
The company may also focus on improving the quality of its products. As Vonderembse and White (2013) point out, when products are rejected because of poor quality, it leads to wasting production capacity. The case study data show that grinding and drilling machines have the highest reject rate, which is 5% and 7%, respectively. Nallusamy et al. (2018) argue that manufacturers can decrease reject rates by analyzing the causes of rejections and implementing the necessary improvements. If Beck Manufacturing could reduce reject rates in grinding and drilling centers to 3%, it would gain an extra capacity of 44 pieces per day. Finally, increasing the number of shifts is a viable option for expanding capacity if the company decides not to invest in new equipment (Weston et al., 2017). Maintenance shifts are important for keeping machines functioning, so Beck Manufacturing should not replace them with work shifts. Yet, the company can add two Saturday shifts; it will increase the system’s capacity by 2,128 pieces per week, but it will also increase labor costs.
References
Kolinska, J., & Domanski, R. (2017). The analysis of production lines bottlenecks identification and ways of management. Business Logistics in Modern Management, 109-123.
Nallusamy, S., Nivedha, R., Subash, E., Venkadesh, V., Vignesh S., & Vinoth kumar, P. (2018). Minimization of rejection rate using Lean Six Sigma tool in medium scale manufacturing industry. International Journal of Mechanical Engineering and Technology, 9(1), 1184-1194.
Vonderembse, M., & White, G. (2013). Operations Management. Bridgepoint Education, Inc.
Weston, J., Escalona, P., Angulo, A., & Stegmaier, R. (2017). Strategic capacity expansion of a multi-item process with technology mixture under demand uncertainty: An aggregate robust MILP approach. In Proceedings of the 6th international conference on operations research and enterprise systems (ICORES 2017) (pp. 181-191). SCITEPRESS.