Bernadette Giene Cain
BU644: Operations Management
Professor Vanessa Washington
June 23, 2015
The expansion of a company’s production equipment can be very costly, and the decision to expand is made off the assessment of the product demand behavior. The expansion must be profitable enough to minimize future decreased demand, and help alleviate production issues in order to increase production growth. Expansion can also be utilized in order to compete within a market, as this could mean that a company is looking to enter into a new product line, or demand for the existing product is so high that the company cannot meet these demands. Often times, there is a system capacity issue where a step in the production process is causing a bottleneck effect. Therefore, this step of the process must be analyzed in order to determine whether its capacity can be increased to meet production or if additional machinery is needed. “Many manufacturers of consumer products are grappling with how much product variety to offer. Manufacturers of industrial products are also seeking to modify their product lines in response to market needs” (Dobson & Candace. 2002. Pg. 293, para. 1).
Al Beck, the President of Beck manufacturing, a producer of steering gears for auto manufacturers, wants the system capacity and to determine if the capacity can be increased. In this case study, an analysis will be done to determine the capacity capability of each stage of the production process, and where a possible bottleneck may occur. Below in chart 1 is the number of machines in the production process, and the capacity capability per minute for each machine. Chart 1:
Beck Manufacturing has five operation work stations in the production process, milling, grinding, boring, drilling and assembly. Each station has a run time where they can produce a piece in an allotted timeframe, and the percentage of pieces that are rejected in each station of the process. The milling station has five machines and can produce two pieces per minute with a three percent reject rate. Grinding has seven machines that produce three pieces per minutes with a five percent reject rate. Boring has three machines that produce one piece per minute with a two percent reject rate. Drilling has six machines that produce two and a half pieces per minute with a seven percent reject rate. The assembly station does not have unlimited capacity, but is capable of meeting the capacity needed to complete production. “In the process of production, if the capacity of one production cell is weak enough, it will become a bottleneck to restrict the full utilization of the other production cells” (Yan & Shi. 2010. Pg. 665, para 3.). Bottleneck in a department is where the input from the previous stage is too large for the second stage of the process. This will limit the amount of product that can continue through the process, therefore decreasing the expected output of stage two. In this process, it will be determined where the bottleneck occurs, and whether or not the capacity can be increased in order to improve the process to run at full production capacity.
There are different methods to help detect bottlenecks in the production line, and one method commonly used is to analyze the queue length in the manufacturing process. The way to do this is to look at which stage has the longest queue or waiting time, and this is the station that is the bottleneck. This method does not prove accurate results and is not capable of analyzing any elements that affect the process of the machines. The following chart shows the production capacity for each station, the amount of products rejected, and the slack in production during a normal 16 hour production shift. Chart 2:
This chart identifies that the Boring station is responsible for the bottleneck in the production process. This station is capable of producing 2880 pieces in a 16 hour period which leaves a...
References: Dobson, G., & Candace, A. Y. (2002). Product offering, pricing, and make-to-stock/make-to-order decisions with shared capacity.Production and Operations Management, 11(3), 293-312. Retrieved from http://search.proquest.com/docview/228711710?accountid=32521
Mary-Paz, A. P. (2007). THE TIMING OF CAPACITY EXPANSION INVESTMENTS IN OLIGOPOLY UNDER DEMAND UNCERTAINTY.Investment Management & Financial Innovations, 4(1), 40-55,108. Retrieved from http://search.proquest.com/docview/216682891?accountid=32521
Vonderembse, M.A. & White, G.P. (2013). Operations Management . San Diego, CA: Bridgepoint Education, Inc.
Yan, H., An, Y., & Shi, W. (2010). A new bottleneck detecting approach to productivity improvement of knowledgeable manufacturing system. Journal of Intelligent Manufacturing, 21(6), 665-680. doi:http://dx.doi.org/10.1007/s10845-009-0244-3
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