Bottlenecks in a Process
Bottlenecks In A Process
Bottleneck can slow down production and diminish efficiency. According to Li, Chang, & Ni, (2009) “quick and correct identification of the bottleneck locations can lead to an improvement in the operation management of utilizing finite manufacturing resources, increasing the system throughput, and minimizing the total cost of production” (p.1). The operation of preparing dinner will be analysis to find where the process has a bottleneck and how to eliminate or reduce the bottleneck time. Identifying the Bottleneck in the Process
When preparing dinner marinating the meat has proven to be a bottleneck for the process. For example steak can require up to 24 hours to be marinated, holding production for 24 hours is a problem. Choosing a different cut of meat can reduce the time and can require as little as one hour for the meat to marinate. In the production of preparing dinner an hour is still a bottleneck in the process. Considering it can be one hour to marinate the meat, then twenty minutes to cook while side dishes such as rice will only take about thirty minutes to cook the two process can not be run parallel on product will be undercook while the other overcook. Data Collection
Reviewing the data collected over the last four week in preparing dinner the cycle of the process is longer when meat requiring longer marinating time is used in the preparation of dinner. During week two on the second day the preparation of dinner took sixty minutes. The marinating of the meat prevented the process of the side dish to begin because it would cause the meal to be overcooked. The key is to schedule the process capacity carefully to ensure the bottleneck is eliminate or reduce. One step taken to reduce the bottleneck time to make long-term decision regarding the process and have the meat marinates overnight. Avoiding last minute decision increases the efficiently in the process time....
References: Kamauff, J. (2010) Manager’s guide to operations management New York: McGraw Hill/Irwin.
Li, L., Chang, Q., & Ni, J. (2009). Data driven bottleneck detection of manufacturing systems. International Journal of Production Research, 47(18), 5019-5036. doi:10.1080/00207540701881860
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