OPS 571 Week 2 Indivadual Assignment Learning Curve Concept
OPS 571 Week 2 Indivadual Assignment Learning Curve Concept
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Date Created: 11/16/15
Learning Curve Concept 1 Running Head: Learning Curve Concept Learning Curve Concept: Application in the Context of Pizza Store Layout Simulation Writer’s Name Course Name, Semester No, Class Level Supervisor Name Learning Curve Concept 2 Introduction The basic premise behind the learning curve concept is the improvement in performance of process due to repetitive nature of tasks operated by individual or organization again and again. This theory is based on three fundamental assumptions which is as follows: 1. The time required for completion of task decreases as it is repeated number of times 2. The percentage of improvement decreases with corresponding increase in volume of units, 3. The rate of improvement is predictable over the certain time There has been increment in the process of performance in such a way that units of productions gets doubled in reduced span of time after the certain period of implementation. This is also defined as the rate of learning where constant percentage of reduction in time is taken care of. The slope of the curve is calculated by the difference between the rate of learning and numerical value of one hundred. If the timing between the doubling of units are decreased by 10 percent, then it will be connotated as 90 percent learning curve. Discussion of the learning curve concepts to test the alternative to the process The table for process performance data for the metric identified in the Pizza Store Layout Simulation is as follows: Learning Curve Concept 3 Table 1 S. No. Week No of No of Avg. Wait Avg. Profit s Custom Custom Time(Min) Queu ($) ers for ers for e Group Group Lengt of 2 of 4 h 1 0 70 106 11.67 3.21 1,054 2 1-2 71 105 6.46 2.56 1,120 3 3-4 71 105 5.53 2.67 1,380 4 5-6 100 140 4.93 2.88 1,985 5 7-8 92 147 3.45 2.68 2,081 Learning curve can be developed by many curve fitting methods like arithmetic tables, logarithmic scale or other methods. Learning Curve Concept 4 The plot for each week denoted by S. No. on Xaxis and Avg Wait Time (Min) on Yaxis from above Table. The results of Pizza simulation process is shown above in tabular format. There is definite improvement in average waiting time for customer from first week till the eigth week of pizza simulation process of Mario’s Pizza. It has decerased from 11.67 minutes to 3.45 minuts at the end of process after applying optimization strategy and removing the bottleneck in process. If we can do the analysis of curve, we see that average waiting time has decreased to almost half from 11.67 to 5.53 minutes at the end of fourth week. We have to apply approimation to fit the curve. The approximate slope of curve for eight week can be calculated by (11.673.45)/(80) = 1.0272 i.e. avaerage waiting time is decreasing by 1.0272/11.67 = 0.088 ~0.09. We can say that the rate of learning is 9% which means it is 91% learning curve. It can be estimated on the learning rate how the improvement in waiting time happens. Similar interpretation can be applied to the profit gained by the improvement in process. Learning Curve Concept 5 The plot for each week denoted by S. No. on Xaxis and Profit ($) on Yaxis from above Table. There is significant improvement in profit for customer from first week till the eigth week of pizza simulation process of Mario’s Pizza. It has improved from 1,054 dollars to 2,081 dollars at the end of process after changing diiferent parameters of optimization strategy and handling the bottleneck in process. If we do the analysis of curve, we see that profit has increased to almost double from 1,054 to 2,081 dollars at the end of eigth week. The approximate slope of curve for eight week can be calculated by (2,081 1,054)/( 80) = 128.375 i.e. profit is increasing by 128.375 $ each week. Thepercentage increase in profit is 128.375 /2,081 = 0.061 ~0.06 per week. We can say that the rate of learning is 6% which means it is 94% learning curve.This can be applied for estimating the weekly improvement for further improvement. Cumulative average or cum avaerage theory can be applied to optimize and estimate the overall cost of restaurant staffs, rents, Pizza cost and ovens operating charges. Learning Curve Concept 6 (Source: http://fast.faa.gov/pricing/9830c18.htm ) Here, Y calculates the mean value of cost which has been beared by utilization of X quantities of different units. In cum avareage theory, average costs reperesnts the cumulative units of X operating units. In other words, The total cost of producing X units will be calculated by X multiplied by the cum average cost. In pizza simulation scenario, the average cost of no of pizzas consumed by customer can be calculated for the eight week production using the average costs for running the restaurant each day. It will give the rough estimate for optimizing the price of Pizza to maximize the profit. We have seen how service facilities and their utilization affected the waiting lines at Mario’s. Waiting lines form when customers arrive at a faster rate than the service system can provide. Maintaining waiting lines, is not about shorter or longer queues, but about maintaining balance between the demand for service and the capacity of the system to provide the service. Conclusion As a manager concern should be about operating characteristics such as the line length, the number of customers in the system, the waiting time spent in the line, the total time spent in the system, and the service facility utilization. An effective way of analyzing a waiting line problem is to relate these characteristics to their costs. Learning Curve Concept 7 A long queue at favorite restaurant is enough to annoy even the most patient customer. Several such experiences may result in loss of a customer, which translates into loss in sales. Therefore, learning curve concept is important in estaimating cost of the Wait Staff, Kitchen Staff, Manual Ovens, Plax Ovens, and size of Tables for 4 and Tables for 2 to maiximize the profit of Mario’s Pizza. Learning Curve Concept 8 References Bibliography Baloff, Nicholas (1971). "Extensions of the Learning Curve Some Empirical Results." Operations Research Quarterly, 22.44. Website Federal Aviation Administration. (n.d.). Retrieved August 18, 2009, from The Learning Curve: http://fast.faa.gov/pricing/9830c18.htm
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