# Car Washing Case Solution

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SIMULATION REFLECTIVE REPORT

BALANCING PROCESS CAPACITY

PHAM THI NGOC SEN

MBA

FRIDAY, 12 Feb, 2016

Dr. Hilal Hurriyet

1. What strategy did you use in Challenge 1? Please discuss and refer to your results. How Challenge 2 is different to Challenge 1? Please discuss by referring to your results.

According to simulation game, as an operations manager, I have to make decision on how to allocate money either to vacuum, machine wash, or hand dry stations in order to maximize efficiency and improve overall profitability.

With the challenge one, because the number demand of carwash is constant and performance is fixed at each station, I have to try to gain capacity is balanced across the three stations as mentioned above. First of all, when looking at current capacity of each station, I realize the hand dry and windows station have the highest total time per unit with only 24 cars per hour, so I recognize that it is the bottleneck of the process. Therefore, it is necessary to invest more money to upgrade capacity into this station than others. The problem is how much money for each station is optimal, initially, with budget is 3 million dollar, I decide to put 1 million dollar into each station, the average number of car each station process is 37.5, after calculating, I find out that \$1 million the capacity can upgrade 1.5 cars per hour, \$500 upgrading more 7.5 cars per hour and \$1.5 million upgrading more 13.5 cars per hour for three stations, respectively. Thus, capacity is balanced at 37.5 cars per hour. As a consequence, the process reach the maximum profit at \$825 and the total number of carwash is 300 cars per day. And the detail result showed as below:

[pic 1][pic 2]

However, in challenge 2, it is not undoubtedly that the strategy applied in challenge 1 is not suitable in challenge 2 due to variable performance at the station and inherent demand variability. This has lead to the difference in process performance. There are three dimensions that the variability affected. Specifically, this has lead to longer in cycle time and lead time, decreased profit and changeable bottleneck.[pic 3]

First of all, after examining approximately 30 times different combinations of investment strategy, I recognize that there is a fluctuation in capacity at each station and capacity is not balanced across the three stations, this means that bottleneck move around over three stations. Therefore, existence the same profit when even choosing different allocate money options and the optimal solution for this process to reach the profit is \$690 and the total number of carwash is 273 cars below:

Simultaneously, variability leads to longer cycle time and lead time, considering cycle time in challenge 1, because the capacity is balanced across three stations so cycle time of the process is equal cycle time of each station. Conversely, in challenge 2, there is variability so the cycle time of the process is the station which possesses the longest cycle time, this will also impact on throughput time from predictable 19 min to unpredictable 23 min. It can also be explained by many reasons which are generated by variability such as breakdowns and repairs, operator experience or material variations.[pic 4]

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