X Opoly

1235 words 5 pages
Case Analysis
“X-Opoly, Inc.”

1 Summary
The text deals with the topic of developing and producing a board game, called X-Opoly. The game is similar to the famous game ‘’Monopoly’’. It was the idea of two students. Their business has grown rapidly. This year they are expecting that they will sell 50,000 units. Over next 5 years the sales will grow 25 percent annually.
The order of the game has to be differentiated in ordering a new game and ordering a game, which was already produced. For every new game one employee of the art department and the client have to set the design. The required time can vary because it depends on the customer’s specification. The next step is printing. In the printing department the design of the board,
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Year | Expected Demand | 0 | 50000 | 1 | 62500 | 2 | 78125 | 3 | 97656 | 4 | 122070 | 5 | 152588 |
Table [ 1 ]: Expected Demand

6 Question 5: Precedence Graph
In figure 1 and 2 show the basic and new precedence graph. It is presumed that the assembly line is absolutely necessary, which means that all tasks should be in a series.

Figure 1: Precedence Graph
A recommendation for rebalancing the line is to combine stations which in total are not higher than the cycle time of 108 s with the objective to eliminate delays. Besides, it is only possibility to combine a station with one of the following stations because of the assembly line. According to these conditions eight stations are required.
If the disposal of the assembly line could be changed it would be possible to run processes in parallel. The transformation process would be optimized, efficiency would be increased and time saved.

Figur 2: Basic and New Precedence Graph

7 Question 6: Impact on Capacity and Efficiency
With fewer stations the efficiency will increase and the capacity decrease. Consequently the company saves resources.
Efficiency = outputinput
= total task time (NA stations) x cycle time = 6508 x 108
= 75.23 %
By combining stations the efficiency will increase to 75.23 %.

Capacity per year = time available x stations = days x hours per daytotal task time x stations = 200days x 7.5h0.18h x 8 stations
= 66,666 units
Now the capacity amounts to