Applichem (A)

/Applichem (A)
Applichem (A) 2019-07-06T07:27:56+00:00

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The Problem

There is a case study pertaining to a hypothetical plant namely, Gary Plant. There are obvious problems that specifically associated with the same plant. The growth of the company is inefficient and the have certain problems within their operations that needed to be identified. The company has lost its technical efficiency and curiosity. There are numerous manufacturing plants which are producing different volumes.

Analysis and Findings

 Firstly, it is likely to analyse about the operational cost among different plants. There are a total of six different plants which have been discussed in the same outcome (Boardman et al., 2017). Total Cost includes different operational cost along with packaging and load cost as well. The total cost computation is as follows

Mexico95.01
Canada97.35
Venezuela116.34
Frankfurt76.69
Gary102.93
Sunchem153.8
 642.12

There are six different plants which are associated with the company. The first one is the plant in Mexico. From the computation of the cost, it is clearly found that the total cost incurred in this particular plant is $95.01 (per thousand). It is also found that the proportion of Mexican plant compared with the total cost incurred by them is 15%, as demonstrated in the graph mentioned above. Moving to the second one. The second one is the plant in Canada. From the computation of the cost, it is clearly found that the total cost incurred in this particular plant is $97.35 (per thousand). It is also found that the proportion of Canadian plant compared with the total cost incurred by them is 15% also, as demonstrated in the graph mentioned above, but it is marginally higher than the Mexican plant. The 3rdone is the plant of Venezuela. From the computation of the cost, it is clearly found that the total cost incurred in this particular plant is $116.34 (per thousand). It is also found that the proportion of Venezuelan plant compared with the total cost incurred by them is 18%, as demonstrated in the graph mentioned above, which is way higher than the couple of plants mentioned earlier (Mishan, 2015). The next one is the plant of Frankfurt. From the computation of the cost, it is clearly found that the total cost incurred in this particular plant is $76.69 (per thousand). It is also found that the proportion of Frankfurt plant compared with the total cost incurred by them is 12%, as demonstrated in the graph mentioned above, which is the lowest. Moving towards the Gary’s Plant which has higher cost as well which is amounted to $ 102.93 (per thousand), which has a proportion of 16% which is again higher. The plant of Sunchem is the most expensive one with a total cost of $ 153.8 (Per Thousand) with a proportion of 24% in total. Apart from the cost, there is yet another important thing that sounds highly efficient in the same context which is the output. It is essential for a plant to produce the products in accordance with their requirement or design capacity. The table and chart representing the production, capacity and the variance are as follows

Production CapacityVariance
Mexico17.2224.8
Canada2.63.71.1
Venezuela4.14.50.4
Frankfurt38479
Gary1418.54.5
Sunchem451

From the aforementioned table and chart, it is clearly found that the variation is found in almost every plant in particular. It is showing that each of the plant is producing lesser amount of product than its actual capacity. For Mexico, the bar graph is showing that the capacity is 22, while the actual production is 17.2, showing that the level of variation is 4.8. In this way, the company can influence the management of Mexican plant to increase their capacity accordingly, as it is a regular and important practice for them (Raman, 2015). Moving to the second plant, which is of Canada. For Canada, the bar graph is showing that the capacity is 3.7, while the actual production is 2.6, showing that the level of variation is 1.1. In this way, the company can influence the management of Canadian plant to increase their capacity accordingly, as it is a regular and important practice for them.The next capacity is for Venezuela. For this, the bar graph is showing that the capacity is 4.5, while the actual production is 4.1, showing that the level of variation is 0.4. In this way, the company can influence the management of Venezuelan plant to increase their capacity accordingly, as it is a regular and important practice for them. Now, moving to the next plant which has the highest variation in the capacity and actual production, which is of Frankfurt. For Frankfurt, the bar graph is showing that the capacity is 47, while the actual production is 38, showing that the level of variation is 9. In this way, the company can influence the management of Frankfurt plant to increase their capacity accordingly, as it is a regular and important practice for them. Moving on, there is a plant located in Gary. For Gary, the bar graph is showing that the capacity is 18.5, while the actual production is 14, showing that the level of variation is 4.5. In this way, the company can influence the management of Gary plant to increase their capacity accordingly, as it is a regular and important practice for them. Finally, it is plant of Sunchem that has the highest cost factor. For this plant, the bar graph is showing that the capacity is 5, while the actual production is 4, showing that the level of variation is 1. In this way, the company can influence the management of the same plant to increase their capacity accordingly, as it is a regular and important practice for them. However, it has the lowest variation.

Conclusion

 Based on the same analysis, it is recommended to the company to increase the factor of monitoring for the cost, and the items which have been created and producing by the company in order to maintain the capacity and design capability of the company.

References

Boardman, A. E., Greenberg, D. H., Vining, A. R., & Weimer, D. L. (2017). Cost-benefit analysis: concepts and practice. Cambridge University Press.

Mishan, E. J. (2015). Elements of Cost-Benefit Analysis (Routledge Revivals). Routledge.

Raman, A. (2015). A Cost to Benefit Analysis of a Next Generation Electric Power Distribution System. Arizona State University.