Question: You have been hired to evaluate a proposal presented to a small regional trucking company by an engine manufacturer. The proposal would extend the life

You have been hired to evaluate a proposal presented to a small regional trucking company by an engine manufacturer. The proposal would extend the life of the 20-truck fleet by 5 years, reducing their operating costs while improving fuel efficiency.

Given the uncertainty in the trucking industry over the next few years due to Amazon's massive growth, the company's owner has been advised to consider any short-term fix which exceeds a 9.00% internal rate of return.

The average number of miles drive per truck - 120,000 per year

Create a discounted cash flow model using the following data to determine if the company should move forward with the proposal.
Below are the costs and estimated savings. Cost per new Engine - $15,000
Cost to install each engine - $3,500

It is estimated the new engines will improve the trucks' fuel efficiency (Miles Per Gallon) by 10% per mile, from 10 MPG to 11 MPG over their entire life. Further, it is estimated the company will save $5,000 per truck in annual maintenance for year one, but that savings will decline by 20% per year for the 5-year estimated life of these engines. As of today, the national average for diesel fuel is $5.10 per gallon and is expected to be very volatile - i.e., an area one might consider stressing.

The current truck fleet is owned by the company with no debt. The trucks have been fully depreciated for tax purposes. The company's CPA suggests the best approach would be to expense the cost of these engines in the year they are installed rather than depreciate them - treating them as a repair and maintenance expense. As a consultant, your job is not to provide tax advice.

The company enjoys an effective tax rate of 25%. Further, they have sufficient income to benefit from the expense relating to installation costs.

Create a discounted cash flow model to analyze this situation. Make any assumptions, clearly labeling them. 

Summarize your results when submitting your model.

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