A manufacturing firm has set up a project for developing a new machine for one of its production lines. The most likely estimated cost of the project itself is $1 million, but the most optimistic estimate is $900,000 while the pessimists predict a project cost of $1,200,000. The real problem is that even if the project costs are within those limits, if the project itself plus its implementation cost exceed 1,425,000, the project will not meet the firms NPV hurdle. There are four cost categories involved in adding the prospective new machine to the production line: (1) engineering labor cost, (2) non-engineering labor cost, (3) assorted materials cost, and (4) production line down-time cost.

The engineering labor requirement has been estimated to be 600 hours, plus or minus 15% at a cost of $80 per hour. The non-engineering labor requirement is estimated to be 1500 hrs., but could be as low as 1200 hrs. or as high as 2200 hrs. at a cost of $35 per hour. Assorted material may run as high as $155,000 or as low as $100,000 but is most likely to be about $135,000. The best guess of time lost on the production line is 110 hours, possibly as low as 105 hours and as high as 120 hours. The line contributes about $500 per hour to the firms profit and overhead. What is the probability that the new machine project will meet the firms NPV hurdle? Use Crystal Ball simulation to answer the question.

You need to use triangular distribution as the assumption for each cost, and add all costs in the spreadsheet. Note that for the downtime costs what varies is the number of downtime hours, but by multiplying that number for the line per hour contribution profit and overhead you can calculate the downtime cost. Once you have the total cost probability distribution, you can estimate the probability of that cost being above or below the required cost limit to meet the NPV requirement.