Merton Truck Co

2033 WordsApr 11, 20109 Pages
Case Analysis: Merton Truck Company Linear programming techniques can be used to not only determine the best production mix, but also to provide clues and data suggesting ways to improve profits. In 1988, Merton Truck Company was searching for ways to increase profits and ultimately its poor financial performance. Options being considered included changing their product mix by either removing or adding a product line, or renting capacity. In the following pages, the product mix and capacity options considered by Merton are evaluated, other factors and alternatives are discussed, and final recommendations are provided. Product Mix Based on the financials in 1988, Merton’s president suspected that discontinuing their Model 101 would…show more content…
The same result was obtained when the analysis was done in Excel Solver (see attached Exhibit 3, Model 101 & 102 Solver Results). The binding constraints seen in Exhibit 4 are no longer the Model Assemblies as seen with earlier combinations, but are now the Engine Assembly and Metal Stamping departments. The optimal product mix for Merton given their current product mix and constraints has been determined, but Merton is also considering the addition of a new Model 103. The values for contribution margin (CM) are given as well as the portion of departmental capacity required to produce 103. Based on the capacity information, it was determined that Model 103 would require 0.8 hours of Engine Assembly, 1.5 hours of Metal Stamping, and 1 hour of Model 101 Assembly per truck. The constraints and objective function were modified with these new values and run in Excel’s Solver, which determined that Model 103 should not be produced (Exhibit 5). Exhibit 6 provides a sensitivity report indicating a reduced cost of -$350, meaning that the CM of Model 103 would need to increase by $350 before it would make sense for Merton to begin producing Model 103. Capacity Options Given the capacity limitations seen thus far, it is a fair conclusion that increasing capacity may present an opportunity. In the optimal solution, there are limitations in

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