EMBA 2011-12
MERTON TRUCK COMPANY
CASE SOLUTION
HARSHID DESAI AMRUT MODY SCHOOL OF MANAGEMEMNT ROLL NO. 03
Merton Truck Company
Calculating contribution for each truck, Contribution for model 101 = selling price (direct mat. + direct labour + variable o/h) = 39000 (24000 + 4000 + 8000) = Rs. 3000/Contribution for model 102 = selling price (direct mat. + direct labour + variable o/h) = 38000 (20000 + 4500 + 8500) = Rs. 5000/-
Decisions variables: x1 = number of model 101 trucks produced, x2 = number of model 102 trucks produced, The algebraic formulation is: Max. 3000.x1 + 5000.x2, Constrains, 1.x1 + 2.x2 2.x1 + 2.x2 2.x1 + ..+ 3.x2 x1, x2 0.
4000, 6000, 5000, 4500,
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Q.1 (A) Find best products mix for
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constrain 1 which is engine assembly machine hour, we can push it in the opposite direction of origin till it passes through intersection point of (line 2 and line 4) 2nd and 4th constrain i.e. stamping and model 102 assembly. To derive that point of intersection we need to calculate as below. Finding the value of x1 and x2 using equation >> 2.(x1) + 2.(x2) = 6000 >> So we get,
X2 = 1500, and x1 = 1500
3.(x2) = 4500
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With the further increase in unit of capacity of engine assembly machine hour (from 4500 to 4501) there is no change in the contribution. So no. of units can be added calculated below, Substituting the value of x1 and x2 in the below equation, = 1.(x1) + 2.(x2) = 1.(1500) + 2.(1500) = 4500 Therefore, unit can be added is (4500 4000 = 500).
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Q.2 Sol. Company should adopt this alternative as we seen in Q1 (b) and Q (d). increase in one unit of capacity inceases contribution by Rs. 2000/- and company should rent 500 machine hours till which contribution increases after that there is no change in contribution of increased unit in capacity. So it is obvious that company should be willing to pay Rs. 2000/- for a rented machine hour.
Q.3 Sol. Decisions variables: x1 = number of model 101 trucks produced, x2 = number of model 102 trucks produced, x3 = number of model 103 trucks produced. The algebraic formulation is: Max. 3000.x1 + 5000.x2 + 2000.x3, Constrains, 1.x1 + 2.x2 + 0.8.x3 2.x1 + 2.x2 + 1.5.x3 2.x1
The diagram below shows the feasible region of the intersection of two lines. This means that any point within the feasible region satisfies all constraints that we established before graphing. Feasible regions make it easier for us to determine the maximum profit and now we know all the possible combinations it’s important to know what point on the graph is going to be the most profitable.
x ≤ 1900 and y ≤ 1400 (Constraints for monthly production of Model S and Model LX)
11. If 8,000 units are produced, what is the total amount of manufacturing overhead cost incurred to support this level of production? What is the total amount expressed on a per unit basis?
Q.1) Compute the following quantities for the current production process as well as for Mike’s and Ike’s plans, assuming the plans are implemented as described in the case.
Model Description The model takes much of the busywork out of the case, enabling students to spend more time on interpretation and evaluation. Like most case models, the student and instructor versions differ only in regard to the input data. The instructor’s version contains the complete base case inputs, while these inputs are zeroed out in the student version of the model. The model for this case takes the input data (cost pool values and allocation rates) and allocates overhead costs from the three overhead departments to the three patient services departments using all four allocation methods. Additionally, the model calculates the profitability of each patient services department under each allocation method. The model’s (instructor’s version) Input Data and Key Output sections are as follows:
Since the amount of juice to sell is in units of plastic bottles e.g., two bottles of orange juice, all decision variables must be an integer.
In this particular case, Randy will need to assign the correct numbers to the correct category. For the purposes of this case study, assume T will equal 1 to make the equation represent one year of employment in one of the ice cream shops. For following variables, Nn will equal 50 as there will be 50 applicants total selected to be hired, rxy will represent .30 in one equation representing the interview and job performance and in the other equation, it will represent .50 which will represent the work sample predictor and job performance, SDy will be chosen to represent .20, Ẑs will be .80 because it will be the predictor score of the selected applicants, Na will represent 100, as that is the total number of applicants that submitted applications, and Cy will represent the cost per applicant in the interview and job performance in one equation as 100 and it will represent 150 in the other equation for work sample and job
was 7,920 units. The company has provided the following data concerning the formulas to be used in its
Each week there are 300 pounds of material 1; 400 pounds of material 2; and 200 hours of labor. The output of product A should not be more than one-half of the total number of units produced. Moreover, there is a standing order of 10 units of product C each week.
A linear formula idea will be used and the decision variables will be labeled as follow:
Write a constraint to ensure that if machine 4 is used, machine 1 will not be used.
These two bottlenecks constrained the whole process. Alex and his colleagues were happy to identify two "Hebie"s, NCX-10 and Heat Treatment Department, which bottlenecked a flow sufficient to meet demand and make money. So the only thing to do was to find more capacity. To increase the capacity of the plant was to increase the capacity of only the bottlenecks. To increase the capacity of bottlenecks did not mean to install new machine, but to find the hidden capacity. With the help of Jonah, Alex found the NCX-10 had 1-hour idle time, as the union contract stipulated that there must be a half-hour break after every four hours work. The hours lost in the breaks of NCX-10 were enormously expensive because the throughput for the entire plant had been lowered by the bottleneck. The problem of the second "Hebie", heat treat, was that they didn 't make the bottleneck work on the parts contributed to throughput and many products were unable to be shipped without the parts in pile for treatment. What was more, they only did most inspections prior to final assembly but never inspected the parts before bottleneck. It easily let defects go through bottleneck and lost time in the bottleneck could not be recovered. The cost of one hour lost in these two bottlenecks is the cost of an hour lost in the system, which is computed as the total expense of the system divided by
The objective functions and constraints mentioned in step two and three are translated into excel columns as follows Objective Function Formula
The shadow prices for each of the constraints show how much the objective function would get better or worse by if the right hand side was increased by one unit. For instance if the total number of trucks needed for month 1 increased from 10 to 11, the cost would get better by $2485 or decrease by $2485 (since the shadow price is the negative of the dual price). The positive dual values for the long-term trucks show that using the long-term trucks instead of the short-term trucks actually