Cee 5930 – Engineering Management Methods

CEE 5930 – Engineering Management Methods

Fall 2015

Assignment 6

Due: December 1st

ControlTemp, Inc. produces refrigeration units for use in mobile applications (trucks, railcars, etc.) associated with transporting food. One of their principal input materials is copper tubing, which they purchase by total length (meters) from their supplier, Reynolds Tubing Corp. Every Friday, the buyer at ControlTemp places an order with Reynolds to replace the tubing they have used during the current week. Reynolds has what is called a “freedom-of-the-week” delivery provision in their contract, which means that they will deliver the ordered tubing the following week, but it may come in one or more deliveries at any time before the end of the following Friday. Thus, ControlTemp cannot count on using any of that tubing during the following week and they must always have enough tubing on hand to meet their needs for the next week. The tubing ordered now and delivered next week can be used the week after that, etc.

The primary concern in this analysis is that the ControlTemp management wants to determine an effective end-of-week level of inventory for copper tubing. They don’t want more than they need because inventory represents money (value of the material, space required to store it, potential for damage while it’s sitting there, etc.). On the other hand, they don’t want to run short during the next week and have to halt production. Their decision is complicated by the fact that their tubing usage each week is quite variable. The variability derives from two major factors – variability in the average tubing usage rate per hour of production, and variability in the number of production hours achieved each week.

The average tubing usage rate per hour in any given week depends on the mix of types of refrigeration units being produced, potential production change orders, etc. For the analysis in this assignment, we’ll consider 100 meters of tubing to be a unit. Data have been collected over the last two years (104 weeks) on the average tubing usage per production hour, measured in units, and recorded to the nearest tenth (10 meters of tubing). These data are shown in Table 1. (A copy of these data is in the spreadsheet “Assignment 6 Data – Fall 2014.xlsx” on the course Blackboard site.) These data will be the basis for determining a probability distribution for tubing usage, to be used in a spreadsheet Monte Carlo simulation.

The second source of variability in overall tubing consumption in a week is the number of production hours achieved. In a standard week, 70 hours of production are scheduled, but due to tooling changeovers, machine breakdowns, etc., actual production hours achieved are usually less than 70. Figure 1 shows the probability distribution that has been estimated for the number of actual weekly hours of production, denoted h. The probability density function (pdf) for this distribution is:

[pic 1]

Your task in this assignment is to construct a spreadsheet simulation to estimate the overall consumption of copper tubing per week in the ControlTemp plant, as the basis for setting end-of-week minimum inventory. The weekly consumption is a random variable, and you can generate samples from that random variable using a very simple calculation after you have drawn samples from the distributions of average tubing usage per hour, and the number of production hours per week. In your simulation, you may assume that the average usage rate per hour and the number of production hours are independent random variables.