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Unformatted text preview: Recitation #11 and Homework #9: Logistic Regression OR&IE 3120, Spring 2009 The problems in this lab should be handed in as homework #9 and are due on Thursday, April 16, at 4pm. 1 Case Background In this lab, we continue the analysis of the casting problem. Recall that, as part of a longer manufacturing process, a factory needs to cast a large number of rectangular metallic blocks. The blocks are manufactured using a mold, consisting of the main cavity, a cup through which the molten metal is poured, and two risers for cooling. The size and shape of the pouring cup and risers affect how quickly the metal can be poured into the mold, how quickly it cools, and whether it sets correctly. Objective: The factory needs to cast batches of 100 blocks of size 4 . 5 × 4 . 5 × 7 inches. The current casting approach is fairly conservative – it takes a long time to pour, but the blocks always set correctly and are usable. Your goal is to achieve a significant reduction in average casting time while still ensuring that most blocks are usable. Variables characterizing the mold: The following nine mold-variables can be varied: Riser Height, Riser Diameter, Riser 1 Position, Riser 2 Position, Gate Diameter, Cup Height, Sprue Height, Sprue Diameter Bottom, Sprue Diameter Top . Data: To obtain data on how various mold-variable settings affect pouring and cooling, a batch of 100 is poured with random variations 1 in the nine mold-variables, centered about their baseline values. The data are available in castdata2.csv , which is identical to the file castdata.csv used in a previous lab except that there is an 11th column with the variable Feasible . Feasible is 1 if the casting is feasible and 0 otherwise. As before, the first nine columns are the mold-variables listed above and the 10th column is BatchTime ....
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- Spring '09