Prof. Howard Weiss’s suggestions may help you teach your OM course this semester.
As the developer of POM for Windows and Excel OM for the Heizer/Render/Munson text, I am naturally biased about the use of software in an OM class. In
my opinion, students in an OM course, as opposed to an Operations Research course, should not be bogged down in the mechanics of computation but rather should understand the model concepts, inputs and outputs. There are four categories of problems that are strong candidates for assigning students to use POM, Excel OM or Excel.
Problems with a large data set There is no reason to ask students to solve PERT/CPM models with a large number of activities by hand. It makes much more sense to have the students enter the data and solve the problem using software, and then stress the concepts such as slack or crashing. In forecasting, students should understand the meaning and use of the trend and the error measures rather than spending time computing the intercept and slope. For control charts, if a student has computed results for 5 samples by hand does it really make sense to ask the student to compute the results by hand for 30 samples rather than using software to perform the computations and instead ask the student about his or her conclusions. There are many more examples of topics that include numerous computations – factor rating, center of gravity, assembly line balancing, ABC analysis, MRP, Lot-sizing and one machine sequencing come to mind. (Also, for models with much data, students should not spend a great deal of time entering data. It is very easy to copy and paste the data tables from MyOMLab to the software).
Iterative Models The discussion of LP, transportation, assignment and 2 machine scheduling, should focus on the formulation of the problems, the inputs, the goals and the interpretation of the results.
Models with multiple methods Some models have more than one approach. It is useful for the students to compare the results of these different methods without having to try every method by hand themselves. Obvious models are time- series analysis, assembly line balancing, aggregate planning and one-machine scheduling.
Models for which the software goes a step further than the text. In a few cases the software presents methods or results that are not part of the textbook. In one machine scheduling, Moore’s method is available to minimize the number of late jobs. Wagner-Whitin is included in the software for lot-sizing. Pairwise comparison is available to determine the layout with the minimum amount of movement.