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EOQ Calculations in Excel

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Last week in Operations Management we used Excel to calculate the Economic Order Quantity and graph Carrying Costs, Ordering Costs, and Total Costs. The Economic Order Quantity or "EOQ" is the order size that "minimizes" Total Costs. Any more or less and you are spending too much on ordering or too much on keeping inventory. For example, in the Excel spreadsheet below, if you had an Annual Demand of 12000 units, Ordering Costs of $10 per order, and Holding costs of $4 per unit per year, the EOQ would be 245 units and Total Costs would be $980.00: We used the following formula in Excel to calculate EOQ: =SQRT((2*B2*B3)/B4) And the following formula to calculate Total Costs at this point: =$B$6/2*$B$4+$B$2/B6*$B$3 To create the graph, we used the following formulas and simply copied them over a range of 100 to 500 units. Ordering Costs: =$B$2/D2*$B$3 Holding Costs: =D2/2*$B$4 Total Costs: =F2+G2 Looking at this chart, we can clearly see that our order size of 245 is ...
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Reliability Calculations in Excel

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In Operations Management today we used Excel to calculate product reliability. Reliability is defined as "the ability of a product, service, part, or system to perform its intended function under a prescribed set of circumstances" (Stevenson, 2009). In order to calulate reliability over a given length of time we need to use the following formula: P(no failure) = e -t/MTBF where: e = 2.7183 t = Length of service before failure MTBF = Mean Time Between Failures One of the cases we did in class involved an auto detailing company that wanted to calculate the reliability of its vacuum cleaners. Excel provides an "EXP" funtion that we can easily apply here. After entering all data for the problem as shown on the spreadsheet below, we type the formula =EXP(-A5/$B$2) in cell B5 and copy down. Next we plot the distribution for t=0 to the maximum life expectancy of 20 years using a line graph. What we end up with looks like a classic case of "ex...
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Excel’s Power Query Editor and Power BI

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Power Query is found within both Excel and Power BI, helping users to transform and clean up their data before they analyze it. With Power Query, you can easily connect to data sources like Excel worksheets, external databases, websites, and even Cloud services. Once connected, you can import data and perform a wide range of data transformations. Data Cleaning: Clean up messy or redundant data. Power Query can help clean up by removing duplicates, correcting errors, and standardizing formats. Data Transformation: Power Query lets you pivot, unpivot, merge, and append tables to get your data ready for analysis. Columns: Add calculated columns or split existing columns. Similar to the way we do it in Excel, Power Query makes it easy to perform various operations. Data Merging: Power Query can merge data from separate tables or files into a single large dataset for analysis. Power Query records all the steps you take to transform your data so if your data changes, you can refresh your qu...
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