Comet Dry Cleaners specializes in same-day dry cleaning. Customers drop off their garments early in the...
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Comet Dry Cleaners specializes in same-day dry cleaning. Customers drop off their garments early in the morning and expect them to be ready for pickup on their way home from work. There is a risk, however, that not all garment will be cleaned on the same day that they are dropped off. If a garment is held overnight, it will cost the company $25 per garment. The manager is contemplating whether they should expand the facility to reduce or total eliminate backlog. To determine if it is cost-effective to expand the facility, the owner wants to determine if the cost of expansion is consistently less than the holding cost per day. In terms of the company's operations, there are two random events. The first is that the company does not know how many garments will be brought in daily for cleaning. The second is that the company does not know how many garments can actually be processed in a given day. Therefore, the owners have collected data and have provided the following probability distribution tables. Daily Garment Demand #Garments 50 60 70 80 90 Probability 8% 27% 32% 23% 10% Daily Processing Capacity #Garments 60 70 80 Probability 27% 41% 32% 1. Based on the Daily Garment Demand Probability Table, calculate the lower and upper bounds of the probability distribution. 2. Based on the Daily Processing Capacity Table, calculate the lower and upper bounds of the probability distribution. 3. Create a simulation for Comet Dry Cleaners for 30 days. Use the probability distribution tables to generate values for Daily Garment Demand and Daily Processing Capacity randomly. a. Assume for the first day of the simulation, that zero garments are in the queue. HINT: You are free to use IF, MIN, or MAX formulas for the remaining formulas that are needed for the simulation. b. c. Be sure to calculate Holding Cost. This cost should be charged on the day the unit was not completed. In other words, if 10 garments were in the queue at the end of the first day, then the Holding Cost for day 1 will be 10*$25, or $250. 4. Create a Line Chart for the number of queued garments at the end of the day. 5. Based on the first run of your simulation (i.e. 30 days), calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" Remember, if the Average Holding Cost/Day is less than $250/day, then the expansion is NOT a good idea. Please reference the $250 reference at the top of the spreadsheet to make the spreadsheet dynamic. 6. Now that you have the first run of the simulation compete, complete the Data Table using the results from the previous part in order to generate 200 replicates. 7. Based on the Data Table, calculate how many instances recommended that the expansion was either a good idea or not. In addition, compute the percentage of times the expansion was a good idea or not. 8. Based on the 200 replicates of the simulation, calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" This statement should reference the percentages found in the previous part. Assume that the manager only requires a majority vote to determine whether the expansion is a good idea or not. In other words, if there are more yes votes than not, the decision to expand is a good one. 9. Create a Pie Chart based on the results found in Part 7. The Pie Chart should show the percentages that were calculated for Yes and No. Add data labels to the chart so that the Category Name, Value, and Legend Key are shown. Comet Dry Cleaners specializes in same-day dry cleaning. Customers drop off their garments early in the morning and expect them to be ready for pickup on their way home from work. There is a risk, however, that not all garment will be cleaned on the same day that they are dropped off. If a garment is held overnight, it will cost the company $25 per garment. The manager is contemplating whether they should expand the facility to reduce or total eliminate backlog. To determine if it is cost-effective to expand the facility, the owner wants to determine if the cost of expansion is consistently less than the holding cost per day. In terms of the company's operations, there are two random events. The first is that the company does not know how many garments will be brought in daily for cleaning. The second is that the company does not know how many garments can actually be processed in a given day. Therefore, the owners have collected data and have provided the following probability distribution tables. Daily Garment Demand #Garments 50 60 70 80 90 Probability 8% 27% 32% 23% 10% Daily Processing Capacity #Garments 60 70 80 Probability 27% 41% 32% 1. Based on the Daily Garment Demand Probability Table, calculate the lower and upper bounds of the probability distribution. 2. Based on the Daily Processing Capacity Table, calculate the lower and upper bounds of the probability distribution. 3. Create a simulation for Comet Dry Cleaners for 30 days. Use the probability distribution tables to generate values for Daily Garment Demand and Daily Processing Capacity randomly. a. Assume for the first day of the simulation, that zero garments are in the queue. HINT: You are free to use IF, MIN, or MAX formulas for the remaining formulas that are needed for the simulation. b. c. Be sure to calculate Holding Cost. This cost should be charged on the day the unit was not completed. In other words, if 10 garments were in the queue at the end of the first day, then the Holding Cost for day 1 will be 10*$25, or $250. 4. Create a Line Chart for the number of queued garments at the end of the day. 5. Based on the first run of your simulation (i.e. 30 days), calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" Remember, if the Average Holding Cost/Day is less than $250/day, then the expansion is NOT a good idea. Please reference the $250 reference at the top of the spreadsheet to make the spreadsheet dynamic. 6. Now that you have the first run of the simulation compete, complete the Data Table using the results from the previous part in order to generate 200 replicates. 7. Based on the Data Table, calculate how many instances recommended that the expansion was either a good idea or not. In addition, compute the percentage of times the expansion was a good idea or not. 8. Based on the 200 replicates of the simulation, calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" This statement should reference the percentages found in the previous part. Assume that the manager only requires a majority vote to determine whether the expansion is a good idea or not. In other words, if there are more yes votes than not, the decision to expand is a good one. 9. Create a Pie Chart based on the results found in Part 7. The Pie Chart should show the percentages that were calculated for Yes and No. Add data labels to the chart so that the Category Name, Value, and Legend Key are shown. Comet Dry Cleaners specializes in same-day dry cleaning. Customers drop off their garments early in the morning and expect them to be ready for pickup on their way home from work. There is a risk, however, that not all garment will be cleaned on the same day that they are dropped off. If a garment is held overnight, it will cost the company $25 per garment. The manager is contemplating whether they should expand the facility to reduce or total eliminate backlog. To determine if it is cost-effective to expand the facility, the owner wants to determine if the cost of expansion is consistently less than the holding cost per day. In terms of the company's operations, there are two random events. The first is that the company does not know how many garments will be brought in daily for cleaning. The second is that the company does not know how many garments can actually be processed in a given day. Therefore, the owners have collected data and have provided the following probability distribution tables. Daily Garment Demand #Garments 50 60 70 80 90 Probability 8% 27% 32% 23% 10% Daily Processing Capacity #Garments 60 70 80 Probability 27% 41% 32% 1. Based on the Daily Garment Demand Probability Table, calculate the lower and upper bounds of the probability distribution. 2. Based on the Daily Processing Capacity Table, calculate the lower and upper bounds of the probability distribution. 3. Create a simulation for Comet Dry Cleaners for 30 days. Use the probability distribution tables to generate values for Daily Garment Demand and Daily Processing Capacity randomly. a. Assume for the first day of the simulation, that zero garments are in the queue. HINT: You are free to use IF, MIN, or MAX formulas for the remaining formulas that are needed for the simulation. b. c. Be sure to calculate Holding Cost. This cost should be charged on the day the unit was not completed. In other words, if 10 garments were in the queue at the end of the first day, then the Holding Cost for day 1 will be 10*$25, or $250. 4. Create a Line Chart for the number of queued garments at the end of the day. 5. Based on the first run of your simulation (i.e. 30 days), calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" Remember, if the Average Holding Cost/Day is less than $250/day, then the expansion is NOT a good idea. Please reference the $250 reference at the top of the spreadsheet to make the spreadsheet dynamic. 6. Now that you have the first run of the simulation compete, complete the Data Table using the results from the previous part in order to generate 200 replicates. 7. Based on the Data Table, calculate how many instances recommended that the expansion was either a good idea or not. In addition, compute the percentage of times the expansion was a good idea or not. 8. Based on the 200 replicates of the simulation, calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" This statement should reference the percentages found in the previous part. Assume that the manager only requires a majority vote to determine whether the expansion is a good idea or not. In other words, if there are more yes votes than not, the decision to expand is a good one. 9. Create a Pie Chart based on the results found in Part 7. The Pie Chart should show the percentages that were calculated for Yes and No. Add data labels to the chart so that the Category Name, Value, and Legend Key are shown. Comet Dry Cleaners specializes in same-day dry cleaning. Customers drop off their garments early in the morning and expect them to be ready for pickup on their way home from work. There is a risk, however, that not all garment will be cleaned on the same day that they are dropped off. If a garment is held overnight, it will cost the company $25 per garment. The manager is contemplating whether they should expand the facility to reduce or total eliminate backlog. To determine if it is cost-effective to expand the facility, the owner wants to determine if the cost of expansion is consistently less than the holding cost per day. In terms of the company's operations, there are two random events. The first is that the company does not know how many garments will be brought in daily for cleaning. The second is that the company does not know how many garments can actually be processed in a given day. Therefore, the owners have collected data and have provided the following probability distribution tables. Daily Garment Demand #Garments 50 60 70 80 90 Probability 8% 27% 32% 23% 10% Daily Processing Capacity #Garments 60 70 80 Probability 27% 41% 32% 1. Based on the Daily Garment Demand Probability Table, calculate the lower and upper bounds of the probability distribution. 2. Based on the Daily Processing Capacity Table, calculate the lower and upper bounds of the probability distribution. 3. Create a simulation for Comet Dry Cleaners for 30 days. Use the probability distribution tables to generate values for Daily Garment Demand and Daily Processing Capacity randomly. a. Assume for the first day of the simulation, that zero garments are in the queue. HINT: You are free to use IF, MIN, or MAX formulas for the remaining formulas that are needed for the simulation. b. c. Be sure to calculate Holding Cost. This cost should be charged on the day the unit was not completed. In other words, if 10 garments were in the queue at the end of the first day, then the Holding Cost for day 1 will be 10*$25, or $250. 4. Create a Line Chart for the number of queued garments at the end of the day. 5. Based on the first run of your simulation (i.e. 30 days), calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" Remember, if the Average Holding Cost/Day is less than $250/day, then the expansion is NOT a good idea. Please reference the $250 reference at the top of the spreadsheet to make the spreadsheet dynamic. 6. Now that you have the first run of the simulation compete, complete the Data Table using the results from the previous part in order to generate 200 replicates. 7. Based on the Data Table, calculate how many instances recommended that the expansion was either a good idea or not. In addition, compute the percentage of times the expansion was a good idea or not. 8. Based on the 200 replicates of the simulation, calculate the various descriptive statistics. a. In addition, write an IF statement that answers the following question. "Is the expansion a good idea?" This statement should reference the percentages found in the previous part. Assume that the manager only requires a majority vote to determine whether the expansion is a good idea or not. In other words, if there are more yes votes than not, the decision to expand is a good one. 9. Create a Pie Chart based on the results found in Part 7. The Pie Chart should show the percentages that were calculated for Yes and No. Add data labels to the chart so that the Category Name, Value, and Legend Key are shown.
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Related Book For
Operations management processes and supply chain
ISBN: 978-0136065760
9th edition
Authors: Lee J Krajewski, Larry P Ritzman, Manoj K Malhotra
Posted Date:
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