A local manufacturer of Toys produces several toys. Among the most popular is Elsa Doll. Suppose that there are currently 100 Elsa Doll in inventory and that there are customer orders that have been committed and must be filled. Suppose that a production lot size of 150 Elsa Dolls. The weekly forecasts for the eight weeks are 176, 172, 50, 130, 40, 120, 132, and 135 respectively. The customer orders for weeks 1, 2, 3 through 8 are the 88, 86, 25, 65,20, 51, 0, 0 respectively. Using the standard principles of Master Production Schedule (MPS) along with Available-To-Promise (ATP) for the Elsa Dolls, what is the Available to promise (ATP) level in week 2 Select one: О а. 150 O b. 79 О с. 39 Od. 0

A local manufacturer of Toys produces several toys. Among the most popular is Elsa Doll. Suppose that there are currently 100 Elsa Doll in inventory and that there are customer orders that have been committed and must be filled. Suppose that a production lot size of 150 Elsa Dolls. The weekly forecasts for the eight weeks are 176, 172, 50, 130, 40, 120, 132, and 135 respectively. The customer orders for weeks 1, 2, 3 through 8 are the 88, 86, 25, 65,20, 51, 0, 0 respectively. Using the standard principles of Master Production Schedule (MPS) along with Available-To-Promise (ATP) for the Elsa Dolls, what is the Available to promise (ATP) level in week 2 Select one: О а. 150 O b. 79 О с. 39 Od. 0

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter10: Introduction To Simulation Modeling

Section10.4: Simulation With Built-in Excel Tools

Problem 15P

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In Problem 12 of the previous section, suppose that the demand for cars is normally distributed with mean 100 and standard deviation 15. Use @RISK to determine the best order quantityin this case, the one with the largest mean profit. Using the statistics and/or graphs from @RISK, discuss whether this order quantity would be considered best by the car dealer. (The point is that a decision maker can use more than just mean profit in making a decision.)
The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. Can you guess the results of a sensitivity analysis on the initial inventory in the Pigskin model? See if your guess is correct by using SolverTable and allowing the initial inventory to vary from 0 to 10,000 in increments of 1000. Keep track of the values in the decision variable cells and the objective cell.
The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. As indicated by the algebraic formulation of the Pigskin model, there is no real need to calculate inventory on hand after production and constrain it to be greater than or equal to demand. An alternative is to calculate ending inventory directly and constrain it to be nonnegative. Modify the current spreadsheet model to do this. (Delete rows 16 and 17, and calculate ending inventory appropriately. Then add an explicit non-negativity constraint on ending inventory.)
The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. Modify the Pigskin model so that there are eight months in the planning horizon. You can make up reasonable values for any extra required data. Dont forget to modify range names. Then modify the model again so that there are only four months in the planning horizon. Do either of these modifications change the optima] production quantity in month 1?
A local manufacturer of Toys produces several toys. Among the most popular is Elsa Doll. Suppose that there are currently 100 Elsa Doll in inventory and that there are customer orders that have been committed and must be filled. Suppose that a production lot size of 150 Elsa Dolls. The weekly forecasts for the eight weeks are 176, 172, 50, 130, 40, 120, 132, and 135 respectively. The customer orders for weeks 1, 2, 3 through 8 are the 88, 86, 25, 65,20,51,0, o respectively. Using the standard principles of Master Production Schedule (MPS) along with Available-To-Promise (ATP) for the Elsa Dolls, what is the Available to promise (ATP) level in week 5 question Select one: a. 162 b. 150 c. None is correct d. 79 e. 2.39
A local manufacturer of Toys produces several toys. Among the most popular is Elsa Doll. Suppose that there are currently 100 Elsa Doll in inventory and that there are customer orders that have been committed and must be filled. Suppose that a production lot size of 150 Elsa Dolls. The weekly forecasts for the eight weeks are 176, 172, 50, 130, 40, 120, 132, and 135 respectively. The customer orders for weeks 1, 2, 3 through 8 are the 88, 86, 25, 65,20,51,0, 0 respectively. Using the standard principles of Master Production Schedule (MPS) along with Available-To-Promise (ATP) for the Elsa Dolls, what is the Available to promise (ATP) level in week 6 Select one: a. 162 b. 150 c. None is correct d. 79 e. 39
A local manufacturer of Toys produces several toys. Among the most popular is Elsa Doll. Suppose that there are currently 100 Elsa Doll in inventory and that there are customer orders that have been committed and must be filled. Suppose that a production lot size of 150 Elsa Dolls. The weekly forecasts for the eight weeks are 176, 172, 50, 130, 40, 120, 132, and 135 respectively. The customer orders for weeks 1, 2, 3 through 8 are the 88, 86, 25, 65,20,51,0,0 respectively. Using the standard principles of Master Production Schedule (MPS) along with Available-To-Promise (ATP) for the Elsa Dolls, what is the Available to promise (ATP) level in week 5 Select one: O a. None is correct O b. 162 O c. 39 O d. 79 O e. 150
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