former NFL licensed jersey producer‚ many key decisions must be made to reduce inventory costs in periods of low demand while maximizing profits in periods of high demand for player specific jerseys. Using the newsvendor model to determine the optimal order quantity and leftover inventory‚ we will present a possible approach to inventory planning with uncertain demand. Uncertain Demand: Within the replica jersey industry‚ seasonality plays a vital part in keeping sufficient inventory to cover customer
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Otto’s Auto Parts Statistical Report Hansen Consulting proudly presents the following statistical information for Otto’s Auto parts. Statistics is a branch of mathematics that makes it possible for you to gain an edge over your competitors by providing a method for collection of data‚ and a way to summarize and quantify it to represent real world observations from which predictions can be made. Statistics also includes stochastic modeling‚ which is a powerful tool that incorporates random variables
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Labour‚ overhead‚ meat‚ buns and condiments cost $1 per burger. Demand is normally distributed with a mean of 400 kg per day and a standard deviation of 50 kg per day. What daily order quantity is optimal? 2. A manager is going to purchase new processing equipment and must decide on the number of spare parts to order with the new equipment. The spares cost $200 each‚ and any unused spares will have an expected salvage value of $50 each. The probability of usage of parts can be described by the following
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facing Sport Obermeyer‚ which has been addressed in Appendices A and B. Appendix A shows how much should be produced in Hong Kong given the assumption that there is no limit to the capacity; however‚ we have been asked to comment only on the initial order quantity‚ and not the reorder quantity. In keeping with this constraint‚ and using the forecasts given by all the committee members‚ we believe that Appendix B is an accurate representation of the amount of each style that should be produced in Hong
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first part of our analysis involved deriving an order policy from the forecasts provided in the sample problem. We solved this problem using simplifying assumptions and then relaxing some of those assumptions. Our initial assumption was that there was no minimum order quantity. We decided that risk would be minimized by producing the smallest allowable amount during the first production run due to the lack of information. Thus‚ we calibrated our order quantity formulas to sum to 10‚000 units. We wanted
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Develop an inventory plan to help ZBC. We will use EOQ Formula in order to derive some data for estimates. Annual demand = D = 439 Cost of Bicycle at whole sale (C) = 0.60*170 = $102 Carrying cost (H) = 12% of cost = 102 *.12 = 12.24 Ordering cost (S) = $65 per order Lead time = 4 weeks Re order point = ROP = daily demand x lead time (days) = 439/365 * 28 = 33.67 EOQ Formula Order quantity Q = Sqrt (2DS / H) = Sqrt ( 2 * 439 * 65 / 102 *.12
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demand is constant at 32‚000 books per ear. The cost of placing an order to replenish stock is $10 and the annual cost of holding is $4 per book. Stock is received five working days after an order has been placed. No backordering is allowed. Assume 300 working days a year. a. What is Dot Com’s optimal order quantity (EOQ)? b. What is the optimal number of order per year? c. What is the optimal interval (in working days) between orders? d. What is the demand during the lead time? 2. Leaky Pipe
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Sport Obermeyer case (Venugopal Vinjamuri and Kailash Kothari) In order to determine the quantity of each product that should be purchased at the outset so as to fill half of the total forecasted volume (10‚000 units)‚ we need to calculate the purchase price per product (something that isn’t provided in the case) and also the salvage price per product. Let’s start with the cost information of the Rococo Parka. The cost to produce one piece in Hong Kong is $60.08 while the cost in China is $51.92
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Annual rate 22.0% 2. Ordering Cost 2 hours at $28.00 $56.00 Other expenses (2‚375/125) 19.00 Cost per order $75.00 3. Set-up Cost 8 Hours at $50.00 $400 per set-up 4. & 5. a. Order from Supplier - EOQ model Ch = IC = 0.22 ($18.00) = $3.96 [pic]units Number of orders = D/Q = 9.19/year Cycle time = 250(Q) / D = 250(348.16) / 3200 = 27.2 days Reorder Point: P(Stockout) = 1 / 9.19 = 0.1088 r
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COMM 225: POM REVIEW PROBLEMS – TUTORIAL QUESTIONS Week Q1 (Ref: Q. 9-23‚ p413 of (Operation management: creating value along the Supply Chain)): The following table provides the information necessary to construct a project network and project crash data: Activity a b c d e f g h Predecessor a a b b c d‚ e Normal Times (Weeks) 16 14 8 5 4 6 10 15 Crash Times (Weeks) 8 9 6 4 2 4 7 10 Normal Costs Crash Costs $2000 $1000 $500 $600 $1500 $800 $3000 $5000 $4400 $1800 $700 $1300 $3000 $1600 $4500
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