"Economic order quanity" Essays and Research Papers

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    Analysis Northco case

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    inventory. High Forecast error fluctuating demand ‚ schhols changing fabric & design on short notice Lack of systems to track w/h inventory in real time Basic products also available at department stores only 25% confirmed customer orders by April High Leftover Inventory High product variety 12000 SKU with over 5000 SKU for school Uniform School Uniform subject to fashion trends Michael’s high inventory level issues cannot be tackled by just implementing an information

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    Ludo Case

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    1. What is the optimal order quantity that Michelle Peach should use for Dado and for Wedo? What are the resulting expected profits? The optimal order quantities that Michelle Peach should use for Dado and for Wedo are 1‚270 and 730. The gross margins and expected profits would be: The annual net income has considered that all the other costs as constant. The advertising revenues are the same (fixed amount‚ not per unit ad amount). 2. Michelle finds out that Bobby Peru‚ a local recycler

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    COMM 225: MIDTERM REVIEW QUESTIONS TOPIC: PROJECT MANAGEMENT Q 1.1: Kozar International‚ Inc. begun marketing a new instant-developing film project. The estimates of R&D activity time (weeks) for Kozar’s project are given in the table below. The project has two paths: AC-E-F and A-B-D-F. Assume the activity times are independent. a) What is the probability that the project will be completed between 35 and 45 days? b) If the time to complete the path A-B-D-F is normally distributed‚ what is the probability

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    Bsop434 Lab 1 Answers

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    sold to retail customers in an even flow. Low was uncertain of how many nails to order at any time. Initially‚ only two costs concerned him: order-processing costs‚ which were $60 per order without regard to size‚ and warehousing costs‚ which were $1 per year per keg space. This meant that Low had to rent a constant amount of warehouse space for the year‚ and it had to be large enough to accommodate an entire order when it arrived. Low was not worried about maintaining safety stocks‚ mainly because

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    Sport Obermeyer

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    Sport Obermeyer‚ Ltd. General Background Klaus Obermeyer emigrated from Germany to the United States in 1947 and started teaching at the Aspen Ski School. He was credited with making the first goose-down vest from a comforter in the 1950s. In 1992‚ estimated sales were $32.8 million with 45% share of children ’s skiwear market and 11% share of the adult skiwear market. It produced and sold parkas‚ vests‚ ski suits‚ shells‚ ski pants‚ sweaters‚ turtlenecks‚ and accessories

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    Chapter 13 Exercise Answers

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    Chapter 13: Determining Optimal Level of Product Availability Exercise Solutions 1. 0.2941 Optimal lot-size == NORMINV(0.2941‚100‚40) = 78.34 Given that p = $200‚ s = $30‚ c = $150: Expected profits = (p – s) NORMDIST((O – )/‚ 0‚ 1‚ 1) – (p – s) NORMDIST((O – )/‚ 0‚ 1‚ 0) – O (c – s) NORMDIST(O‚ ‚ ‚ 1) + O (p – c) [1 – NORMDIST(O‚ ‚ ‚ 1)] = $2‚657 Expected overstock = (O – )NORMDIST((O – )/‚ 0‚ 1‚ 1) +  NORMDIST((O – )/‚ 0‚ 1‚ 0) = 7.41 Expected understock = ( – O)[1 –

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    after day 60. Management’s main concern is managing the capacity of the lab in response to the complex demand pattern predicted. Delays resulting from insufficient capacity would undermine LL’s promised lead times and ultimately force LL turn away orders. * Based on an assignment written by Sunil Kumar and Samuel C. Wood‚ Stanford University Graduate School of Business. Copyright 2009. No part of this document may be reproduced without permission from Responsive Learning Technologies‚ Inc. info@responsive

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    Drift Vedlikehold

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    Project  report     MOM460  Operation  and  maintenance   management     Operation  and  maintenance  challenges  facing  the   development  of  Skrugard  and  Havis  facilities           Student   Fredrik  Haugland  Danielsen   Veronica  Hamarhaug   Annikken  Larsen   Linn  Underbakke     Student  number   204286   206810   207493   207349     Email   f.hauglanddanielsen@stud.uis.no   v.hamarhaug@stud

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    problems are how to forecast the future demand with limited uncertainty as well as would that be too risky if increasing production in China due to China’s larger minimum order requirement and intense trade relationship with US. To solve those problems‚ we can first lay out what information and conditions we have: The minimum order quantity is 600 in Hong Kong and 1200 in China. The average cost of producing in Hong Kong and China is $60.08 and $51.92 respectively. The expected profit is 24% of wholesale

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    point)   We know‚ A = d * LT‚ so the fixed order interval order quantity equation Q becomes Q = (d * LT) + (d * OI) – (d * LT)     * Q = d * OI = (6) (89)  = 534 units      Therefore‚ ordering at six-week intervals requires an order quantity of 534 units.   Now‚ the optimal order quantity is determined by using EOQ equation.   Q = sqrt(2dS/H)     = sqrt[(2*89*32)/.08]      =   266.833 (or) 267 The weekly total cost based on optimal order quantity EOQ is given below: TC of EOQ =

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