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    Aggregate Planning - Essay

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    PRODUCTION MANAGEMENT ASSIGNMENT Topic:- Aggregate Planning Submitted by:- ANJANA KRISHNAN FM-673 AGGREGATE PLANNING: Aggregate planning is the process of developing‚ analyzing‚ and maintaining a preliminary‚ approximate schedule of the overall

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    Qualitative Forecasting

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    educated opinions of appropriate persons 1. Delphi method: forecast is developed by a panel of experts who anonymously answer a series of questions; responses are fed back to panel members who then may change their original responses a- very time consuming and expensive b- new groupware makes this process much more feasible 2. Market research: panels‚ questionnaires‚ test markets‚ surveys‚ etc. 3. Product life-cycle analogy: forecasts based on life-cycles of similar

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    L.L.Bean case Study

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    merchandising‚ design‚ product‚ and inventory specialists. The first step of its creation process is initial conceptualization followed by the preliminary forecasts of total sales. Then forecasts were developed by book. After the layout and pagination of the books‚ initial commitments to vendors were made. The subsequent step is that item forecasts were repeatedly revised and finally the items were fixed. When catalogs were in the hands of customers‚ inventory managers decided on additional commitments

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    Chapter 1 Introduction to Operations Management True/False 1. Operations managers are responsible for assessing consumer wants and needs and selling and promoting the organization’s goods or services. Answer: False  Page: 4 Difficulty: Easy 2. Often‚ the collective success or failure of companies’ operations functions will impact the ability of a nation to compete with other nations. Answer: True Page: 4  Difficulty: Easy 3. Companies are either producing

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    National Institute of Technology Calicut Department of Mechanical Engineering PRODUCTION PLANNING (AGGREGATE PLANNING) § § § § Concerned with the overall operations of an organisation over a specified time horizon Determines the efficient way of responding (allocating resources) to market conditions Effectively allocate system capacity (plant‚ equipment‚ and manpower) over designated period A good production plan should Ø be consistent with organisational policy Ø meet demand requirements

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    graph of the data. On this same graph‚ plot a 12-month moving average forecast. Discuss any apparent trend and seasonal patterns. 2. Use regression to develop a trend line that could be used to forecast monthly sales for the next year. Is the slope of this line consistent with what you observed in question 1? If not‚ discuss a possible explanation. 3. Use the multiplicative decomposition model on these data. Use this model to forecast sales for each month of the next year. Discuss why the slope of the

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    Solution

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    STAT 758: Homework #6 Due on Wednesday‚ 11 April‚ 2012 Zaliapin‚ 1:00pm Tracy Backes 1 Tracy Backes STAT 758 (Zaliapin): HW #6 Problem #1 We assume below that Zt ∼ W N (0‚ σ 2 )‚ B is a backshift operator. 6.1 For the model (1 − B)(1 − 0.2B)Xt = (1 − 0.5B)Zt : a) Classify the model as an ARIMA(p‚ d‚ q) process (i.e. find p‚ d‚ q). ARIMA(1‚1‚1) b) Determine whether the process is stationary‚ causal‚ invertible. • The process is stationary if all roots of ϕ(z) are off of the unit

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    MGT 2070 Assignment

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    with week 2 and ending with week 11‚ forecast registrations using the naïve forecasting method. Naïve Forecast Ft = At-1 ie F2 = A1 = 22. Carrying this down the table through to week 11 gives: Week 1 2 3 4 5 6 7 8 9 10 11 Registrations 22 21 25 27 35 29 33 37 41 37 Forecast 22 21 25 27 35 29 33 37 41 37 (3 marks) b) Starting with week 3 and ending with week 11‚ forecast registration using a two-week moving average. Moving Average Forecast Ft = ie F3 = = = 21.5. Carrying

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    LL Bean Case Study

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    past demand data and a specific item forecast to decide how many units of that item to stock? L.L. Bean uses different type of calculation to determine the number of units of a particular item it should stock (new item or never out item). First we detect a frozen demand forecast for the item in the upcoming season. This figure is a result of an agreement between product people‚ merchandising‚ design and inventory specialists. Then‚ we analyze the historical forecast errors (named A/F ratios) and the

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    Forecast

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    Production and Operations Management Report BSE Supplement Product Made by Miss Benjawan Pornsawan | 5431203038 | Mr. Pornchai Khunlavanish | 5431203052 | Mr. Surachai Sakdakongka | 5431203087 | Mr.Sai kung shan | 5431203117 | Miss Jintana Kaising | 5431203126 | Mr.Patiwat Autapong | 5431203135 | Miss Siriporn Ngeoninta | 5431203138 | Miss Suphaphit Totaeng | 5431203148 | Miss Yinling Zhang | 5431203508 | Miss Angsana Kaewsai | 5531209123 | Mr.Woramate Jumjoung | 5431201092

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