Introduction to O&SCM -- Chapter 1 • Definitions • Operations and supply chain management (OSCM) is defined as the design‚ operation‚ and improvement of the systems that create and deliver the firm’s primary products and services • Concerned with the management of the entire system that produces a product or delivers a service • Operations refers to manufacturing and service processes that are used to transform the resources employed by a firm into products desired by customers •
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Study Guide for the Second Exam Aggregate Production Planning (APP) 1. What are the major inputs‚ constraints‚ and outputs of the aggregate production plan (APP)? Inputs - Strategic objectives of the corporation‚ policies‚ demand. Constraints - financial constraints (cash) and capacity constraints (machining capacity‚ limited labor in certain skill category‚ a critical component and/or raw material.) Outputs - is to determine the gross levels of inventory‚ overtime‚ subcontracting‚ backordering
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Accounting Estimate • Accounting estimate – An approximation of a monetary amount in the absence of a precise means of measurement. This term is used for an amount measured at fair value where there is estimation uncertainty‚ as well as for other amounts that require estimation. PSA 540 9 The auditor shall review the outcome of accounting estimates included the prior period financial statements‚ or‚ where applicable‚ their subsequent re-estimation for the purpose of the current period. The nature
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Greaves Brewery Case Analysis Greaves Brewery: Bottle Replenishment Case Analysis Case Synopsis The following is an analysis of the case‚ Greaves Brewery: Bottle Replenishment. It details the growing beer operation of Greaves Brewery located in the Caribbean island of Trinidad. The purchasing manager for the company‚ Alex Benson‚ is uncertain about how many bottles to order from the company’s German glass supplier. His decision is complicated by the possibility of a new bottle design being
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OPR1010 Operations Management (Winter 2010) In-class Assignment 2: Forecasting Directions: ( We will check the answers during the supplemental session on Feb. 18. (Participation points will be considered for volunteers. (This is not a take-home assignment. You do not have to turn in the answers. (Use MS-Excel for Questions 1 through 4. Q-1. The Polish General’s Pizza Parlor is a small restaurant catering to patrons with a taste for European Pizza. One of its specialties is Polish Prize
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106 (Chapter 3) of Text Book Heizer‚Render & Rajashekhar (a) Using exponential smoothing‚ with α = .6‚ then trend analysis‚ and finally linear regression discuss which forecasting model fits best for Salinas’s strategic plan. Justify the selection of one model over another. Answer: We have done forcasting using exponential smoothing and linear regression methods. Below are the forcast values: Method Exponential smoothing MAD 3.5 Linear Regression 10.6 Year 1 1 2 3 4 5
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software that was used in order to predict the future sales was StatTools. StatTools provided me with four different methods (Moving Averages‚ Simple‚ Holt’s & Winters’ exponential smoothing) of forecasting to identify the most accurate prediction possible. With a Means Absolute Percentage Error (MAPE) of 3.72% the Holt’s exponential smoothing method was determined to be the best method of predicting monthly wine sales for the next sixteen months (Figure 2). Background/Additional Research
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1. (24 points) If needed‚ additional workspace is provided on the next sheet. Doug Moodie is the president of Garden Products Limited. Over the last 5 years‚ his vice president of marketing has been providing the sales forecast using his special “focus” forecasting technique. The actual sales for the past ten years and the forecasts from the vice president of marketing are given below. |Year |Sales |VP/Marketing
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Index Cover Page 1 1. Executive Summary 3 2. Background 3 3. Issue Statement 4 4. Analysis of the problem 4-9 1. Moving Average 4-6 2. Holt Winters’ Exponential Smothing 6-7 3. Simple Average 7 3. Exponential Smothing 8-9 5. Recommandations 10 6. References 11 Executive Summary In the given case study‚ Snow the revenue manager of the Hamilton hotel has to make a decision which is to accept the group of not for 22nd August. As it is a business hotel and generally it
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Contents Introduction Some applications of forecasting Defining forecasting General steps in the forecasting process Qualitative techniques in forecasting Time series methods The Naive Methods Simple Moving Average Method Weighted Moving Average Exponential Smoothing Evaluating the forecast accuracy Trend Projections Linear Regression Analysis Least Squares Method for Linear Regression Decomposition of the time series Selecting A Suitable Forecasting Method More on Forecast Errors Review Exercise CHAPTER
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