Executive Summary The Problem: Merton Truck Company has been experiencing difficulties related to their financial performance, and they do not know which is the optimal product mix to maximize profits and performance. Group 2 was asked to make recommendations and analyze the given situation to eliminate the difficulties and come up with the right product mix and the optimal solutions considering different alternatives and scenarios. The Solution: Linear Programming was used to analyze the different
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In the summer of 1988, Merton Truck Company (“Merton”) was struggling with financial performance. A manufacturer of two specialized trucks (model 101 and model 102), Merton was conflicted with how to manage production and improve financial results. The executive team offered many different options to improve performance, but many were conflicted. For example, the sales manager suggested cancelling all production of model 101 trucks, whereas the controller suggested increasing model 101 production
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Merton Trucks Case Note Abstract We discuss Merton Trucks [Dhe90a] as a case to introduce linear programming in the MBA program. This case adapted from Sherman Motor Company case, was used to introduce Linear Programming formulations as well as duality. Refer to the teaching note [Dhe90b]. Our approach differs from the approach suggested by Dhebar [Dhe90b]. First, our audience consists pre-dominantly of engineers with not too much work experience. As a result, handling math and algebra is relatively
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Memorandum To: Richard Merton, President, Merton Truck Company From: Khushdeep Kaur Date: October 22, 2013 ------------------------------------------------- RE: Merton truck company financial performance and product mix concerns Introduction: As requested an analysis was done to find out the most suitable product mix for Merton Truck Company in an effort to find out the combination that maximizes contribution and whether Truck 101 is really losing money or not. Analysis also aimed at finding
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MERTON TRUCK COMPANY Answer 1: Decision Variables: X1: Number of model 101 trucks to be produced X2: Number of model 102 trucks to be produced Objective: To maximise operational profit by optimally producing Model 101 and Model 102 trucks Maximise Z= 3000X1+5000X2 Subject to: X1+2X2<=4000 (Total machine hours available per month for engine assembly) 2X1+2X2<=6000 (Total machine hours available per month for Metal Stamping) 2X1<=5000 (Total machine hours available per month for Model 101
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Operations Research Assignment 1: Merton Truck Company Submitted to Professor Sumit Kumar By Sneh Chandel PGPX 2015-16 Roll No – 1503010 On 27/01/2015 Problem 1 1. (a) The best product mix can be found out by plotting out the corner points of graph obtained to maximize function p = 3000x + 5000y – 8600000 The above function was derived by subtracting cost price of ‘Truck model 101’ & ‘Truck Model 102’ from sales price of ‘Truck model 101’ & ‘Truck Model 102’. Sales price is
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------------------------------------------------- Lessons learnt from unintended consequences of innovations in technology ------------------------------------------------- Individual Assignment: MT5014 Systems Approach to Technology and Innovation Ravi Raman – A0008484A Abstract There have been many great innovations over the course of human history and they had many unintended consequences to the human society and to the technology in general. The study of unintended consequence has been
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Bring data - W edwards deming he theory of bounded rationality proposed by nobel laureate Herbert Simon is evermore significant today with increasing complexity of the business problems; limited ability of human mind to analyze alternative solutions and the limited time available for decision making. introduction of enterprise resource planning (eRP) systems has ensured availability of data in many organizations; however, traditional eRP systems lacked data analysis capabilities that can assist
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and LEAD International, London, November 2003 THE LEMELSON-MIT PROGRAM School of Engineering Massachusetts Institute of Technology 1 Workshop Participants ____________________________ Julia Marton-Lefèvre, Chair, LEAD International, UK Merton C. Flemings, Vice-Chair, Massachusetts Institute of Technology, USA Evan I. Schwartz, Rapporteur, Author and Independent Journalist, USA Shereen El Feki, The Economist, UK David Grimshaw, Intermediate Technology Development Group, UK Pamela Hartigan
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Valuation of Metals and Mining Companies Author: Svetlana Baurens E-Mail: baurens@basinvest.ch Date: 7.11.2010 In collaboration with the University of Zürich, Swiss Banking Institute and Prof. Dr. T. Hens Contents 1. Introduction ...............................................................................................................7 1.1. Motivation .......................................................................................................7 1.2. Structure .........
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