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    Production line case study

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    Contents Product Annual Demand Daily Demand1 Weekly demand2 Level 0 Level 1 Level 2 Hub 1 2‚100 8.4 42 Sleeve (1) 2‚100 8.4 42 Mount (4) 8‚400 33.6 168 Bracket (2) 16‚800 67.2 336 Bolt (2) 16‚800 67.2 336 Hub 2 1700 6.8 34 Sleeve (1) 1‚700 6.8 34 Mount (5) 8‚500 34 170 Bracket (2) 17‚000 68 340 Bolt (2) 17‚000 68 340 Hub 3 2‚000 8 40 Sleeve (1) 2‚000 8 40 Mount (4) 8‚000 32 160

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    dasjdasdnafndsafna

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    Lecture 01 Introduction to Modelling and Simulation Peer-Olaf Siebers pos@cs.nott.ac.uk Container Terminal of Novorossiysk G54SIM 2 Module Mission Statement • This module will explain the main systems simulation methods in detail so that students will be competent in choosing and implementing the right method for their particular problem. • Students will learn the general principles and techniques used in modelling and simulation and will gain some practical experience

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    MSCI 609

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    construction and the company’s internal documents and policies. By using the Monte Carlo simulation technique‚ simulation of risks in completed infrastructural projects will be performed. This project will involve the performance of Monte Carlo simulations on two accomplished infrastructural projects. A Monte Carlo simulation is a problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs‚ called simulations‚ using random variables. The simulation will generate both a probability and a range of the outcome

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    into four broad approaches: Empirical models‚ simulation models‚ deterministic models‚ and stochastic models. The first three models can very much be integrated in teaching high school mathematics. The last will need a little stretching. Empirical modelling involves examining data related to the problem with a view of formulating or constructing a mathematical relationship between the variables in the problem using the available data. However‚ simulation modelling involve the use of a computer program

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    Simulation

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    A. The simulation model B. The number of patients treated every week and the waiting time for each patient | Number of patients treated | Waiting time for each patient (Min) | Outpatient department | 39 | 2465 | Inpatient department | 542 | 3616 | C. Some changes in the resource levels I. Each shift includes 2 admission secretaries | Number of patients treated | Waiting time for each patient (Min) | Outpatient department | 39 | 2515 | Inpatient department | 544

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    Hedge Fund

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    Number: (443)956-6067 E-mail Address: surban1@jhu.edu Teaching Assistant Ben Brock: bbrock1@jhu.edu Office Hours Saturdays‚ 10:00am – 12:30pm at DC Center (room 201) or by appointment Required Text and Learning Materials: Stochastic Simulation and Applications in Finance with MATLAB Programs‚ (2008)‚ Huu Tue Huynh‚ Van Son Lai‚ Issouf Soumare (HLS) [this book may be available as an e-book for students] MATLAB: An Introduction with Applications 4th Edition (2010) or earlier Editions

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    This simulation game was developed by Sisk (1976). Basically‚ there are ten imaginary countries (Shima‚ Myna‚ Ila‚ Usa‚ Pam‚ Bonay‚ Shivey‚ Lani‚ Ranu and Bili) and each of these countries has three key elements to be considered: defense‚ resources and demography. The main purpose of this game‚ understanding the importance of negotiation and interdependence between countries. I would like to make some changes in the game for my class. Every student or group will choose their imaginary country.

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    Simulation

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    Global Supply Chain Management Simulation Debrief Slides ©© Enspire Enspire Learning Learning and and Harvard Harvard Business Business School School (revised Dec 2010) 1 Board Members’ Objectives Member Objective Betty Forecasting: choice of options (consensus vs. mean) Doug Forecasting: choice of options (role of risk) Yvonne Stocking Levels: Weighing the costs of over/understocking Meryl Production flexibility: accurate response/ sourcing strategy (focus on flexibility) Paul Production

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    Tata Simulation

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    Introduction The world’s first all-optical notebook computer was launched in 2003 by Quasar. The Neutron is the result of revolutionary efforts by the company. The product processor and memory uses high-speed optical conductors that are five times the speed of existing microchip based companies. The Tata simulator exercise is an aid to decide which industry structure Quasar should use to increase profits‚ create competitive advantage and explores implications of each on business ventures. Market

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    simulation

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    1. What did you observe in inventory and back order levels when you play the game in uncoordinated and coordinated modes? What are the underlying reasons for the problems associated with uncoordinated decision-making? Based on the results you found in the previous part‚ list the potential benefits of coordination. (max 0.75 page) 2. What are the steps companies can take in order to reduce the problems associated with uncoordinated decision-making? Discuss also the potential implementation issues

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