...Teknologi Full paper Improving the Inventory Levels of a Blood Supply Chain Through System Dynamic Simulation Jafar Afshar*, Narjes Sadeghiamirshahidi, Ali Reza Firouzi, Seyed Mojib Zahraee, Syed Ahmad Helmi Syed Hassan Faculty of Mechanical Engineering, Department of Industrial Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia *Corresponding author: amir_1065@yahoo.com Article history Abstract Received :1 January 2014 Received in revised form : 15 February 2014 Accepted :18 March 2014 The blood supply chain is a complex system with a multi-echelon structure. Hence, the integration of various interconnected elements, which should be synchronized appropriately, is a necessity to meet the patients’ requirements. The performance of the blood supply chain is a function of different variables that are dependent of each other. Therefore, the main aim of the chain is the optimization of the overall supply chain by considering the dynamic behavior of the system. The purpose of this study is to develop a system dynamic simulation model for a complex blood supply chain in order to improve the average level of inventories. The developed model is based on three echelons with a centrality on a regional blood center. The performance of the supply chain network in the current condition is investigated and based on the objectives, 17 scenarios were experimented for improving the average level of inventories to avoid outdates while there are...
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...5 Supply Chain Management Based on Modeling & Simulation: State of the Art and Application Examples in Inventory and Warehouse Management Francesco Longo Modeling & Simulation Center – Laboratory of Enterprise Solutions (MSC-LES) Mechanical Department, University of Calabria Via P. Bucci, Cubo 44C, third floor, 87036 Rende (CS) Italy 1. Introduction The business globalization has transformed the modern companies from independent entities to extended enterprises that strongly cooperate with all supply chain actors. Nowadays supply chains involve multiple actors, multiple flows of items, information and finances. Each supply chain node has its own customers, suppliers and inventory management strategies, demand arrival process and demand forecast methods, items mixture and dedicated internal resources. In this context, each supply chain manager aims to reach the key objective of an efficient supply chain: ‘the right quantity at the right time and in the right place’. To this end, each supply chain node (suppliers, manufacturers, distribution centers, warehouses, stores, etc.) carries out various processes and activities for guarantying goods and services to final customers. The competitiveness of each supply chain actor depends by its capability to activate and manage change processes, in correspondence of optimistic and pessimistic scenarios, to quickly capitalize the chances given by market. Such capability is a critical issue for improving the performance of the ‘extended...
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...Wolf The simulation is broken down into a series of situations and provides suggestions throughout the inventory management system within the Elms Valley SurgiCare Center (EVSC). The simulation helps to demonstrate how cycle service level, lot sizes and safety stock have the influence to impact inventory cost. The data presented was used to calculate inventory levels as followed: I under-estimated the stock on hand quantities, over-estimated the demand for the gloves and also over-estimated the quantities ordered for the surgical gloves. Both EOQ’s were shown to be less than optimum per the simulations standards, but the decisions that I made were shown to be the best alternatives. The average price computed out to $0.27 each for surgical gloves, with what was considered to be an optimum cost of $.025 each, and $0.29 for exam gloves and an optimum cost of $0.24 each. The simulation also explored a “Quantity Discount Schedule” and the quantities required to experience price breaks. The introduction of new data was used to calculate the EOQ lot sizes and increase them to 4000 for both gloves followed by the order quantities decreased because of the excess supply. Both safety stocks and order quantities were within 100 of the optimum value. What was computed was the average cost per unit for surgical gloves at $.01 less than the optimum value, but exam gloves stayed the same, at $.01 more than the optimum value The next section of the simulation brought about...
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...A SYSTEM SIMULATION STUDY ON THE THREE FAST MOVING PRODUCTS (MARLBORO, C2, VIVA) OF THE COLLEGE VARIETY SHOPPE USING THE MONTE CARLO SIMULATION IN INVENTORY MANAGEMENT EXECUTIVE SUMMARY This study shows how the selected three fast moving products (Marlboro cigarettes, C2, Viva mineral water) move from the current Inventory Management technique of the College Variety Shoppe from its distributors to its warehouse storage to the end user or customer. An excel program and a simulation model was made to observed its current performance. After the observation, the group performs an experimentation that will improve the current technique of the College Variety Shoppe. After simulating the experimentation, the group then give conclusions and recommendations on how to improve the College Variety Shoppe’s current Inventory Management. TABLE OF CONTENTS Title Page ........................................................ 1 Executive Summary ........................................................ 2 Table of Contents ........................................................ 3 Introduction ........................................................ 4 Methodology ........................................................ 6 Model Development ........................................................ 7 Model Validation ........................................................ 11 Experimentation, Results .......
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...should be used to forecast any issues that might lie ahead. It also should be used to provide time to the company to make any necessary changes, before it is too late. By using budget and pro forma accounting any company should have a good understanding of what type of financial resources are available to them in order to cut costs and increase profits. During the simulation I initially did not pay too much attention to the budget or the pro forma accounting statements, which did not do me any favors. After reviewing the pro forma statement at the end of the first quarter, I should have made adjustments. The cash flow was lower than the recommended $300,000, so I reviewed my decisions, but did not want to change anything. Which inevitably put my company in a high risk situation right from the start. When the quarter was done and I was able to review the actions that had taken place, I realized I was way over budget and the simulation automatically set me up with a loan shark to help cover the costs. I was then burdened with paying back the loan shark with interest and stock share throughout the rest of the simulation. I was not able to successfully get out of the financial situation until the fourth quarter when my products were on the rise, but even then the loan shark held stock. By the end of the second quarter I learned my lesson and utilized the financial statements...
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...RJCT Task 1 Marketplace Simulation – Smart Systems A. Documents • Fourth quarter cumulative balanced scorecard. • Income statements for the four quarters • Balance sheets for the four quarters Fourth quarter cumulative balanced scorecard – Smart Systems Minimum Maximum Average Smart Systems Total Overall 0.00 444.77 5.76 20.03 Financial Performance -53.84 186.46 5.13 51.97 Market Performance 0.00 0.67 0.06 0.24 Marketing Effectiveness 0.00 0.81 0.12 0.73 Investment in Future 0.00 267.79 0.58 1.49 Wealth -0.90 4.57 0.24 1.94 Human Resource Management 0.00 0.81 0.12 0.70 Asset Management 0.00 2.13 0.18 1.46 Manufacturing Productivity 0.00 1.00 0.12 0.76 Financial Risk 0.00 1.00 0.16 1.00 Income Statement – Smart Systems Income Statement Quarter 1 Quarter 2 Quarter 3 Quarter 4 Gross Profit Revenues 0 2,292,030 6,805,030 15,734,725 - Rebates 0 120,625 241,200 524,800 - Cost of Goods Sold 0 1,491,528 4,012,841 8,427,764 = Gross Profit 0 679,877 2,550,989 6,782,161 Expenses Research and Development 120,000 0 60,000 60,000 + Advertising 0 160,000 268,875 320,798 + Sales Force Expense 0 120,186 319,875 546,937 + Sales Office Expense 220,000 330,000 470,000 370,000 + Marketing Research 0 15,000 15,000 15,000 + Shipping 0 36,184 86,397 141,905 + Inventory Holding Costs 0 9,727 13,220 0 + Excess Capacity Cost 0 255,693 528,982 0 + Depreciation 0 25,000 70,833 95,833 = Total Expenses...
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...relationships between different income statements and balance sheet accounts. A set of current financials serve as the foundation on which the pro forma will be built.” (Vlieland-Boddy, 2011) With starting a new company and brand, I did not have much in the way of current financials to use for helping create the pro forma statements initially. When I did start receiving the reports, the information was hard for me to use for projections due to the lack of a track record to prove to me that I was on the right track with my planning. Due to my conservative nature I feel more comfortable basing decisions on historical facts and because of this my planning was too focused on the short term and was influenced by finance. When I began the simulation, I based everything off of the projected demand numbers provided. I then made the assumption that I would not...
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...place on the first Littlefield simulation game we knew what we needed to do to win the second simulation game. We were very eager to outperform our competition and we almost did so, but ended up in second place again with a cash balance of $2,660,393. The second Littlefield simulation game focused on lead time and inventory management in an environment with a changing demand (“but the long-run average demand will not change over the product’s 268-day lifetime”). Therefore our strategy to win this game was controlling the Littlefield Lab’s system capacity and the inventory level with choosing a right contract as well as keeping the cash daily as much as possible. In other words, we first needed to find daily average demand and match it to the Littlefield Lab’s system capacity. Second, we controlled the inventory level with finding right QOPT (Optimal Order Quantity) and reorder point according to continuous review system method. Lastly we chose the right contract among our 3 options to maximize the profits according to daily average job lead-time. When first approaching this game we met to strategize, forecast, make a meeting schedule, and divide the work. At our first meeting we analyzed the first given 50 days so that we could get the daily average demand and SD (Standard Deviation). First, 50 days of daily average demand was 15.50 and SD was 4.12. With the daily average demand and SD we could control the Littlefield Lab’s system capacity. Since “neither the...
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...INTRODUCTION: The purpose of this paper is to bring out the use of Simulation by Managers of various organizations. Under discussion will be: Definition of simulation. Model construction. When and why it becomes handy to use simulation. Steps used in simulation technique. Random selection in simulation. Advantages / benefits derived from use of simulation technique. Disadvantages /Challenges associated with simulation technique. Role of computer in simulation. Conclusion / comments. Definition of simulation: Simulation can be defined as a quantitative technique which describes a process by developing a model of that process and then conduct a series of organized trial and error experiments to predict the behavior of the process through time often with the aid of a computer. It is a method that is used to solve a problem in many areas of management, for example inventory management, queuing problems, profit analysis and project management among others. Model construction: A successful simulation model has to be carefully designed in order to achieve the intended predictive purpose. Therefore important factors have to be considered such as; i. It must be objective oriented. It must be constructed for a purpose and be able to achieve that purpose. ii. Critical variables and relationships. These must be identified and incorporated in model. However it is not essential or indeed desirable to include all variables in the model. iii. Simplicity...
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...The Root Beer Game Simulation John Doe TUI University ITM 436 Operations Mgmt and Operations Sys. John Doe, Ph.D. What I learn about supply chain management during this tutorial? Successful supply chain management is significant to the survival of today’s business. To review supply chain strategies and evaluate proposed changes that impact the business as a hole, supply chain managers should be able to assertively predict their network’s performance under a range of conditions. This apparently impossible task has urged a search for better software to help decision makers analyze the design and operation of their supply chain. Computer simulations have become the tool of choice. Since simulation capture real world system variability, a simulation program helps managers to better understand the supply chain as it presently exists. Most significantly, a simulation gives planners a realistic view of what will happen in their supply chain under conditions that do not currently exist, but might take place. The tutorial presented a distribution network for a root beer beverage. The simulation starts in week 16 of the inventory with 170,000 cases of root beer on backlog. Having product cases on inventory or backlog will add additional expenses to the company (inventory $.50/bottle and Backlog costs $1/bottle). The business objectives include reducing inventory and backlog cost. The simulation project provides managers a tool for supporting strategic supply chain decisions...
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...existed. Changes made to the simulation for run number two of the paper airplane factory were implemented as a means of combatting the chaotic atmosphere that were present during run number one. These changes are listed as follows. Workstations one through four were relocated to one table. Signal cards were placed on the table after each workstation. The foreman was no longer part of the simulation, and the paper stock inventory was relocated to a position right beside workstation one on the table. Batch sizes were reduced to just one unit. The same work instruction was used for each operation just as in run number one. The material handler was in charge of moving one batch from the inventory...
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...service was offered. As a retailer manager, one of the important things he or she might focus on is that the queue line length which could not be too long or too short. If the queue line is too long, the customer would be impatient and complain about the service quality the shop offers while if the shop gives too many counters to deal with the customers transaction further to reduce the length of the queue, it is definitely to increase the cost of the operation. Queue Theory is a kind of tool that could help the managers who need to analyze the queue line and estimate the cost of controlling it to understand the situation and make a decision on it. The prerequisite of Queue Theory is that the customers, services and other factors in the systems are discrete. In other words they are independent with each other since the rate of the customer coming and the rate of the service provided would not affect each other. Then these factors could meet the demand of Poisson Distribution. There are four models about Queuing Theory according to our textbook: MM1- Single-Server Queuing Model, MMS- Multiple-Server Queuing Model, MD1- Constant-Service-Time Model and Limited-Population Model. They are very useful in the different areas in the business. The first model single-server Queuing Model is the model the paper plan to explain a little detailed than the other three. In the real situation, you could easily imagine that there is a queue line with a large amount of people waiting for checking...
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...PART ONE Introduction to Discrete-Event System Simulation 1 Introduction to Simulation A simulation is the imitation of the operation of a real-world process or system over time. Whether done by hand or on a computer, simulation involves the generation of an artificial history of a system, and the observation of that artificial history to draw inferences concerning the operating characteristics of the real system. The behavior of a system as it evolves over time is studied by developing a simulation model. This model usually takes the form of a set of assumptions concerning the operation of the system. These assumptions are expressed in mathematical, logical, and symbolic relationships between the entities, or objects of interest, of the system. Once developed and validated, a model can be used to investigate a wide variety of “what-if” questions about the realworld system. Potential changes to the system can first be simulated in order to predict their impact on system performance. Simulation can also be used to study systems in the design stage, before such systems are built. Thus, simulation modeling can be used both as an analysis tool for predicting the effect of changes to existing systems, and as a design tool to predict the performance of new systems under varying sets of circumstances. In some instances, a model can be developed which is simple enough to be “solved” by mathematical methods. Such solutions may be found by the use of differential calculus, probability...
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...RJCT Task 1 B1. Budgets and pro forma statements are very important to the success of the simulation. You needed to keep close track of your available funds, and it was also important to be able to predict how your expenditures would affect your success. Budgets are where we allot amounts to be spent in specific areas for the business. Without a budget, it is no doubt that spending would get out of control and the business would soon fail. Without a budget, I would have likely spent way too much on making and advertising my products in the simulation. It was great that each of these areas had a sort of guide when it came to how much was actually a good idea to spend. Pro forma statements are a sort of hypothetical or possible statement of the future based on certain inputs and factors. This was a great help in the simulation because it allows you to project possible future earnings, risks and so on. It also helped gauge whether or not our business in the simulation would be left with enough funds to continue. Both of these tools work hand in hand in an attempt to keep your company out of debt. I used these in the simulation to help me gauge just how much it might be wise to spend on things like expansion, inventory, and so on. I would decide if I had enough money to spend by keeping track of expenses in my budget, and then I would look at my pro forma statement to see what they would predict as the outcome of the quarter. This helped me decide whether or not to spend...
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...Management Sciences (JETEMS) 2(2):131-141(ISSN:2141-7024) Information Distortion in Supply Chain: A Simulation Approach to Quantifying the Bullwhip Effect 1 1 Oyatoye, E.O and 2Fabson, T.V.O Department of Business Administration University of Lagos, Akoka-Yaba, Lagos, Nigeria 2 Telsy Value Consult, Onike Road, Iwaya, Lagos, Nigeria Corresponding Author: Oyatoye, E.O ____________________________________________________________ ______________________________ Abstract Supply chain exists due to the fact that it is difficult for any company to provide all that is required from raw materials to final products and at the same time get the products to the end users. Successful supply chain management requires a change from managing individual functions to integrating activities into key supply chain process; hence, accurate information is of essence. One of the key factors that can adversely affect effective and efficient supply chain process is information distortion. Demand forecasting and ordering policies have been recognized as two key causes of bullwhip effect in supply chain management. This study explored the simulation approach in quantifying the effect of bullwhip in supply chain, using various forecasting methods. ____________________________________________________________ ______________________________ Keywords: information distortion, supply chain, simulation, quantifying bullwhip effect, forecasting methods ____________________________________________________________ ...
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