Using the VinLogic Simulation Model: Insights Gained and Lessons Learned

I enjoyed the Global Supply Chain Management Simulation (GSCM). It was exciting to be a Manager of the supply chain of a mobile phone manufacturer. I learned very quickly the pressures of running such a large operation. In this review, I will discuss lessons learned regarding conceptions shown in the simulation. I will explain how if completing the simulation again, what I would complete differently. In conclusion, I will talk about my key overall takeaways from this exercise.

Recently, Tricia-Mart opened new branches to its existing ones. The management are keen on improving efficiency and services of the company. There are many ways in which this improvement can be done using simulation software: higher quality and efficiency from capital assets, better management of inventory, higher return on asset, this list is endless. But some of these improvements could be made without simulation, so the real question is ‘Why use simulation instead of another method such as real life experimentation?’

Management 460 is a case studies course in the management of manufacturing and service processes and operations. The course addresses manufacturing and service process selection and analysis, forecasting, capacity planning, aggregate

An ideal SCM integrates all aspects of logistics in a rapid manner attempting to achieve the objectives by using who, what, when, where, and why (the 5Ws) for accuracy and success. The focus of this literature will cover the history, functions, modifications and future of SCM, while also considering the literature and preceding research that was conducted in each area. This paper will enhance the readers’ understanding of the SCM in general along with the process and concepts of the subject. It will also enable readers to apply aspects of SCM in their respective line of business. The literature for this review is relative, ranging from one to three years old. Organizations must understand that Supply Chain Management can increase the company’s EBITA (Earnings Before Interest Taxes Amortization) or decrease it if used properly. An additional benefit of an optimal SCM is optimizing time from production to customer, which can increase customer base when the industry notice speed of delivery to customers.

This submission analyzes the results of the supply-chain simulation completed. This analysis will comprise several noted points encountered in the simulation. Each discussion point will include a discussion of the correlation of the author’s actions with the simulation results, comparative success results, and alternate actions to produce better results. Further analysis will be applied to the author’s actions with relation to just-in-time

Chase, R. B., & Jacobs, F. R. (2011). Operations and Supply Chain Management, 13e. Boston: McGraw-Hill Irwin.

The supply and demand simulation was a simulation of GoodLife Management, a property management firm controlling all of the seven apartment complexes in the city of Atlantis. For the 9 year period in the simulation the housing market had many ups and downs because of businesses moving into the area bringing an increased amount of jobs, the change in consumer preferences and company expectations, and the policy changes induced from the government.

I hold my breath in anticipation: the moment had finally arrived. What lay behind this door would be formidable, to say the least. However, knowing this only increased my excitement of what was to come. I glanced at my teammates, and a familiar combination of eagerness and anxiety met my eye. Ever-so-cautiously, we open the door and see our patient, awaiting our arrival – the test had begun.

In the following, a general overview of UML as a unified language will be given. It is important to provide a basis for a better understanding of how UML works in logistical processes. Therefore a short outline of the history and the development of UML will be presented with a subsequent explanation of what UML is and what types of diagrams exist.

Movement along the route was one of the many ways in which I could have improved in using the simulation. I feel that if I could have transported more product inventory along the route and between the warehouses and stores, I could have created a way to lower fuel cost more without increasing storage costs.

Russell, R. S., & Taylor III, B. W. (2014). Operations and Supply Chain Management, 8th edition. Hoboken, New Jersey: John Wiley & Sons, Inc.

SCM Globe is a supply chain game designed to teach concepts in supply chain design, demand forecasting, resource allocation, and production planning by the use of illustrating how different supply chain designs produce different operating results and explore how to manage those results. The game is performed in a real-time setting that allows for helping to create a supply chain that meet customer demands for products with the lowest operating costs and lowest inventory levels. The simulation gives students an opportunity to design and manage the supply chain of stores that sell Crunch Candy and Just Born Candy. During the simulation experience, students create products, facilities, vehicles and routes while

The most common implementations of supply chains throughout the US Army are focused on logistics and ensuring a continual stream of supplies to each base and installation. The periodic nature of supply chain planning for each base is made more challenging due to the need for greater levels of accounting accuracy and more effective approaches to statistical analysis of supply chain performance. These constraints over time have often been factored into the development of linear programming models used for simulating overall supply chain performance (Trainor, Parnell, Kwinn, Brence, 2007). Linear programming concentrates on solving complex supply chain problems including constrained logistics flows across multiple depots, locations and

(Bowersox, D.J., Closs, D.J., and Cooper, M.B. (2010). Supply Chain Logistics Management. (3rd Edition) New York, NY: McGraw-Hill/Irwin.

Simulation enables researchers to construct models to understand and evaluate current systems and alternatives for applying new processes or improving current processes in various areas (Greasley, 2004; Ingalls, 2008; Iqbal et al., 2012). The simulation method has been adopted in various industries such as airline, port operation, banking, service, food and transportation (Robinson, 2004; Kotachi et al., 2013). Although simulation raises quality concerns and does not provide absolute answers, simulation is flexible to design simple and complex processes (Chung, 2003; Kotachi et al., 2013). Researchers used different approaches to simulate returnable container (RC) models such as agent approach, regression approach and discrete event simulation approach. Apparwal (2014) used agent based system approach to study about RC based RFID tracking system for logistic services provider. Kim et al. (2014) used regression simulation model to study about RC for perishable products under stochastic return times.