Simulating Sudden Refugee Influx and Its Impact on Demographic Structure: the Korean Case

The problem of low fertility rate in a country gives rise to numerous other social and economic problems. Many solutions have been proposed for overcoming this issue, and immigration is one of the proposed solutions which may also entail opening up country for refuge, due to some unfortunate incidents in other countries. Working on these lines, we simulate the impact of rapid immigration influx on fertility rates in Korea, using real data and agent based modeling.

A Discrete Event Simulation Model to Test Multimodal Strategies for a Greener and More Resilient Wood Supply in Austria

Increasing occurrence of natural disturbances such as windstorms and high snow cover as well as uncer-tainty according to queuing and lead times, bottlenecks, utilization, stock level, wagon and truck availability and machine breakdowns lead to supply chain risks and seasonal irregularities in wood harvest and transport. Innovative multimodal systems via rail terminals offer the potential to increase buffer capacity and reduce greenhouse gas emissions. Therefore, a train terminal is included in a new virtual environment spanning the whole wood supply chain and enabling manager involvement in testing, analysis and evalua-tion of a complex multimodal transport system. The simulation model facilitates carrying out experiments and scenario designs for strategy comparisons in workshops with supply chain managers and provides in-tuitive decision support by animation and a KPI-cockpit. Adapting collaborative supply chain control strat-egies in participatory simulation enhances the development of advanced risk management and therefore improves supply chain resilience, efficiency and sustainability.

Simulation of a Coal Lading Port

This case study considers the simulation of a coal lading port in order to determine which extensions are needed based on expected capacity demands. These investigations are executed in cooperation with the German company TAKRAF GmbH which planned and constructed the considered port. Processes at this port are influenced by uncertainties, like the provided coal mix from mines and transportation times from mines to the port or meteorological disturbances. The maximum capacity of the current state of the port was determined at a first step. Components which mainly limit the maximum outcome were identified. Based on these results, different extension scenarios were evaluated.

Agent Based Simulation Marketing Mix Model for Budget Management in Cosmetic Industry

A worldwide leading company in the cosmetic industry was dealing with great challenges regarding adapting its positioning strategy to the dynamically changing behaviors of the market. The company needed to decide where to invest its marketing budget to optimize its revenue and was using different traditional marketing mix models without any success. A marketing mix model was developed using agent-based modeling to predict the market’s reaction to a given distribution of a certain budget among the different touchpoints available. This innovative model uses market information and consumer information collected from surveys to estimate the company’s sales, level of awareness and level of consideration given its distributed investment. The tool was implemented as part of the marketing plan decision making process, providing the ability to test different scenarios and generate quantitative analysis of its results.

Short-term Forecasting in Open Pit Mining Using Simulation Modelling

Simulation modelling has long been used to support operations strategy decisions in the mining industry. Recently, the commodity cycle and push for lower costs has driven efforts to improve operations efficiency. The use of simulation has typically been challenging in the operational time horizon due to the difficulty of initializing the system state and the sensitivity of the results to initial conditions. However, a recent explosion in data availability has made it feasible to know, in real time, the location of each piece of equipment in the fleet, what it is carrying and where it is going. This makes it possible to simulate and predict production performance within a shift and to allow testing of what-if scenarios to improve operations efficiency. In this case study we describe the approach taken, the application of simulation for short-term forecasting and the challenges faced implementing this for a global mining company.

The Role of Simulation Optimization in Process Automation for Discrete Manufacturing Excellence

We discuss the application of simulation to estimate a nominal, or target, processing times for work stations on a serial assembly line. The expectation is that having different processing times per station per product will increase the throughput of the line, compared to having a constant time for all stations. A demonstration case at ABB Robotics in Sweden will be presented. This is a small part in the “Process Automation for Discrete Manufacturing Excellence” project (PADME) involving five manufacturing industry partners and four research organizations, that aim at adapting Industrie 4.0 strategies and existing state-of-the-art technologies into new configurations, serving as a framework that can be used by similar industries.

Simulation Education in Non-simulation Courses

In many curricula and degree programs, simulation courses are not required, but these tools and techniques could be beneficial to students preparing for a variety of careers. The current paper describes two examples of simulation education embedded into broader course topics from a development perspective. The examples, from courses generally described in this paper as Cloud Computing and Big Data, offer a recommended approach for exposing students to practical uses of simulation. In the first example, we use simulation techniques to develop a web service emulation response database within a cloud computing environment for software testing. In the second example, simulation techniques provide an approach to generate data sets for learning data analytics techniques.

Towards a Multimodel Approach for Simulation of Crowd Behaviour Under Fire and Toxic Gas Expansion in Buildings

A holistic approach for the simulation of evacuations from buildings in cases of fire and toxic gas spread is developed within the German project iSiGG to achieve high reliability in fire safety planning. Its essence is in the mutual interaction of the domains of crowd simulation, pollutant gas spread simulation (CFD) and Building Information Modeling (BIM), embedded in a coherent IT system. The conceptual basis of this system is provided by a dynamic multimodel ensuring interoperability of all system components and supplying simulation tasks with the necessary building and environmental data. More importantly, it allows to take into account various possible changes of the state of building elements, which may be caused by inhabitants or by the building control systems and can lead to strong changes in the simulation models. The simulations themselves are coupled on numerical level through a shared Voxel Model in a co-simulation approach.

Flexibility as an Enabler for Carbon Dioxide Reduction in a Global Supply Chain: a Case Study From the Semiconductor Industry

Due to the significant rise in environmental awareness of companies and customers for the past few years, research on how to optimize business with respect to carbon dioxide (CO2) emission has gained more attention and importance. This paper investigates how flexibility can be an enabler for CO2 reduction over a global production network especially in a capital intensive and high volatile market like the semiconductor one. We tested this hypothesis with discrete-event simulation experiments based on a case study obtained from a semiconductor company. The study indicates that global supply chains (SCs), like those in the semiconductor industry, should be equipped with a certain level of flexibility to cope with demand volatility if the CO2 burden due to transportation is low compared to those due to manufacturing. This flexibility provides ecological benefits to companies in reducing the carbon footprint of their products.

Dynamic Price and Lead Time Quotation Under Semiconductor Industry Related Challenges

We consider the dynamic price and lead time quotation problem in the practical context of the semiconductor industry. Our model considers an inventory decoupled supply chain and accounts for a limited capacity, stochastic demand and processing times and quote-sensitive customers. We focus on performance evaluation under two decision making strategies. The first is lead time based pricing (LTBP). It follows a sequential approach where the firm decides first on the lead time quote (manufacturing) and then quotes the price under the given lead time (marketing). The second strategy suggests determining the lead time and the price quotes simultaneously. From the practical view-point, it is interesting to first understand the system performance under LTBP and then look for the ways to realize it. Based on our numerical results, we elaborate on the effect of LTBP on the key performance indicators and discuss conditions for close performance to a simultaneous decision strategy.