Improving a process in a brazilian automotive plant applying process mapping, Design of Experiments and Discrete Events Simulation

The objective of this article is to apply the Design of Experiments technique along with the Discrete Events Simulation technique in an automotive process. The benefits of the design of experiments in simulation include the possibility to improve the performance in the simulation process, avoiding trial and error to seek solutions. The methodology of the conjoint use of Design of Experiments and Computer Simulation is presented to assess the effects of the variables and its interactions involved in the process. In this paper, the efficacy of the use of process mapping and design of experiments on the phases of conception and analysis are confirmed.

Step size control for efficient discrete element simulation

The step size determines the accuracy of a discrete element simulation. The position and velocity updating calculation uses a pre-calculated table and hence the control of step size can not use the integration formulas for step size control. A step size control scheme for use with the table driven velocity and position calculation uses the difference between the calculation result from one big step and that from two small steps. This variable time step size method chooses the suitable time step size for each particle at each step automatically according to the conditions. Simulation using fixed time step method is compared with that of using variable time step method. The difference in computation time for the same accuracy using a variable step size (compared to the fixed step) depends on the particular problem. For a simple test case the times are roughly similar. However, the variable step size gives the required accuracy on the first run. A fixed step size may require several runs to check the simulation accuracy or a conservative step size that results in longer run times. (C) 2001 Elsevier Science Ltd. All rights reserved.

Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation

Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.

Experimental and discrete element simulation studies of bell-less charging of blast furnace

This thesis presents an experimental study and numerical study, based on the discrete element method (DEM), of bell-less charging in the blast furnace. The numerical models are based on the microscopic interaction between the particles in the blast furnace charging process. The emphasis is put on model validation, investigating several phenomena in the charging process, and on finding factors that influence the results. The study considers and simulates size segregation in the hopper discharging process, particle flow and behavior on the chute, which is the key equipment in the charging system, using mono-size spherical particles, multi-size spheres and nonspherical particles. The behavior of the particles at the burden surface and pellet percolation into a coke layer is also studied. Small-scale experiments are used to validate the DEM models.

Application of Design of experiments on the simulation of a process in an automotive industry

The objective of this article is to apply the Design of experiments technique along with the Discrete Events Simulation technique in an automotive process. The benefits of the design of experiments in simulation include the possibility to improve the performance in the simulation process, avoiding trial and error to seek solutions. The methodology of the conjoint use of Design of Experiments and Computer Simulation is presented to assess the effects of the variables and its interactions involved in the process. In this paper, the efficacy of the use of process mapping and design of experiments on the phases of conception and analysis are confirmed. © 2007 IEEE.

A Framework for the Automation of Discrete-Event Simulation Experiments

Simulation is an important resource for researchers in diverse fields. However, many researchers have found flaws in the methodology of published simulation studies and have described the state of the simulation community as being in a crisis of credibility. This work describes the project of the Simulation Automation Framework for Experiments (SAFE), which addresses the issues that undermine credibility by automating the workflow in the execution of simulation studies. Automation reduces the number of opportunities for users to introduce error in the scientific process thereby improvingthe credibility of the final results. Automation also eases the job of simulation users and allows them to focus on the design of models and the analysis of results rather than on the complexities of the workflow.

Modelling a biomass supply chain through discrete-event simulation

The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided

Forest-based supply chain modelling using the SimPy simulation framework

Proper management of supply chains is fundamental in the overall system performance of forestbased activities. Usually, efficient management techniques rely on a decision support software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains’ nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forestbased supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event systems using operations such as events, processes and resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic behaviours of processing and driving times were simulated. The obtained results validate the SimPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.

Using system dynamics in a discrete-event simulation study of a manufacturing plant

Purpose - To provide an example of the use of system dynamics within the context of a discrete-event simulation study. Design/methodology/approach - A discrete-event simulation study of a production-planning facility in a gas cylinder-manufacturing plant is presented. The case study evidence incorporates questionnaire responses from sales managers involved in the order-scheduling process. Findings - As the project progressed it became clear that, although the discrete-event simulation would meet the objectives of the study in a technical sense, the organizational problem of "delivery performance" would not be solved by the discrete-event simulation study alone. The case shows how the qualitative outcomes of the discrete-event simulation study led to an analysis using the system dynamics technique. The system dynamics technique was able to model the decision-makers in the sales and production process and provide a deeper understanding of the performance of the system. Research limitations/implications - The case study describes a traditional discrete-event simulation study which incorporated an unplanned investigation using system dynamics. Further, case studies using a planned approach to showing consideration of organizational issues in discrete-event simulation studies are required. Then the role of both qualitative data in a discrete-event simulation study and the use of supplementary tools which incorporate organizational aspects may help generate a methodology for discrete-event simulation that incorporates human aspects and so improve its relevance for decision making. Practical implications - It is argued that system dynamics can provide a useful addition to the toolkit of the discrete-event simulation practitioner in helping them incorporate a human aspect in their analysis. Originality/value - Helps decision makers gain a broader perspective on the tools available to them by showing the use of system dynamics to supplement the use of discrete-event simulation. © Emerald Group Publishing Limited.

Modelling manufacturing planning and control systems:the application of object-oriented principles and discrete-event simulation

Manufacturing planning and control systems are fundamental to the successful operations of a manufacturing organisation. 10 order to improve their business performance, significant investment is made by companies into planning and control systems; however, not all companies realise the benefits sought Many companies continue to suffer from high levels of inventory, shortages, obsolete parts, poor resource utilisation and poor delivery performance. This thesis argues that the fit between the planning and control system and the manufacturing organisation is a crucial element of success. The design of appropriate control systems is, therefore, important. The different approaches to the design of manufacturing planning and control systems are investigated. It is concluded that there is no provision within these design methodologies to properly assess the impact of a proposed design on the manufacturing facility. Consequently, an understanding of how a new (or modified) planning and control system will perform in the context of the complete manufacturing system is unlikely to be gained until after the system has been implemented and is running. There are many modelling techniques available, however discrete-event simulation is unique in its ability to model the complex dynamics inherent in manufacturing systems, of which the planning and control system is an integral component. The existing application of simulation to manufacturing control system issues is limited: although operational issues are addressed, application to the more fundamental design of control systems is rarely, if at all, considered. The lack of a suitable simulation-based modelling tool does not help matters. The requirements of a simulation tool capable of modelling a host of different planning and control systems is presented. It is argued that only through the application of object-oriented principles can these extensive requirements be achieved. This thesis reports on the development of an extensible class library called WBS/Control, which is based on object-oriented principles and discrete-event simulation. The functionality, both current and future, offered by WBS/Control means that different planning and control systems can be modelled: not only the more standard implementations but also hybrid systems and new designs. The flexibility implicit in the development of WBS/Control supports its application to design and operational issues. WBS/Control wholly integrates with an existing manufacturing simulator to provide a more complete modelling environment.

Implementing an agent-based model with a spatial visual display in discrete-event simulation software

There has been an increasing interest in the use of agent-based simulation and some discussion of the relative merits of this approach as compared to discrete-event simulation. There are differing views on whether an agent-based simulation offers capabilities that discrete-event cannot provide or whether all agent-based applications can at least in theory be undertaken using a discrete-event approach. This paper presents a simple agent-based NetLogo model and corresponding discrete-event versions implemented in the widely used ARENA software. The two versions of the discrete-event model presented use a traditional process flow approach normally adopted in discrete-event simulation software and also an agent-based approach to the model build. In addition a real-time spatial visual display facility is provided using a spreadsheet platform controlled by VBA code embedded within the ARENA model. Initial findings from this investigation are that discrete-event simulation can indeed be used to implement agent-based models and with suitable integration elements such as VBA provide the spatial displays associated with agent-based software.

Using discrete event simulation to investigate road delivery policies to UK retailers

Retail customers provide a number of significant challenges to the efficiency and effectiveness of distribution systems. These challengers include shorter delivery windows, fluctuating volumes and a wider product mix. This paper demonstrates the use of discrete-event simulation to investigate policy issues regarding the incorporation of retail customers in a road delivery network from the spoke terminal of a hub and spoke distribution system. In particular a comparison of a mixed (retail and non-retail) delivery policy with a dedicated retail delivery run is made.

Methods of modelling people using discrete-event simulation

Discrete-event simulation (DES) is a developed technology used to model manufacturing and service systems. However, although the importance of modelling people in a DES has been recognised, there is little guidance on how this can be achieved in practice. The results from a literature review were used in order to identify examples of the use of DES to model people. Each article was examined in order to determine the method used to model people within the simulation study. It was found that there are no common methods but a diverse range of approaches used to model human behaviour in DES. This paper provides an outline of the approaches used to model people in terms of their decision making, availability for work, task performance and arrival rate. The outcome brings together the current knowledge in this area and will be of interest to researchers considering developing a methodology for modelling people in DES and to practitioners engaged with a simulation project involving the model ling of people’s behaviour.