A methodology for input data management in discrete event simulation projects

ABSTRACT Discrete event simulation (DES) projects rely heavily on high input data quality. Therefore, the input data management process is very important and, thus, consumes an extensive amount of time. To secure quality and increase rapidity in DES projects, there are well structured methodologies to follow, but a detailed guideline for how to perform the crucial process of handling input data, is missing. This paper presents such a structured methodology, including description of 13 activities and their internal connections. Having this kind of methodology available, our hypothesis is that the structured way to work increases rapidity for input data management and, consequently, also for entire DES projects. The improvement is expected to be larger in companies with low or medium experience in DES

A Methodology for Continuous Quality Assurance of Production Data

High quality input data is a necessity for successful Discrete Event Simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a day-to-day engineering tool requires high quality production data to be constantly available. Unfortunately, there are no detailed guidelines that describes how to achieve this. Therefore, this paper presents such a methodology, based on three concurrent engineering projects within the automotive industry. The methodology explains the necessary roles, responsibilities, meetings, and documents to achieve a continuous quality assurance of production data. It also specifies an approach to input data management for DES using the Generic Data Management Tool (GDM-Tool). The expected effects are increased availability of high quality production data and reduced lead time of input data management, especially valuable in manufacturing companies having advanced automated data collection methods and using DES on a daily basis

Design of experiments for non-manufacturing processes : benefits, challenges and some examples

Design of Experiments (DoE) is a powerful technique for process optimization that has been widely deployed in almost all types of manufacturing processes and is used extensively in product and process design and development. There have not been as many efforts to apply powerful quality improvement techniques such as DoE to improve non-manufacturing processes. Factor levels often involve changing the way people work and so have to be handled carefully. It is even more important to get everyone working as a team. This paper explores the benefits and challenges in the application of DoE in non-manufacturing contexts. The viewpoints regarding the benefits and challenges of DoE in the non-manufacturing arena are gathered from a number of leading academics and practitioners in the field. The paper also makes an attempt to demystify the fact that DoE is not just applicable to manufacturing industries; rather it is equally applicable to non-manufacturing processes within manufacturing companies. The last part of the paper illustrates some case examples showing the power of the technique in non-manufacturing environments

The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets

The P3 platform: an approach and software system for developing diagrammatic model-based methods in design research

Many issues in design and design management have been explored by building models which capture the relationships between different aspects of the problem at hand. These models require computer support to construct and analyse. However, appropriate modelling tools can be time-consuming to develop in a research environment. Reflecting upon five design research projects, this paper proposes that such projects can be facilitated by recognising the iterative and tightly-coupled nature of research and tool development, and by attempting to minimise the effort of solution prototyping within this process. Our approach is enabled by a software platform which can be rapidly configured to implement many conceivable modelling approaches. This configurability is complemented by an emerging library of modelling and analysis approaches tailored to explore design process systems. The platform-based approach enables any mix of modelling concepts to be easily created. We propose it could thus help researchers to explore a wide range of questions without being constrained to existing conventions for modelling – or for model integration

Business process simulation: An alternative modelling technique for the information system development process

This paper discusses the idea that even though information systems development (ISD) approaches have long advocated the use of integrated organisational views, the modelling techniques used have not been adapted accordingly and remain focused on the automated information system (IS) solution. Existing research provides evidence that business process simulation (BPS) can be used at different points in the ISD process to provide better integrated organisational views that aid the design of appropriate IS solutions. Despite this fact, research in this area is not extensive; suggesting that the potential of using BPS for the ISD process is not yet well understood. The paper uses the findings from three different case studies to illustrate the ways BPS has been used at different points in the ISD process. It compares the results against IS modelling techniques, highlighting the advantages and disadvantages that BPS has over the latter. The research necessary to develop appropriate BPS tools and give guidance on their use in the ISD process is discussed

Panel on future challenges in modeling methodology

This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing

Fluid flow queue models for fixed-mobile network evaluation

A methodology for fast and accurate end-to-end KPI, like throughput and delay, estimation is proposed based on the service-centric traffic flow analysis and the fluid flow queuing model named CURSA-SQ. Mobile network features, like shared medium and mobility, are considered defining the models to be taken into account such as the propagation models and the fluid flow scheduling model. The developed methodology provides accurate computation of these KPIs, while performing orders of magnitude faster than discrete event simulators like ns-3. Finally, this methodology combined to its capacity for performance estimation in MPLS networks enables its application for near real-time converged fixed-mobile networks operation as it is proven in three use case scenarios

Conceptual modelling: framework, principles, and future research

The conceptual modelling task in a simulation project is very important and yet is still generally regarded as more of an art than a science. The meaning and nature of conceptual modelling are discussed and a framework set out. The overall aim should be to choose the best model for the project and conceptual modelling can be viewed as a difficult optimisation problem that can be tackled effectively using a creative search process that develops alternative models and predicts their performance throughout the project. An experiment relating model characteristics to some aspects of performance is described and this type of experiment may inform the process of predicting model performance. Based on advice from the literature and my own previous work on conceptual modelling 17 principles of conceptual modelling are suggested. Conceptual modelling research is still at an early stage and ideas for future research are proposed