Towards Automated Simulation Input Data (original) (raw)
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Input Data Management methodology for Discrete Event Simulation
Proceedings of the 2009 Winter Simulation Conference (WSC), 2009
Input Data Management (IDM) is a time consuming and costly process for Discrete Event Simulation (DES) projects. In this paper, a methodology for IDM in DES projects is described. The approach is to use a methodology to identify and collect data, then use an IDM software to extract and process the data. The IDM software will structure and present the data in Core Manufacturing Simulation Data (CMSD) format, which is aimed to be a standard data format for any DES software. The IDM methodology was previously developed and tested by Chalmers University of Technology in a case study in the automotive industry. This paper presents a second test implementation in a project at the National Institute of Standards and Technology (NIST) in collaboration with an aerospace industry partner. 1 INTRODUCTION Discrete Event Simulation (DES) has proved itself to be an effective tool for complex processes analysis (Ericsson 2005; Banks et al. 2000). The drawback of using DES is the effort required and costs spent on processing the input data from various data sources to ensure valid simulation results. Large amount of time in a DES project is needed for gathering and extracting data (Skoogh and Johansson 2007). Most of the time, the needed information can be found in various Information Technology systems (IT-systems) in the companies. However, data is usually not in the right format required for DES and IT-systems do not have a standardized way of communicating with each other. This makes it hard to integrate several ITsystems and DES software and hence customized interfaces for exchanging information often need to be developed. A reusable, neutral, standardized interface should help reduce the effort and cost related to Input Data Management (IDM) in DES projects (Johansson et al. 2007). Researchers at the National Institute of Standards and Technology (NIST) have developed the Core Manufacturing Simulation Data (CMSD) specification (SISO 2009) to create a neutral format between common production software applications and DES tools. The concept has already been tested in pilot implementations in some case studies (Heilala et al. 2008, Johansson, and Zachrisson 2006, Johansson et al. 2007). For example, the CMSD was used to generate input data that can be reused for DES models developed using both Enterprise Dynamics (ED) and Plant Simulation (Johansson et al. 2007).
A test implementation of the core manufacturing simulation data specification
2007 Winter Simulation Conference, 2007
This paper describes an effort of testing the Core Manufacturing Simulation Data (CMSD) information model as a neutral data interface for a discrete event simulation model developed using Enterprise Dynamics. The implementation is based upon a model of a paint shop at a Volvo Car Corporation plant in Sweden. The model is built for a Swedish research project (FACTS), which focuses on the work procedure of developing new and modified production systems. FACTS has found standardized simulation data structures to be of high interest to achieve efficient data collection in conceptual stages of production development programs. For the CMSD-development team, implementations serve as an approach to validate the structures in CMSD and to gather requirements for future enhancements. CMSD was originally developed to support job shops, but the results of this implementation indicate a good possibility to extend CMSD to also support flow shops.
Information structure to support discrete event simulation in manufacturing systems
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693)
Discrete Event Simulation (DES) is ranked among the top three tools for management support. However, it lags in becoming the successful tool in the industry that many experts have predicted. In this paper, sixteen projects accomplished in the area of DES have been analyzed in order to find the reasons for this delay. Most important is the lack of reliable manufacturing data in companies. This is due to inadequate practices within the organization, thus forcing users to build simulation models with estimated data. The paper also answers other questions as to why DES is an underutilized decision tool. DES is an information-intensive tool for decision-making, but has weak support concerning working procedures within organizations. Continuous generation of manufacturing data at all levels has to be supported by the working procedure in order to increase the use of DES as an everyday tool. How to improve this situation also is discussed.
Application of Discrete Event Simulation in Industrial Sectors: A Case Study
— Discrete Event Simulation (DES) has become a useful tool in the evaluation of changes that may bring positivity to manufacturing and process organizations for both goods and services provision. The main focus of any business entails the reduction of cost and lead time while increasing profits and this is why refining of production processes is essential. This paper reports the application of DES in two case studies. The case studies selected for the implementation of Discrete Event Simulation are a packaging company and a local mobile phone service provider using the software FlexSim. The implementation aims at showcasing the versatility and its ability to provide the relevant data to make more informed decision while optimizing the entire processes involved in production.
Core manufacturing simulation data (CMSD)
2010
Standard representations for key manufacturing entities could help reduce the costs associated with simulation model construction and data exchange between simulation and other software applications. This change would make the use of simulation technology more affordable and accessible to a wide range of potential industrial users. To help foster this change, the Core Manufacturing Simulation Data (CMSD) specification was created. CMSD is a neutral, computer-interpretable representation for manufacturing shop floor related information. CMSD defines an information model that describes the characteristics of and relationships between the core manufacturing entities that define shop floor operations. This paper provides an overview of CMSD and describes how it can be used to enable data exchange between simulations and other manufacturing applications.
A survey of the use of the discrete-event simulation in manufacturing industry
Discrete-event simulation improves the possibility to study manufacturing systems. The use is increasing compared to previous studies and 15% of 80 companies investigated are using the tool and of these four companies extensively. The main advantage according to the survey beside the visualization part is that the knowledge about a system is investigated and documented. Other benefits can be basis for new investments and improvements of existing manufacturing lines. Of the companies that have adopted the technology, 79% answered that discrete-event simulation facilitates the decision-making process. Finally, the findings indicate that the potential of the software would be further increased if combined with adequate production improvement techniques to increase overall efficiency of a manufacturing system.
International Journal of Engineering and Advanced Technology
Discrete-Event Simulation (DES) is concerned with system and modeling of that system, where the state of the system is transformed at different discrete points from time to time, and several event occurs from time to time and the changes in state variables will transform then activities/attributes connected to these state variables changes according to the event. It is a robust methodology in the manufacturing industry for strategic, tactical, and operational applications for an organization, and yet organizations ignore to use simulation and do not rely on it. Moreover, companies that are using DES are not using the potential benefits but merely used as a short-hand basis for problems like bottlenecks, optimization, and in later stages of production like PLM, this paper aims to apply and analyze Discrete-Event Simulation through a Manufacturing System. The work describes here is to understand the concept of simulation for a system and to practice Discrete Event methodology
The Potential Role of Open Source Discrete Event Simulation Software in the Manufacturing Sector
Discrete event simulation (DES) is a valuable tool in the manufacturing sector due to its flexibility and ability to model even very complex systems, given sufficient time and resources. Despite its strengths, there seems to be less penetration in this industry than expected. Models are typically oneoff projects that are not maintained beyond the initial analysis. Industry based research conducted through the Irish Centre for Manufacturing Research suggests that due to cost and licensing restrictions, modelling is limited to a single user and consequently the associated skillsets are not developed more widely across the organisation. A possible solution is the use of open source DES which does not carry the same cost and licensing restrictions as the equivalent proprietary software. This paper reports on some of the open source packages currently on offer and provides a case study based comparison of open source and proprietary DES software.