A methodological approach to develop an integrated simulation system in manufacturing processes (original) (raw)
Related papers
An integrated approach to develop a simulation model in manufacturing processes
International Journal of Systems Applications, …
The present paper faces the problem of simplifying simulation tools management in their industrial applications. An approach to implement efficiently and effectively simulation models in manufacturing systems, as decision support system, is deployed. The framework proposed is very flexible and easy to use because of the building block architecture and the automatic model generation. This model is focused on operational decisions as those concerning with scheduling problems.
Towards an improved tool to facilitate simulation modelling of complex manufacturing systems
The International Journal of Advanced Manufacturing Technology, 2009
Computer-based simulation is one of the most valuable aids for manufacturing systems design, yet its use remains limited. The main reason for this is that current manufacturing systems are extremely complex and the user-friendly capabilities provided even by the most advanced simulation tools are not sufficient to cope with such complexity. On this basis, the paper explores the development of an improved tool to ease and speed up simulation modelling of complex manufacturing systems. A simulation interface, created and currently used at a major automotive manufacturer, is considered and a rigorous assessment of the extent to which this interface can support the simulation modelling process is provided. The paper evaluates the viability to use the interface as a basis for a general purpose simulation modelling tool capable of coping with any complex manufacturing systems, analyses its potential values, and proposes developments that can support the uptake of simulation techniques within the manufacturing industry.
DEVELOPMENT OF A PROCEDURE FOR MANUFACTURING MODELLING AND SIMULATION
Simulation is a powerful tool for allowing designers imagine new systems and enabling them to both quantify and observe behaviour. Whether the system is a production line, an operating room or an emergency-response system, simulation can be used to study and compare alternative designs or to troubleshoot existing systems. With simulation models, we can explore how an existing system might perform if altered, or how a new system might behave before the prototype is even completed, thus saving on costs and lead times.
… Seminar on Manufacturing Systems', …, 2000
This paper outlines a methodology for development of future manufacturing systems, where modeling and simulation are naturally integrated components, supporting all business decisions and stretching beyond their traditional application areas. The research described here has two objectives: (i) to provide a basis for joint research efforts within this area, and (ii) to contribute with integration of simulation into such a methodology. Developing such a methodology will be necessary to deal with an increasingly complex and competitive global business environment, characterized by change and uncertainty. It will be crucial in the realization of enterprise integration, and virtual and extended enterprises. The methodology aims at building on work already done in this area, and to use established standards to as large an extent as possible.
Simulation-Based Decision Support for Manufacturing System Life Cycle Management
Journal of Advanced Manufacturing Systems, 2004
Previous research has highlighted the role of virtual engineering tools in the development of manufacturing machinery systems. Simulation models created for this purpose can potentially be used to provide support for other tasks, such as operational planning and service and maintenance. This requires that the simulation models can be fed with historic data as well as with snapshot data. Furthermore, the models must be able to communicate with other business software. The paper describes how simulation models can be used for operational production planning and for service & maintenance support. Benefits include a better possibility to verify production plans and the possibility to monitor and service manufacturing machinery from remote locations. Furthermore, the expanded and continuously updated models provide a good tool to study the effect of for instance planned new product introduction in existing manufacturing systems. The paper also presents directions for future research. One ambition is to add AI tools to the system so as to develop a semi-autonomous system for decision support.
An Hybrid Simulation model to support decision making in a manufacturing plant
Wseas Transactions on Systems, 2014
The objective of the following paper is to determine a quantitative approach is generic enough and able to reproduce the logical steps for the construction of tools for decision support systems. The heart of the problem is the use of simulation techniques based on the concepts of System Dynamics. A further innovation is logged in the System Dynamics is to demonstrate how an efficient technique used in decision support systems, not only strategic, but also tactics. The paper will consist of five sections. First we will describe the main characteristics of the DSS and their role in decision-making. In the second section we focus will shift on the simulation, in particular, we highlight the differences between the various techniques and its role within the DSS . In the last few three sections it will be a case study, which will be exposed, as we were able to solve a problem using the System Dynamics. In particular, there will be an in-depth analysis of the problem. In the fourth will turn to an analysis of data and the description of the simulation model. Finally, in the fifth and final section, we discuss how the simulation was carried out and the results thereof, the latter will be analyzed and be put forward ideas for resolving the problem, the simulation will be performed again and will report the results of various scenarios.
2010
Discrete-event simulation (DES) has mainly been used as a production system analysis tool to evaluate new production system concepts, layout and control logic. Recent developments have made DES models feasible for use in the day-to-day operational production and planning of manufacturing facilities. Operative simulation models provide manufacturers with the ability to evaluate the capacity of the system for new orders, unforeseen events such as equipment downtime, and changes in operations. A simulation-based Decision Support System (DSS) can be used to help planners and schedulers organize production more efficiently in the turbulent global manufacturing. This paper presents the challenges for development and the efforts to overcome these challenges for the simulation-based DSS. The major challenges are: 1) data integration 2) automated simulation model creation and updates and 3) the visualization of results for interactive and effective decision making. A recent case study is also presented.
A proposal for a standard framework for simulating and modeling manufacturing systems
Process efficiency is definitively a critical factor for manufacturing enterprises and the literature review clearly shows how researchers and operations managers consider simulation as a useful tool to study and optimize production processes. Nevertheless, even the studies that celebrate the simulation as the best approach for analyzing, designing and improving manufacturing processes, highlight some important limits that prevent the diffusion of simulation tools outside universities and research centers boundaries. The literature review suggested to concentrate on the design of a new modeling framework for simulating manufacturing processes that implements a structure and a working logic much closer to real production systems. This paper presents some key elements for developing a standard framework for simulating and modeling manufacturing systems, showing how a different modeling approach can allow to reproduce the actual dynamics of a generic production process, natively replicating both information flow and physical material flow. Snapshot of a simulation tool, still in development, are presented as well.
Integrating simulation and optimization of manufacturing systems
IEEE Transactions on Systems, Man, and Cybernetics, 2003
This paper presents the ongoing development of a modeling methodology and a tool (the so-called simulation integrated system with modeling and optimization (SISMO) solver) that permits manufacturing systems to be both simulated and optimized according to several improvement strategies. We point out that the different steps of modeling, simulating, and optimizing uses the same integrated formalism and environment. A major point of this methodology and tool is the original decision-making mechanism over a hierarchy of complex discrete systems that model the real world. For the SISMO platform to be validated, we applied it to an actual highly constrained discrete-continuous scheduling problem. This study on a real-life problem has systematically led to improvements.