DSSL II: A Powerful Tool for Modelling and Analysing Complex Systems
International Journal of Operations & Production Management
Article publication date: 1 April 1991
Sound design, planning and monitoring is critical to the operational and financial success of today′s sophisticated manufacturing and non‐manufacturing systems. Owing to their increasing complexity, discrete‐event simulation is becoming the most acceptable tool to aid planning the design and management of production and operations. This growing acceptance has led to the development of many simulators. Two fundamental criteria enable assessment of the suitability of these simulations in complex environments. First, the sophistication of their modelling capability to handle a wide range of problematic situations and second, ease of use. These two considerations, however, tend to conflict; resulting in flexible simulators being difficult to use and vice versa. DSSL II is an advanced simulation methodology with a well defined and user‐friendly modelling strategy. It has been devised to offer a versatile approach in modelling today′s sophisticated systems and policies. Features incorporated include a schematic modelling concept to represent the operational logic of systems, a set of software modules and an associated logical structure. Using the logical structure, the modules are combined to transform the concept of the schematic model into a representative computer program. Using DSSL II, models of manufacturing and non‐manufacturing systems are constructed readily to provide accurate and trustworthy answers to essential “what‐if” questions posed by decision makers, to determine which out of several scenarios would be the most appropriate. The purpose of this paper is to present the concepts and techniques employed by DSSL II. A simple case study and an example of a real industrial application are given in order to demonstrate its features and potential.
Chaharbaghi, K. (1991), "DSSL II: A Powerful Tool for Modelling and Analysing Complex Systems", International Journal of Operations & Production Management, Vol. 11 No. 4, pp. 44-88. https://doi.org/10.1108/01443579110006171
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