The rapid design of simulation models using cladistics and template based modelling

The drive towards a more globally competitive market has led to an increase in demand for goods and services on a global scale. As a result of this increase in productivity, production systems are being designed and redesigned at an increased rate and that they are becoming more innovative as they progress with time. The challenge this research attempts to address is how to improve the ability of the UKbased manufacturing industry to make a more effective decision during manufacturing systems design/redesign by adopting simulation techniques as both strategic and operational decision making tools. The aim of this research is to develop a classification scheme based on cladistics and evolutionary analysis and to use this classification in the development of a template based modelling library. The research focused on identifying the existing manufacturing layout types, the various layout configurations that are being used and template based model generation. Some of the major developments of the research conducted were the construction of the manufacturing layout and component based cladograms and the RapidSim generator. A literature review on manufacturing systems layouts revealed the types of system layouts which are most commonly used in the manufacturing sector as well as the component configurations and characteristics which are found within each production systems. This research makes a major contribution by providing a cladistical classification of manufacturing systems layouts, an external interface for model building and development and a set of recommendations, which when adopted may help increase the use of template based simulation modelling. Based on the data analysis carried out, the findings suggest that there is room for the development and implementation of a template based modelling approach to the development of simulation based models. The most important result obtained from the validation of the model was that the time taken to build and run the model decreased significantly by around 65% when compared to the conventional model building process.