Traditional simulation tools, such as simulators and simulation languages do not support intelligent simulation output analysis and offer little - or no - features to model intelligence within a system. However, in a modern manufacturing environment we often find ourselves facing high flexibility requirements and the need for quick response. We find an increasing number of artificial Intelligence (AI) applications on the shop floor and the need to figure out what is going on in our system - now, not later.
Simulation is one tool which is useful to analyze manufacturing systems and make decisions based on the findings. Thus, it is desirable to be able to represent the intelligence we find on the shop floor in our simulation model, as well as an automated output analysis in order to speed up the decision making process.
This paper describes the conceptual design and implementation of an AI architecture with the aim to offer a platform where both aspects, representation of intelligence in the system and outside the system (output analysis) can be performed. The architecture is based on Wang's extension (1995) of the simulation environment by Beaumariage (1990) which is implemented in an object-oriented environment. The object-oriented environment also offers an excellent means for implementing the Al architecture. To verify its usefulness two areas of application - priority sequencing at servers and material release - were implemented and several case studies carried out. / Graduation date: 1997
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33960 |
| Date | 05 June 1996 |
| Creators | Kaiser, Ren�� |
| Contributors | Beaumariage, Terrence G. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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