I believe that CBR has already been incorporated into CAD
software already since the eighties. I have seen my engineer
friend using AutoCAD from AutoDesk for retrieving similar design patterns that has been stored in the database. I am no expert in AutoCAD but the user specify design attributes and then AutoCAD retrieves the
closest match or similar match (not exact match as symbolic rules like JESS) of any design that is close to the desired target attributes.
Other engineering tools such as Pro-Engineer are reported to have similar capability as that of AutoCAD (search capability for similar designs from the database).
I attended the international CBR workshop held at University of Auckland, New Zealand here on the 12th to 14th January, 2003 and it
was amazing the number of areas that CBR can be applied. The applications ranges from decision tool support, Customer Relation Management (CRM), voice-print identification (analysis of similar voice signals), Chemical identification , to data mining and many many more. Research in Hybrids CBR & other technologies are moving at a very fast pace. Elsevier publishers have bounded a print book for this workshop.
I saw presentation in Soft-Computing techniques such as Fuzzy-Logic, Artificial Neural Network (ANN),Bayesian Belief Network (BBN), Support Vector Machines (SVM), Rough Sets (RS), Evolutionary Computation (EC), Memetic which is combined with CBR.
The cutting edge of expert systems comes from combining JESS with Soft-Computing methods. One thing I have noticed from AutoCAD that if the expert systems of recommending patterns to the engineer have been using Symbolic rules like CLIPS or JESS then it would not be useful at all. The user will specify attributes for a design pattern then the system will either search for a MATCH or NO_MATCH of any previously stored design. With CBR, it does not have to match exactly, but a similar match to some degree all is required. The closest match design
can be retrieved for the user can be adapt by the user and then stored
as a new knowledge. JESS has advantages compared to other rules engine is that it has already combined well with FuzzyJ (FuzzyJess). It is easier to incorporate other soft-computing techniques using FuzzyJ that can work well with JESS. The is the established practice of Soft-Computing hybrids (Neuro-Fuzzy, Fuzzy-Bayesian, Neuro-Genetics, Rough Sets-Bayesian and so on). A JESS rule based systems (JESS plus Soft-Computing) that is self-learning would be awesome. There was one presentation for this sort of CBR + Soft-Computing hybrids at the Auckland CBR-2003 workshop.
Jason Morris wrote:
Hi Rich,
Hybrid (case-based/rule-based) systems are an absolutely fascinating concept, and I have been wondering about their implications and possibilities for some time also.
My original interest in expert systems came by way of involvement in developing online performance-support tools for mid-range, computer-aided design software. My though was: Why can't CAD software really help an engineer do "engineering" while he or she is creating geometry. Right now, CAD tools are reaching a feature-functionality parity where they basically do all the same things inside the same performance envelope. I was looking for innovative product differentiators, and I saw an opportunity to add real design intelligence to the tools.
As an example, picture a CAD tool that could:
[] Interactively and in real-time monitor your geometry creation and point out potential stress concentrations, point out violations of ASME or company standards, or other conflicts with other design constraints not related to geometry.
[] Apply "design patterns" from existing designs or "best-practices" (use cases), or compare geometry creation intent to standard design-for-manufacturing (DFM) or design-for-assembly (DFA) principles to catch problems before they occur, or deduce a best design approach given company standards and methods (use rules).
Does this sound too far fetched? I didn't think so then... and with tools like Jess and FuzzyJess, I certainly don't now. Is it a big undertaking? Without question! I have no illusions about how huge this would be to do.
Management will always say, "That's cool, but what's the business case? What customer problem are you trying to solve?" I think that one could claim that such a system, by folding actual engineering knowledge into the geometry creation process and leveraging accumulated corporate knowledge, would:
* Reduce time-to-market by collapsing the overall time to design and prototype a viable system (promote design reuse). * Reduce manufacturing and assembly costs by catching conflicts before they hit the production floor. * Push risky processes further up the development process where they can be caught and eliminated quickly before they cause problems down-stream.
Given the esoteric and very non-conventional nature of the proposal, convincing management about the ROI enough that it ever got funded as a project was impossible. I hate to accuse management of being narrow-minded, but as in most industries, there are long-established ways of doing things in CAD, and the powers that be were (and are) loath to deviate from following them.
So, at the time, I didn't have the programming or knowledge engineering experience to even prototype such a system, but now I do. I'd give my eye-teeth to work on such a project! I'd be very interested to hear your further thoughts as well as anyone else's on the general hybrid subject.
Q. What companies are applying hybrid systems to mechanical design? Does anyone have some examples?
BTW - thanks for all your replies on other threads so far.
-JM ------ Jason Morris Morris Technical Solutions [EMAIL PROTECTED] www.morristechnicalsolutions.com fax/phone: 503.692.1088 -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Rich Halsey Sent: Friday, February 27, 2004 8:51 AM To: [EMAIL PROTECTED] Subject: JESS: Case Based Reasoning with Rules
Hi All,
I have been thinking about Case Based Reasoning (CBR) and it would seem that if a rule-based system could (1) determine which objects it was matching on, (2) use Java reflection to list the object methods used for the predicates, and (3) retrieve within some repository all the objects that fit (1) and (2) and assert them into working memory, then CBR would be a natural extension of a rule-based system.
Any thoughts ??
Rich Halsey
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