Knowledge-based engineering

Knowledge-based engineering (KBE) is the application of knowledge-based systems technology to the domain of manufacturing design and production. The design process is inherently a knowledge-intensive activity, so a great deal of the emphasis for KBE is on the use of knowledge-based technology to support computer-aided design (CAD) however knowledge-based techniques (e.g. knowledge management) can be applied to the entire product lifecycle.

The CAD domain has always been an early adopter of software-engineering techniques used in knowledge-based systems, such as object-orientation and rules. Knowledge-based engineering integrates these technologies with CAD and other traditional engineering software tools.

Benefits of KBE include improved collaboration of the design team due to knowledge management, improved re-use of design artifacts, and automation of major parts of the product lifecycle.

KBE is essentially engineering on the basis of knowledge models. A knowledge model uses knowledge representation to represent the artifacts of the design process (as well as the process itself) rather than or in addition to conventional programming and database techniques.

The advantages to using knowledge representation to model industrial engineering tasks and artifacts are:

KBE can have a wide scope that covers the full range of activities related to Product Lifecycle Management and Multidisciplinary design optimization. KBE's scope includes design, analysis (computer-aided engineering – CAE), manufacturing, and support. In this inclusive role, KBE has to cover a large multi-disciplinary role related to many computer-aided technologies (CAx).

There are two primary ways that KBE can be implemented:

An early example of the first approach was the Simkit tool developed by Intellicorp in the 1980s. Simkit was developed on top of Intellicorp's Knowledge Engineering Environment (KEE). KEE was a very powerful knowledge-based systems development environment. KEE started on Lisp and added frames, objects, and rules, as well as powerful additional tools, such as hypothetical reasoning and truth maintenance. Simkit added stochastic simulation capabilities to the KEE environment. These capabilities included an event model, random distribution generators, simulation visualization, and more. The Simkit tool was an early example of KBE. It could define a simulation in terms of class models and rules and then run the simulation as a conventional simulation would. Along the way, the simulation could continue to invoke rules, demons, and object methods, providing the potential for much richer simulation as well as analysis than conventional simulation tools.

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