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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. ==Overview== 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: * Improved integration. In traditional CAD and industrial systems each application often has its own slightly different model. Having a standardized knowledge model makes integration easier across different systems and applications. * More re-use. A knowledge model facilitates storing and tagging design artifacts so that they can easily be found again and re-used. Also, knowledge models are themselves more re-usable by virtue of using formalism such as IS-A relations (classes and subclasses in the object-oriented paradigm). With subclassing it can be very easy to create new types of artifacts and processes by starting with an existing class and adding a new subclass that inherits all the default properties and behaviors of its parents and then can be adapted as needed. * Better maintenance. Class hierarchies not only facilitate re-use they also facilitate maintenance of systems. By having one definition of a class that is shared by multiple systems, issues of change control and consistency are greatly simplified. * More automation. Expert system rules can capture and automate decision making that is left to human experts with most conventional systems. 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: # Build knowledge models from the ground up using knowledge-based technology # Layer knowledge-based technology on top of existing CAD, simulation, and other engineering applications 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. One of the issues that Simkit faced was a common issue for most early KBE systems developed with this method: The Lisp knowledge-based environments provide very powerful knowledge representation and reasoning capabilities; however, they did so at the cost of massive requirements for memory and processing that stretched the limits of the computers of the time. Simkit could run simulations with thousands of objects and do very sophisticated analysis on those objects. However, industrial simulations often required tens or hundreds of thousands of objects, and Simkit had difficulty scaling up to such levels. The second alternative to developing KBE is illustrated by the CATIA product suite. CATIA started with products for CAD and other traditional industrial engineering applications and added knowledge-based capabilities on to them; for example, their KnowledgeWare module. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Knowledge-based engineering」の詳細全文を読む スポンサード リンク
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