{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T11:37:45Z","timestamp":1648813065098},"reference-count":15,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2009,2,27]],"date-time":"2009-02-27T00:00:00Z","timestamp":1235692800000},"content-version":"unspecified","delay-in-days":5689,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[1993,8]]},"abstract":"<jats:p>A number of automated reasoning systems find their basis in process control engineering. These programs are often model-based and use individual frames to represent component functionality. This representation scheme allows the process system to be dynamically monitored and controlled as the reasoning system need only simulate the behavior of the modeled system while comparing its behavior to real-time data. The knowledge acquisition task required for the construction of knowledge bases for these systems is formidable because of the necessity of accurately modeling hundreds of physical devices. We discuss a novel approach to the capture of this component knowledge entitled automated knowledge generation (AKG) that utilizes constraint mechanisms predicated on physical behavior of devices for the propagation of truth through the component model base. A basic objective has been to construct a complete knowledge base for a model-based reasoning system from information that resides in computer-aided design (CAD) databases. If CAD has been used in the design of a process control system, then structural information relating the components will be available and can be utilized for the knowledge acquisition function. Relaxation labeling is the constraint-satisfaction method used to resolve the functionality of the network of components. It is shown that the relaxation algorithm used is superior to simple translation schemes.<\/jats:p>","DOI":"10.1017\/s0890060400000871","type":"journal-article","created":{"date-parts":[[2010,3,31]],"date-time":"2010-03-31T13:47:38Z","timestamp":1270043258000},"page":"181-188","source":"Crossref","is-referenced-by-count":0,"title":["Constraint mechanisms for knowledge acquisition from computer-aided design data"],"prefix":"10.1017","volume":"7","author":[{"given":"Harley R.","family":"Myler","sequence":"first","affiliation":[]},{"given":"Avelino J.","family":"Gonzalez","sequence":"additional","affiliation":[]},{"given":"Massood","family":"Towhidnejad","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2009,2,27]]},"reference":[{"key":"S0890060400000871_ref014","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1987.4309053"},{"key":"S0890060400000871_ref002","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(88)90023-9"},{"key":"S0890060400000871_ref004","unstructured":"Borning A. , Duisberg R. and Freeman-Benson B. 1987. Constraint hierarchies. Proceedings of Object-Oriented Programming Systems, Languages and Applications, pp 48\u201360."},{"key":"S0890060400000871_ref001","first-page":"146","volume-title":"Proceedings of the American Control Conference","author":"Beasley","year":"1986"},{"key":"S0890060400000871_ref003","doi-asserted-by":"publisher","DOI":"10.1145\/357146.357147"},{"key":"S0890060400000871_ref005","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(87)90002-6"},{"key":"S0890060400000871_ref006","volume-title":"Mind over Machine","author":"Dreyfus","year":"1986"},{"key":"S0890060400000871_ref008","doi-asserted-by":"publisher","DOI":"10.1145\/322290.322292"},{"key":"S0890060400000871_ref009","doi-asserted-by":"publisher","DOI":"10.1145\/4221.4225"},{"key":"S0890060400000871_ref012","volume-title":"Constraint Programming Languages: Their Specification and Generation","author":"Leler","year":"1988"},{"key":"S0890060400000871_ref010","first-page":"337","article-title":"Identification of unconstrained item descriptions using string-match heuristics","volume":"4","author":"Gonzalez","year":"1991","journal-title":"International Journal of Expert Systems"},{"key":"S0890060400000871_ref011","unstructured":"Kladke R. 1989. A mega-heuristic approach to the problem of component identification in automated knowledge generation. Master\u2019s Thesis, University of Central Florida, Orlando, FL."},{"key":"S0890060400000871_ref013","first-page":"10","article-title":"Automated knowledge generation from incomplete CAD data: research results","volume":"2","author":"Myler","year":"1989","journal-title":"Proceedings of the Second Florida AI Research Symposium"},{"key":"S0890060400000871_ref015","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(80)90032-6"},{"key":"S0890060400000871_ref007","first-page":"1","article-title":"A knowledge based expert system for propellant system monitoring at the Kennedy Space Center","volume":"22","author":"Jamieson","year":"1985","journal-title":"Proceedings of the 22nd Space Congress"}],"container-title":["Artificial Intelligence for Engineering Design, Analysis and Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0890060400000871","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,15]],"date-time":"2019-05-15T22:17:32Z","timestamp":1557958652000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0890060400000871\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1993,8]]},"references-count":15,"journal-issue":{"issue":"3","published-print":{"date-parts":[[1993,8]]}},"alternative-id":["S0890060400000871"],"URL":"https:\/\/doi.org\/10.1017\/s0890060400000871","relation":{},"ISSN":["0890-0604","1469-1760"],"issn-type":[{"value":"0890-0604","type":"print"},{"value":"1469-1760","type":"electronic"}],"subject":[],"published":{"date-parts":[[1993,8]]}}}