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SmartWeld: A knowledge-based approach to welding
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NTIS Section
SmartWeid: A Knowledge-Based Approach to Welding Mitchiner, J. L.; Kleban, S. D.; Hess, B. V.; Mahin, K. W.; Messink, D. Sandia National Labs., Albuquerque, NM. Corp. Source Codes: 068123000; 9511100 Sponsor: Department of Energy, Washington, DC. Report No.: SAND-96-1372C; CONF-9606211-2 1996 6p Languages: English Document Type: Conference proceeding Journal Announcement: GRAI9624; ERA9649 Artificial intelligence and manufacturing: a research planning workshop, Albuquerque, NM (United States), 24-26 Jun 1996. Sponsored by Department of Energy, Washington, DC. NTIS Prices: PC A02/MF A01 Country of Publication: United States Contract No.: AC04-94AL85000 SmartWeld is a concurrent engineering system that integrates product design and processing decisions within an electronic desktop engineering environment. It is being developed to provide designers, process engineers, researchers and manufacturing technologists with transparent access to the right process information, process models, process experience and process experts, to realize "right the first time" manufacturing. Empirical understanding along with process models are synthesized within a knowledge-based system to identify robust fabrication procedures based on cost, schedule, and performance. Integration of process simulation tools with design tools enables the designer to assess a number of design and process options on the computer rather than on the manufacturing floor. Task models and generic process models are being embedded within user friendly GUI's to more readily enable the customer to use the SmartWeld system and its software tool set without extensive training. The integrated system architecture under development provides interactive communications and shared application capabilities across a variety of workstation and PC-type platforms either locally or at remote sites. Descriptors: *Computer-Aided Manufacturing; *Welded Joints; Computer Graphics; Computer-Aided Design; Expert Systems; Knowledge Base; Mathematical Models; Mesh Generation; Waste Management; Welding; Meetings Identifiers: EDB/360101; EDB/320303; NTISDE Section Headings: 41B (Manufacturing Technology---Computer Aided Manufacturing (CAM)); 41F (Manufacturing Technology--Joining) Artificial Intelligence Applications in Aircraft Systems (Research rept) Goss, S.; Murray, G. Defence Science and Technology Organisation, Canberra (Australia). Corp. Source Codes: 057314000; 394805 Report No.: DSTO-RR-0071; DODA-AR-008-337 Feb 96 66p
Languages: English Journal Announcement: GRAI9624 NTIS Prices: PC A05/MF A01 Country of Publication: Australia Air Operations Division at the DSTO Aeronautical and Maritime Research Laboratory is developing a capability in the use of Artificial Intelligence (AI), including knowledge based systems technology, in applications related to the operation and support of aircraft systems. A survey of the work program of Air Operations Division was undertaken to identify opportunities offered by advanced computing techniques for the solution of existing research problems. This document describes the findings of the survey. Some of the research opportunities identified have been pursued, and a brief description of progress is provided. Descriptors: *Military aircraft; *Artificial intelligence; *Aeronautical engineering; Mathematical models; Avionics; Research facilities; Problem solving; Surveys; Expert systems; Knowledge based systems; Laboratories Identifiers: *Foreign technology; ADO (Australian defense organization); NTISDODXA Section Headings: 51GE (Aeronautics and Aerodynamics-General); 74GE (Military Sciences--General)
Learning in Networks Buntine, W. L. Research Inst. for Advanced Computer Science, Moffett Field, CA. Corp. Source Codes: 095294000; RR454545 Sponsor: National Aeronautics and Space Administration, Washington, DC. Report No.: NAS 1.26:201052; RIACS-TR-95-08; NASA-CR-201052 1 Apr 95 26p Languages: English Journal Announcement: GRAI9623; STAR3411 NTIS Prices: PC A03/MF A01 Country of Publication: United States Contract No.: NAS2-13721 Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms. Descriptors: *Bayes theorem; *Belief networks; *Computer systems programs; *Machine learning; *Markov chains; Expert systems; Graphs (Charts) Identifiers: NTISNASA Section Headings: 62GE (Computers, Control, and Information Theory--General)
NTIS Section
SmartWeid: A Knowledge-Based Approach to Welding Mitchiner, J. L.; Kleban, S. D.; Hess, B. V.; Mahin, K. W.; Messink, D. Sandia National Labs., Albuquerque, NM. Corp. Source Codes: 068123000; 9511100 Sponsor: Department of Energy, Washington, DC. Report No.: SAND-96-1372C; CONF-9606211-2 1996 6p Languages: English Document Type: Conference proceeding Journal Announcement: GRAI9624; ERA9649 Artificial intelligence and manufacturing: a research planning workshop, Albuquerque, NM (United States), 24-26 Jun 1996. Sponsored by Department of Energy, Washington, DC. NTIS Prices: PC A02/MF A01 Country of Publication: United States Contract No.: AC04-94AL85000 SmartWeld is a concurrent engineering system that integrates product design and processing decisions within an electronic desktop engineering environment. It is being developed to provide designers, process engineers, researchers and manufacturing technologists with transparent access to the right process information, process models, process experience and process experts, to realize "right the first time" manufacturing. Empirical understanding along with process models are synthesized within a knowledge-based system to identify robust fabrication procedures based on cost, schedule, and performance. Integration of process simulation tools with design tools enables the designer to assess a number of design and process options on the computer rather than on the manufacturing floor. Task models and generic process models are being embedded within user friendly GUI's to more readily enable the customer to use the SmartWeld system and its software tool set without extensive training. The integrated system architecture under development provides interactive communications and shared application capabilities across a variety of workstation and PC-type platforms either locally or at remote sites. Descriptors: *Computer-Aided Manufacturing; *Welded Joints; Computer Graphics; Computer-Aided Design; Expert Systems; Knowledge Base; Mathematical Models; Mesh Generation; Waste Management; Welding; Meetings Identifiers: EDB/360101; EDB/320303; NTISDE Section Headings: 41B (Manufacturing Technology---Computer Aided Manufacturing (CAM)); 41F (Manufacturing Technology--Joining) Artificial Intelligence Applications in Aircraft Systems (Research rept) Goss, S.; Murray, G. Defence Science and Technology Organisation, Canberra (Australia). Corp. Source Codes: 057314000; 394805 Report No.: DSTO-RR-0071; DODA-AR-008-337 Feb 96 66p
Languages: English Journal Announcement: GRAI9624 NTIS Prices: PC A05/MF A01 Country of Publication: Australia Air Operations Division at the DSTO Aeronautical and Maritime Research Laboratory is developing a capability in the use of Artificial Intelligence (AI), including knowledge based systems technology, in applications related to the operation and support of aircraft systems. A survey of the work program of Air Operations Division was undertaken to identify opportunities offered by advanced computing techniques for the solution of existing research problems. This document describes the findings of the survey. Some of the research opportunities identified have been pursued, and a brief description of progress is provided. Descriptors: *Military aircraft; *Artificial intelligence; *Aeronautical engineering; Mathematical models; Avionics; Research facilities; Problem solving; Surveys; Expert systems; Knowledge based systems; Laboratories Identifiers: *Foreign technology; ADO (Australian defense organization); NTISDODXA Section Headings: 51GE (Aeronautics and Aerodynamics-General); 74GE (Military Sciences--General)
Learning in Networks Buntine, W. L. Research Inst. for Advanced Computer Science, Moffett Field, CA. Corp. Source Codes: 095294000; RR454545 Sponsor: National Aeronautics and Space Administration, Washington, DC. Report No.: NAS 1.26:201052; RIACS-TR-95-08; NASA-CR-201052 1 Apr 95 26p Languages: English Journal Announcement: GRAI9623; STAR3411 NTIS Prices: PC A03/MF A01 Country of Publication: United States Contract No.: NAS2-13721 Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms. Descriptors: *Bayes theorem; *Belief networks; *Computer systems programs; *Machine learning; *Markov chains; Expert systems; Graphs (Charts) Identifiers: NTISNASA Section Headings: 62GE (Computers, Control, and Information Theory--General)