A Hierarchical Expert System for Process Planning and Material Selection

공정계획과 재료선정의 동시적 해결을 위한 계층구조 전문가시스템

  • 권순범 (단국대학교 경영정보학과) ;
  • 이영봉 (국방과학연구소 책임연구원) ;
  • 이재규 (한국과학기술원 테크노경영대학원)
  • Published : 2000.12.01

Abstract

Process planning (selection and ordering of processes) and material selection for product manufacturing are two key things determined before taking full-scale manufacturing. Knowledge on product design. material characteristics, processes, time and cost all-together are mutually related and should be considered concurrently. Due to the complexity of problem, human experts have got only one of the feasilbe solutions with their field knowledge and experiences. We propose a hierarchical expert system framework of knowledge representation and reasoning in order to overcome the complexity. Manufacturing processes have inherently hierarchical relationships, from top level processes to bottom level operation processes. Process plan of one level is posted in process blackboard and used for lower level process planning. Process information on blackboard is also used to adjust the process plan in order to resolve the dead-end or inconsistency situation during reasoning. Decision variables for process, material, tool, time and cost are represented as object frames, and their relationships are represented as constraints and rules. Constraints are for relationship among variables such as compatibility, numerical inequality etc. Rules are for causal relationships among variables to reflect human expert\`s knowledge such as process precedence. CRSP(Constraint and Rule Satisfaction Problem) approach is adopted in order to obtain solution to satisfy both constraints and rules. The trade-off procedure gives user chances to see the impact of change of important variables such as material, cost, time and helps to determine the preferred solution. We developed the prototype system using visual C++ MFC, UNIK, and UNlK-CRSP on PC.

Keywords

References

  1. Advanced in Engineering Software v.16 Hyper Q/Plastics:An Intelligent Design Aid for Plastic Material Selection Beiter K.;S. Krizan;K. Ishii
  2. 2nd Int'l Conf. on Data and Knowledge Sstem for Manufacturing and Engineering An Exper system for the Selection of a Composite Material Bergamaschi S.;G. Gombarda;L. Piancastelli;C. Satori
  3. Cost Engineering v.33 no.5 Material-Process Selection Methodology: Design for Manufacturing and Cost using Logic Programming Bock L.
  4. Knowledge-based Systems v.4 no.2 Knowledge-based System for Material Selection for Design with New Materials Bullinger H. S.;J. Warscht;D. Fischer
  5. Manufacturing Review v.3 no.1 Least Cost Tolerance Allocation for Mechanical Assemblide with Automated Process Selection Chase K. W.;Greenwood W. H.
  6. 3rd Conf. of Annual ES in Government Optimization Material Selections for Performance and Supportability with an Exper System Damody M.;G. Chadwick
  7. Computers Industrial Engineering v.30 no.1 Manufacturing process Planning in a Concurrent Design and Manufactureing Environment Dong Jian;Hamid R. Parsaei;Herman R. Leep
  8. Concurrent Eng.:Research and Application v.3 no.2 Concurrent Materials and Manufacturing Process Selection in Design Fuction Deployment Evbuomwan N. F. O.;S. Sivaloganathan;A. Jebb
  9. Expert Systems with Application: An International Journal v.9 no.1 ES*: An Exper Systems Development Planner Using A Constraint and Fule Based Approach Lee, Jae Kyu;Suhn B. Kwon
  10. Proceeding of Korea IE Fall Conference Concurrent Selection of Materials and Manufacturing Processes using Constraint-Rule Satisfaction Approach Lee Y. B.;Jae Kyu Lee;Suhn B. Kwon
  11. Int. J. of Advanced Manufacturing Technology v.6 no.1 Algorithms of Computer Aided Generative Process Planning Prabhu P.;Wang H. P.
  12. Computers Industrial Engineering v.33 no.3 A CAPP Expert System for rotational Components Younis M. A.;Abdel Wahab
  13. J. of Intelligent Manufacturing v.4 Computer Aided Design for Manufacturing Processes Selection yu Jyh-Cheng;Steven Krizam;Koshuke Ishii
  14. Int. J. of Advanced Manufacturing Technology A Feature-Recognition Knowledge Base for Process planning of Rotational Mechanical Components Zhang K. F.;Wright A. J.