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035 _a.b10070746
099 9 _aAIT RSPR no. CS-86-10
100 1 _aChuan, Karen Lee Tzu
245 1 3 _aAn approach to develop an expert system for production planning
260 _aBangkok :
_bAsian Institute of Technology,
_c1986
300 _a102 p.
490 1 _aResearch studies project report ;
_vno. CS-86-10
500 _aA research study submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Engineering and Technology
502 _aResearch Studies Project Report (M. Sc.) - Asian Institute of Technology, 1986
520 _aThe ability to run a manufacturing business successfully relies on effective production planning. Production planning involves knowledge and decision making on the development of master schedules, finished products inventory planning, material requirement planning, equipment and machine utilization, manpower allocation and inventory investment . Our approach to develop an expert system for production planning combines the basic concept of developing a computerized information system with the important task of knowledge acquisition in building an expert system. In our approach the development of an expert system for production planning is presented in five phases. Phase 1 is requirement analysis in which the major tasks are subdivided in to pre-knowledge-acquisition tasks and knowledge-acquisition tasks. Pre-knowledge-acquisition tasks include three activities : state objectives of t h e expert system, study the production system, and flowchart the production system. Knowledge-acquisition tasks include seven activities select a domain expert, choose a specific problem area, identify characteristics of problem, gather facts and rules used in problem solving, organize knowledge on an initial paper knowledge base, discover basic concept to represent knowledge and produce a final paper knowledge base. Phase 2 is expert system development tool evaluation. A set of factors must be considered in choo sing an appropriate expert -system- building tool. These include specialty, testing, accessibility, development speed and tool features. Phase 3 is design of rules. In this phase the knowledge data for production planning can be represented graphically as a decision path tree. Phase 4 is implementation in which the knowledge base for production planning is created via the selected expert system- building tool and Phase 5 is testing which involves informal and formal testing; the system characteristics to be tested include the quality of the system's decision and advice, the correct ness of the reasoning techniques used , the quality of human-computer interaction a n d the system' s efficiency. The developed approach is used in building an expert system for a selected paint manufacturing comp any in the case study.
650 0 _aExpert systems (Computer science)
650 0 _aProduction planning
700 0 _aKanchit Malaivongs,
_eChairperson
700 1 _aSadananda, Ramakoti,
_eExamination Committee
700 1 _aTabucanon, Mario T.,
_eExamination Committee
710 2 _aBES Engineering Corporation Taiwan, R.O.C.,
_eScholarship Donor
810 2 _aAsian Institute of Technology.
_tResearch studies project report ;
_vno. CS-86-10
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B19467
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