04093nas|a2200397 i 4500 20260817163114.0 241198s1986 th uzm rtt 00| a1eng d .b10070746 AIT RSPR no. CS-86-10 Chuan, Karen Lee Tzu An approach to develop an expert system for production planning Bangkok : Asian Institute of Technology, 1986 102 p. Research studies project report ; no. CS-86-10 A research study submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Engineering and Technology Research Studies Project Report (M. Sc.) - Asian Institute of Technology, 1986 The 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. Expert systems (Computer science) Production planning Kanchit Malaivongs, Chairperson Sadananda, Ramakoti, Examination Committee Tabucanon, Mario T., Examination Committee BES Engineering Corporation Taiwan, R.O.C., Scholarship Donor Asian Institute of Technology. Research studies project report ; no. CS-86-10 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B19467 .b10070746 mnait y 240409 2 951012 m a y 3 mnait mnarc 22 40 Barcode : 30050120616981 CREATED : 2012-05-09 RECORD # : i12693157 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050160005061 CREATED : 2016-03-24 RECORD # : i1290885x LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 7410 7410 0 0 0 0 MAIN MAIN mnait 2026-08-17 0 AIT RSPR no. CS-86-10 30050120616981 2026-08-17 16:31:14 3 2026-08-17 22 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT RSPR no. CS-86-10 30050160005061 2026-08-17 16:31:14 2026-08-17 40