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| 005 | 20260818090711.0 | ||
| 008 | 020519s2001 th u m rtt 00| a1eng d | ||
| 035 | _a.b11855009 | ||
| 099 | 9 | _aAIT Thesis no. ISE-01-36 | |
| 100 | 1 | _aKalra, Shilpi | |
| 245 | 1 | 0 | _aDevelopment of a predefined flow decision making software for effective lot disposition of flash memory products |
| 260 |
_aBangkok : _bAsian Institute of Technology, _c2001 |
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| 300 | _a88 p. | ||
| 490 | 1 |
_aThesis ; _vno. ISE-01-36 |
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| 500 | _aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies | ||
| 502 | _aThesis (M.Eng.) - Asian Institute of Technology, 2001 | ||
| 520 | _aOne of the features that will distinguish the future automated factory is the higher level of information processing and data management. The information system used to support the automated factory of the future will become a "knowledge base management system". The decision making process consists of three phases: intelligence, design and choice. Decision Support System(DSS) was recognized as dealing with technologies for representing and processing knowledge in order to facilitate decision making. Key DSS component is its knowledge system which holds representations of descriptive, procedural and reasoning knowledge and its problem processing system which can draw on knowledge representations in the course of solving or recognizing problems that occur in decision making process. The net effect is that a DSS amplifies the decision makers capacity for handling knowledge. In production activities, decisions often need to be made based on certain operating conditions - e.g. number of rejects, or test yield, retest number of units, etc. The decision making procedures lead to desire action by end users. These decisions are based on known data or solutions, and can be guided by the experience of the personnel. However, in actual operating environment, such as manufacturing plant, conditions and decisions are constantly changing and often the extensive number of users who define conditions and decisions and share the same computer system. It is therefore desirable to develop a single interactive computer based system for decision making guidelines for a large variety of operations, task and conditions, which don't require special programming skills to maintain. With this objective in mind, hereby, we have developed a Predefined Flow Decision Making (PFDM) Software for auto decision making using an expert shell. The output of this software will be editable text file. The Auto Decision Making process involves defining conditions and writing them into computer program and let the computer make the decision on the desired actions to take. A common database, containing knowledge, where users can place their inputs which are in the form of conditions and decisions. The database files are compiled (written) in such a manner that the main program can find, retrieve and read them to interact with the end user. When conditions and decisions change, the user will make modifications to the files in the database only, without touching the main program. Here we also use an expert system to pull conditions and their related decisions from common database, and interacts with end user. The executable computer program never needs modification, regardless of change in conditions and decisions in the system. A ll aspects of e-industry require and enable more rapid, flexible and customized responses. By this work we have tried to explore the importance of matching IT efforts with decision making to control production activities in industries where there are variety of products. This can greatly reduce the time required in decision making and hence right decision at right time will surely increase the effectiveness and efficiency of the organization. Product engineers can easily define their decision criteria. It will help in better and easy sharing of knowledge. Above all the automatic decision at the operator level will lead to faster customer responses. This DSS will help product engineers to save 932 hrs a month with 3.5% increase in productivity. The cost of installation is approximately 1100 USO. | ||
| 650 | 1 | 0 | _aDecision support systems |
| 700 | 1 |
_aAfzulpurkar, Nitin V., _eChairperson |
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| 700 | 1 |
_aBatanov, Dentcho N., _eExamination Committee |
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| 700 | 1 |
_aBohez, Erik L.J., _eExamination Committee |
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| 700 | 0 |
_aPichit Saengpongpaew, _eExamination committee |
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| 710 | 2 |
_aAsian Development Bank - Japan, _eScholarship donor |
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| 810 | 2 |
_aAsian Institute of Technology. _tThesis ; _vno. ISE-01-36 |
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| 856 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B08708 |
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