Knowledge-based systems Essay

Published: 2020-01-18 00:01:21
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We tabulated the required sample size n and the corresponding critical acceptance value [c. sub. 0] for various [alpha]-risks, [beta]-risks, and the capability requirements AQL, LTPD. The results obtained in this paper are useful to the practitioners in making reliable decisions. For illustrative purpose, we demonstrated the proposed method by presenting a case study on liquid-crystal module (LCM) manufacturing process to evaluate the process performance.

Here could be many decision problems in which decision-makers have different interests in reaching certain objectives. A useful decision support system which has interesting characteristics is presented here: it allows each decision-maker to learn individually how to move around the efficient frontier and, interact anonymously, in a progressive manner, with the other members of the group to impel the process toward his interests, or to back down before the other decision-makers interests, to end up in a balanced decision that satisfies all the members of the group.

(Sethi, & King 2001) The system presented here has the role of an impartial and trustworthy facilitator that enables the group to reach their objectives in an appropriated time, manages it, questions it and makes proposals. The system can rapidly synthesize information and judgments and effectively reflect back the tentative outcomes to decision-makers. It generates understanding, learning and creativity. (Edwards 2004)

This process can drive certain members of the group to strongly bias the decisions towards their own interests, by proposing solutions that exceed their goals so that in a negotiation process they can diminish their aspirations to reach their individual true goals. In the proposed methodology several options were included that diminish the vulnerability of the process to radical proposals. These options induce the decision-makers to express their real preferences and not those that would allow them to manipulate the decision.

The proposed methodology allows autonomy and privacy in the decisions of each member of the group. It improves the participation of all decision-makers and avoids pressures by other members. It allows that decision-makers have different importance within the process, and it also includes a weighting system that can be defined by a consultative procedure. (Tan, & Benbasat 2003)


Adelman, L. (2001). Handbook for evaluating knowledge-based systems: Norwell, MA: Kluwer. Anderson, E. E. , & Chen, Y. (2006) Microcomputer software evaluation: An econometric model. Decision Support Systems. 19 (2), 75-92. Adelman, L. (2005). User and R&D specialist evaluation of decision support systems: IEEE Transactions on Systems, Man, and Cybernetics. (SMC-15)2, 334-342. Balasubramanian, P. (1999) Managing process knowledge for decision support: Decision Support Systems. 27 (1-2), 145-162.

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