Knowledge support for problem-solving in a production process: A hybrid of knowledge discovery and case-based reasoning

Liu, Duen‐Ren; Ke, Chih-Kun

doi:10.1016/j.eswa.2006.04.026

Cited by 57 publications

(19 citation statements)

References 25 publications

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“…Memon, Lu and Hussain [23] used a semantic de-biased associations (SDA) model to refine human cognition by reducing cognition biases for ill-structured decision making. Liu and Ke [27] showed a knowledge support approach for problem solving through knowledge discovery and case-based reasoning, where knowledge discovery was employed to extract key concepts of situation and actions and case-based reasoning was adopted to identify similar situations and the action. Goodea and Beckmann [28] investigated the relationships between structural knowledge, control performance and fluid intelligence in a complex problem solving (CPS) task, and indicated that CPS needs to combine domain knowledge and abstract thinking skills.…”

Section: Related Workmentioning

confidence: 99%

Human-centric computational knowledge environment for complex or ill-structured problem solving

Wang

Zhang

Wang

et al. 2014

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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A complex or ill-structured problem cannot be solved only replying on computer since they require human's nonlinear thinking and even innovation. In this paper, taking respective advantages of computer and human, we propose a novel computational knowledge environment (CKE) where human is able to cognize tacit and new knowledge for complex or ill-structured problem solving, through fusing potential knowledge discovered from the collected information data supported by computer. Following the CKE framework, we develop a creativity technique called InnoSpider which greatly support human's perception, intuition, reasoning and cognition for quick decision making. A case study have verified the effectiveness of CKE, and have indicated InnoSpider can drive human to make high-quality decisions in a shorter time.

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Section: Related Workmentioning

confidence: 99%

Human-centric computational knowledge environment for complex or ill-structured problem solving

Wang

Zhang

Wang

et al. 2014

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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“…Chen, Tseng, and Wang (2005) proposed the Root-cause Machine Identifier (RMI) method using the technique of association rule mining for analyzing correlations between combinations of machines and the defective products. Liu and Ke (2007) adopted the technique of association rule to discover decision making and dependency knowledge on a production line. The discovered situation/action profiles and knowledge patterns are used to construct a knowledge support network, which forms the basis of support for solving problems on a production line.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of an intelligent quality management system using fuzzy association rules

Lau

Chu

et al. 2009

Expert Systems with Applications

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“…However, Liao (2000) and Liu and Ke (2007) argued that there are some considerations in integrating CBR into the architecture of DSS to obtain appropriate learning abilities for future problem solving.…”

Section: Outbound Operations In Warehousesmentioning

confidence: 99%

A decision support system to facilitate warehouse order fulfillment in cross‐border supply chain

Lam

Choy

Chung

2011

Journal of Manufacturing Technology Management

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2002),"Linking warehouse complexity to warehouse planning and control structure: An exploratory study of the use of warehouse management information systems"If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to provide a decision support system (DSS) to enhance the performance of cross-border supply chain, the goal of which is to improve order planning and fulfill customer orders within the warehouse. Design/methodology/approach -An intelligent DSS, namely order picking planning system (OPPS) with the adoption of case-based reasoning, is proposed to support managers in making appropriate order fulfilling decisions when an order involves cross-border activities. Similar cases in the past are retrieved and adapted in reference to the new order. A case study is then conducted to illustrate the feasibility and effectiveness of the system. Findings -Recommendations are given to replace the objective decision-making process in cross-border supply chain with the help of the DSS. The warehouse order planning time has been reduced and useful information from past order records can be applied to solve new problems. Originality/value -With the increasing demand for material sourcing across different places, cross-border supply chain has raised the concern for manufacturers to seek lower material and rental costs. The focus on warehouse operations can increase efficiency in order delivery by considering cross-border requirements.

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Knowledge support for problem-solving in a production process: A hybrid of knowledge discovery and case-based reasoning

Cited by 57 publications

References 25 publications

Human-centric computational knowledge environment for complex or ill-structured problem solving

Human-centric computational knowledge environment for complex or ill-structured problem solving

Development of an intelligent quality management system using fuzzy association rules

A decision support system to facilitate warehouse order fulfillment in cross‐border supply chain

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