Journal article
An Agent-Based Approach to Enhance Bio-Manufacturing Quality Control Using Data Mining
IIE Annual Conference. Proceedings
01 Jan 2010
Abstract
Quality Control (QC) is a process employed to ensure a certain level of quality in a product or service. One of the techniques in QC is to predict the product quality based on the product features. However, traditional QC techniques have faced some drawbacks such as heavily depending on the collection and analysis of data and frequently dealing with uncertainty processing. In order to improve the effectiveness during a QC process, an agent-based hybrid approach incorporated with data mining techniques such as rough set theory (RST) is proposed in this paper. Under the agent-based framework, each agent is able to perform one or more functionality during the entire QC process. Based on empirical case study in bio-manufacturing, the proposed solution approach provides a great promise in QC processes. [PUBLICATION ABSTRACT]
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Details
- Title
- An Agent-Based Approach to Enhance Bio-Manufacturing Quality Control Using Data Mining
- Creators
- Tzu-Liang (Bill) TsengRichard ChiouChun-Che HuangJohnny Ho
- Publication Details
- IIE Annual Conference. Proceedings
- Conference
- IIE Annual Conference
- Publisher
- Institute of Industrial and Systems Engineers (IISE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Engineering Leadership and Society/Engineering Technology
- Identifiers
- 991019174559104721