Journal article
E-quality Assessment: Bio Part Inspection Using Intelligent Data Mining
IIE Annual Conference. Proceedings
01 Jan 2011
Abstract
Optimization of design is an important step in acquiring tissue engineering scaffolds with appropriate shape and inner microstructure, which are key features in bio-part fabrication. To date, scaffold porosity is becoming an issue since the porosity percentage is not high due to an improper fabrication process. The traditional inspection procedure utilized the scanning electron microscope is very time consuming and not effective and consequently it is not desirable in current bio industry. In this study, a novel inspection procedure equipped with robotics, machine vision systems and web camera is introduced to characterize the scaffold fabrication. The purpose of this research is using intelligent data mining based on neural networks to perform E-quality control activities particularly focusing on the surface features. The end results of prediction accuracy from the proposed approach are validated and compared with outcomes derived from design of experiment (DOE). The case study represents an empirical use of the intelligent data mining based inspection approach in bio-part fabrication and provides an indication of how to study this problem further and create a path for effective further investigation. [PUBLICATION ABSTRACT]
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Details
- Title
- E-quality Assessment: Bio Part Inspection Using Intelligent Data Mining
- Creators
- Tzu-Liang (Bill TsengAditya ChilukuriPaola GandaraRichard ChiouJohnny HoChun-Che HuangJun Zheng
- 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
- 991019173726004721