Chapter 34. Applicability of Quicksettm Injection Molding to Intelligent Processing of Ceramics

  1. John B. Wachtman Jr
  1. Richard W. Adams,
  2. William B. Householder and
  3. Cathryn A. Sundback

Published Online: 26 MAR 2008

DOI: 10.1002/9780470313848.ch34

Proceedings of the 15th Annual Conference on Composites and Advanced Ceramic Materials, Part 2 of 2: Ceramic Engineering and Science Proceedings, Volume 12, Issue 9/10

Proceedings of the 15th Annual Conference on Composites and Advanced Ceramic Materials, Part 2 of 2: Ceramic Engineering and Science Proceedings, Volume 12, Issue 9/10

How to Cite

Adams, R. W., Householder, W. B. and Sundback, C. A. (1991) Applicability of Quicksettm Injection Molding to Intelligent Processing of Ceramics, in Proceedings of the 15th Annual Conference on Composites and Advanced Ceramic Materials, Part 2 of 2: Ceramic Engineering and Science Proceedings, Volume 12, Issue 9/10 (ed J. B. Wachtman), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470313848.ch34

Author Information

  1. Ceramics Process Systems Corporation Milford, MA 01757

Publication History

  1. Published Online: 26 MAR 2008
  2. Published Print: 1 JAN 1991

ISBN Information

Print ISBN: 9780470375105

Online ISBN: 9780470313848

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Keywords:

  • ceramics;
  • technology;
  • environment;
  • viscosities;
  • microstructures

Summary

The Quicksettm injection molding process is a new approach to the forming of net/near-net shape ceramic components. The Quicksettm process was developed to eliminate binder-related problems associated with thermoplastic or gel injection molding systems, which have traditionally been used to form complex-shape ceramics. Quicksettm has a demonstrated capability for shape forming and superior materials properties. Intelligent processing promises improved manufacturing efficiency and shortened product development cycle times. Coupling Quicksettm with intelligent processing produces a controllable and reproducible process for advanced ceramics. Process flow, process variables, and in situ process/product status sensors are described in relation to the intelligent processing goal.