Model‐Based Computing for Design and Control of Reconfigurable Systems

• Published in: The AI magazine Vol. 24; no. 4; pp. 120 - 130
• Main Authors: Fromherz, Markus P. J., Bobrow, Daniel G., Kleer, Johan
• Format: Journal Article
• Language: English
• Published: La Canada American Association for Artificial Intelligence 01.12.2003; John Wiley & Sons, Inc
• Subjects: Artificial intelligence; Computer programming; Control algorithms; Controllers; Design; Design engineering; Designers; Employment; Engineers; Printers; Productivity
• DOI: 10.1609/aimag.v24i4.1735
• ISSN: 0738-4602

Complex electro‐mechanical products, such as high‐end printers and photocopiers, are designed as families, with reusable modules put together in different manufacturable configurations, and the ability to add new modules in the field. The modules are controlled locally by software that must take into account the entire configuration. This poses two problems for the manufacturer. The first is how to make the overall control architecture adapt to, and use productively, the inclusion of particular modules. The second is to decide, at design time, whether a proposed module is a worthwhile addition to the system: will the resulting system perform enough better to outweigh the costs of including the module? This article indicates how the use of qualitative, constraint‐based models provides support for solving both of these problems. This has become an accepted part of the practice of Xerox, and the control software is deployed in high‐end Xerox printers.