| This thesis examines how the developments along two fronts, viz. advancements in microcomputer hardware and software, and the field of Artificial Intelligence (AI), can be taken advantage of by the textile professional.; The AI concept of "systematizing" knowledge for building intelligent systems has been adopted, and a taxonomy for textile problems has been developed.; An increasingly popular sub-discipline of AI is that of expert systems--systems that can "think", "learn", and "act" like human experts in particular disciplines. A framework for building and using such expert systems for quantifiable knowledge bases has been discussed in detail and compared with the more traditional expert systems.; The viability of the expert systems approach to meeting the knowledge management and problem-solving needs of the textile professional is illustrated by the case studies covering a broad spectrum of applications in textile science and engineering. The developed mathematical models, programs, and templates can be used "as is" in practical situations, and within the currently available hardware and software.; The importance of human factors engineering in the context of the rapid proliferation of inexpensive micro-computers has been discussed. A set of guidelines for the design of an intelligent, user-friendly human-computer interface has been proposed. The newer generation of hardware and software incorporate many of these guidelines thus confirming their validity.; Following an analysis of the real-world requirements and limitations, the foundations for a knowledge processing language that integrates the important features of procedural and nonprocedural computer languages have been laid. It is specifically aimed at the class of sophisticated nonprogrammer-users who may have outgrown constraint languages and long for some powerful features of conventional programming languages during the course of their problem-solving activities. The features and the design of this tool have been discussed in detail. |
