FDAS: architecture and implementation

Abstract

: FDAS (Fabric Defects Analysis System) is a knowledge-based system (KBS) for diagnosing defects in woven textile structures. The following major issues were considered in the design of FDAS: (1) range of applications; (2) user profiles; (3) response time requirements; (4) modularity and (5) ease of system modification and enhancements. Knowledge about defects is represented in FDAS using a hierarchy of classes, with the slots representing defect attributes, and forward chaining rules. The inferencing process is controlled by slots of another distinct class hierarchy. Inference is made more efficient by hierarchical classification of the defects with pruning. The agenda (i.e. ordered set of hypotheses) is dynamically reset using actions attached to rules. The diagnosis information—information about the causes of the defects and remedial actions to be taken—is kept separate from the rules in the knowledge base. The user interface part of the system is also independent of the knowledge base, which facilitates easier tailoring of the system to meet the needs of different users. The user interaction with FDAS is menu-based and has been designed to minimize cognitive load on the user. FDAS has been extensively evaluated by in-house individuals who are experts in the task of fabric defects analysis. It has also been demonstrated to experts from the industry and is ready for field tests.