SBIR-STTR Award

We propose to design, implement and test a knowledge-based system for the dynamic scheduling of job shops. The task of scheduling a job shop is inherently difficult; included are considerations such as flexibility, profitability, traceability, quality assurance and error detection and correction. The two key components of the proposed system that we plan to investigate in phase I are: (1) selfcorrecting inference mechanism which performs planning based on knowledge of constraints in the domain and does re-planning during plan execution on the basis of new unforseen information that may arise; and (2) a generic representation of knowledge that enables multiple different representations of complex objects (e.g., parts, materials, machines), in order to allow the tracking of objects through the job shop during the execution of a job plan.

We propose to design, implement and test a knowledge-based system for interactive and ........ Operations management of aerospace manufacturing, termed sekom-o, that encompasses the key tasks of planning, scheduling and control of operations. The operations management task is inherently difficult; included are considerations such as flexibility, profitability, traceability, quality assurance and error detection and correction. The key problem is to enable independent domain-specific systems to communicate with each other in order to allow coordination among otherwise separate tasks. Our proposed solution to this problem of communicating expert systems is the establishment of a uniform, canonical representational lsystem, in which all representations and data-structures for every constituent expert system are implemented. This uniform representation is made possible by the identification of representational primitive building blocks which ensure that the relationships between any object or event across more than one domain can be explicitly represented, as well as enabling multiple different representations of complex objects in order to allow the tracking of objects through the manufacturing environment during operations.