Fault tolerance in supervisory control systems: a knowledge-based approach

Fault tolerance in computerized systems involved in production has become an ever more important requirement. Existing fault tolerance approaches, wherever used, deal mainly with hardware faults. Nevertheless, the vast majority of contemporary system failures are software related. This paper introduces a knowledge-based approach to handling software related faults occurring in supervisory control systems. These systems are event driven and use data, stored in complex databases, to react to events coming from different kinds of devices by identifying, scheduling, initiating and monitoring operations. Failure of part of the supervisory control system's software to behave rationally when unexpected events occur is called an application fault. The approach introduced in this paper is based on a supervisory control system reference model which reveals the set of all possible application faults together with the major functions of the recovery processes associated with each fault, and leads to a high-level knowledge-based system architecture capable of handling every fault-related condition. This system is called PROFIT (Intelligent PROduction systems Fault Tolerance) and consists of three main components: the fault diagnosis module, the instant fault correction module and the learning module, co-ordinated by a PROFIT meta-level module. The prototype version of PROFIT is analysed and the development as well as the run-time environment that prove the applicability and effectiveness of the system are presented.