A rule-based reasoning decision support system for AS-532 cougar helicopters' maintenance personnel

Abstract

Improvements in the aviation technologies have made the aircrafts more reliable, more capable in terms of operational necessities and as a result more technological. Today, Turkish Army Aviation units possess helicopters that are equipped with the technologically up-to-date equipments. Those new generation helicopters brought their advantages in terms of performance, speed, and reliability as well as the disadvantages in terms of maintenance load, expensive parts and required deep system knowledge. At this point, there is a trade off that takes place between the development and the system integration and maintenance necessities of these ultimate equipments. Helicopter systems turn out to be more interactive. Those developments make it easier to fly for the user pilots, but more difficult to perform the maintenance necessities for the maintenance personnel. New maintenance necessities of the developed equipments and interactive systems make it more difficult to keep the helicopter fleets flying and operational. Furthermore this situation increases the need for the domain experts. Number of unexpected failures and the required time for fault isolation are increasing by the acquisitions of developed helicopters. Acquired experience is an important reference for the maintenance personnel in solving the problems as well as the technical documents of the helicopters. In this study, a decision support system in rule-based reasoning is formed in order to help AS-532 COUGAR helicopters’ maintenance personnel. Extraordinary failures, their possible causes, warning to users and recommended solution procedures are presented in the design of “case”. Users can reach to these cases by following the failure related attribute-value pairs. With the help of this decision support system, it will be possible to share the expertise of the COUGAR experts with the inexperienced personnel. As a result, the percentage of true “fault identification” will increase and required time for fault isolation will decrease. This expertise can also be used in training procedures.