Cabin Refurbishing Supported by Knowledge Based Engineering Software

Author: Bianca Szász

Master Thesis


The cabin related activities, especially refurbishing, are of interest in the present economical context. Airlines need to convert their fleet once the requirement change. A great number of configuration parameters are derived from the requirements (an example of such a requirement based parameter is the position of each cabin item, respecting the regulatory specifications). All these parameters need to be combined within the overall cabin layout and need to be optimized. A virtual medium sized engineering office is considered, having a Design Organizational Approval (DOA) for performing certified cabin conversions. In order to cope with the challenges coming from airliners or from VIP customers, engineering offices today have to make use of up to date software solutions based on Artificial Intelligence. Artificial Intelligence (AI) is "the study and design of intelligent agents", where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. Such software systems allow the isolation of the knowledge behind a design problem and then run the problem solving component. This concept is especially required in cabin configuration. The thesis investigates the use of a Knowledge Based Engineering (KBE) approach applied to a configuration system for aircraft cabins. The KBE approach is tested by using the Pacelab Cabin software. The regulatory specifications are implemented into the program by using the available rules engine of the software. The rules engine is then used to check the consistency of the cabin build-up in the program. If the task is about refurbishing, consistently replacing and updating of cabin items is likewise checked by rules. The paper summarizes the potential of using AI/KBE based configuration systems in practical cabin refurbishing.