Cabin Refurbishing Supported by Knowledge Based Engineering Software
Author: Bianca Szász
Master Thesis
Abstract
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.