Development of a Knowledge-Based Engineering Framework for Modeling Aircraft Production

Abstract

Production modeling and cost estimation are among the main drivers in contemporary approaches to design aircraft and aircraft components. However, the existing methodologies presented in academia to evaluate these disciplines are not widely used in the industry because of (a) black-box behavior of the current production modeling systems, (b) lack of connection between the production modeling systems and the design process, (c) elevated cost and time needed to implement the methods, (d) confidentiality of production information, and (e) resistance to change the working methods. The research presented in this paper proposes a methodology that aims to overcome these limitations by combining knowledge-based engineering with semantic web technologies in the modeling of aircraft production processes. The methodology is realized by a generic, flexible, adaptable and reusable framework for modeling production, which can evaluate the influence of different production concepts, to quantify the interactions between production processes and aircraft design and to conduct studies of performance, and production costs.

Model‐based Framework for Data and Knowledge‐Driven Systems Architecting Demonstrated on a Hydrogen‐Powered Concept Aircraft

“…Based on automating repetitive and routine tasks, this approach is typically associated with an increased development speed (Page Risueño et al, 2019). KBE enables a clarified, rationalized, and less-biased design space exploration (Verhagen et al, 2012).…”

“…Advantages and challenges of KBE. Besides an increased development speed based on automating tasks, KBE is characterized by higher efficiencies, less iterations, and improved interdisciplinary collaboration (Page Risueño et al, 2019). Using KBE, an engineer has more time to focus on creative design tasks during conceptual design (van der Laan, 2008).…”

“…However, since knowledge is often unstructured, formalizing knowledge is a time consuming process reasonable only for systems with significant uncertainty, complexity, and long development times (Verhagen et al, 2012), which all apply to the process of aircraft conceptual design. To ensure ongoing benefits of KBE, the formalized knowledge must be updated regularly creating additional workloads (Page Risueño et al, 2019). In total, KBE seems suitable for knowledge-based systems architecting.…”

“…Due to demographics of western societies, retiring of experts and lack of young engineers is a challenge for knowledge management. To prevent that insights about past developments are lost and that new developments start from scratch, knowledge needs to be organized, formalized, managed, and made accessible for reuse (Page Risueño et al, 2019). Furthermore, application of knowledge-based methods by providing existing knowledge to the engineer poses a promising approach to also handle systems complexity (Pfennig, 2012).…”

Implementing a system architecture model for automated aircraft cabin assembly processes

“…Moreover, it uses common, agreed-upon vocabulary with defined rules and constraints to explicitly represent processes and automatic reasoning to infer knowledge from the entered data and detect inconsistencies. Ontologies as a knowledgebased dataset have become an important segment of socalled "intelligent" processes, which offer more flexibility, efficiency, and cost-effectiveness due to the possibility for inter-dependency between experts, machines, and applications [5]. Based on the specified vocabulary, an algorithm is developed in this research paper that interprets the rules and constraints to automatically and optimally plan the designated processes.…”