Assembly affects the product's performance and reliability directly. The current assembly
method based on geometric deviation quantity controlling, cannot guarantee the physical …

New aerospace product developments need to be done following economic and
environmental drivers like costs reduction, secure a short time-to-market, reduce total carbon …

The accurate prediction of high-pressure rotor system assembly precision before assembly
is the premise of improving aeroengine assembly quality and performance. The existing …

This article presents the concepts, methodologies, and applications of In-Process Quality
Improvement (IPQI) in complex manufacturing systems. As opposed to traditional quality …

In the machine learning domain, active learning is an iterative data selection algorithm for
maximizing information acquisition and improving model performance with limited training …

Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of
cracks aided by high internal stresses. Hence, accurate prediction of maximum internal …

Aeronautics, in the context of industry 4.0, is continuously evolving to respond to the market
dynamics and has incorporated automation to many stages of aircraft manufacturing …

Reconfigurable Manufacturing Systems (RMS) have gained attention in the aerospace
industry in the past years, as post-pandemic context shows drastic production capacity …

Active learning is a subfield of machine learning that is devised for the design and modeling
of systems with highly expensive sampling costs. Industrial and engineering systems are …

Shape control is a critical task in the composite fuselage assembly process due to the
dimensional variabilities of incoming fuselages. To realize fuselage shape adjustment …