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Digital Twin (DT) is a dynamic digital representation of a real-world asset, process or system. Industry 4.0 has recognised DT as the game changer for manufacturing industries in their digital transformation journey. DT will play a significant role in improving consistency, seamless process development and the possibility of reuse in subsequent stages across the complete lifecycle of the product. As the concept of DT is novel, there are several challenges that exist related to its phase of development and implementation, especially in high value manufacturing sector. The paper presents a thematic analysis of current academic literature and industrial knowledge. Based on this, eleven key challenges of DT were identified and further discussed. This work is intended to provide an understanding of the current state of knowledge around DT and formulate the future research directions.

On Airbus aircraft, the undercarriage reinforcing is attached through the lower wing skin using bolts up to 1-inch in diameter through as much as a 4-inch stack up. This operation typically takes place in the wing box assembly jigs. Manual hole drilling for these bolts has traditionally required massive drill templates and large positive feed drill motors. In spite of these large tools, the holes must be drilled in multiple steps to reduce the thrust loads, which adds process time. For the new A380, Airbus UK wanted to explore a more efficient method of drilling these large diameter holes. Introducing automated drilling equipment, which is capable of drilling these holes and still allows for the required manual access within the wing box assembly jig, was a significant challenge. To remain cost effective, the equipment must be flexible and mobile, a llowing it to be used on multiple assemblies.

Significant effort has been applied to the introduction of automation for the structural assembly of aircraft. However, the equipping of the aircraft with internal services such as hydraulics, fuel, bleed-air and electrics and the attachment of movables such as ailerons and flaps remains almost exclusively manual and little research has been directed towards it. The problem is that the process requires lengthy assembly methods and there are many complex tasks which require high levels of dexterity and judgement from human operators. The parts used are prone to tolerance stack-ups, the tolerance for mating parts is extremely tight (sub-millimetre) and access is very poor. All of these make the application of conventional automation almost impossible. A possible solution is flexible metrology assisted collaborative assembly. This aims to optimise the assembly processes by using a robot to position the parts whilst an operator performs the fixing process.

This paper describes and demonstrates the use of an assembly centric design algorithm as an aid to achieving minimal hard tooling assembly concepts. The algorithm consists of a number of logically ordered design methodologies and also aids the identification of other enabling technologies. Included in the methodologies is an innovative systems analysis tool that enables the comparison of alternative assembly concepts, and the prediction and control of the total assembly error, at the outline stage of the design.

In the past few decades the number of airplanes has increased dramatically and aircraft systems have become increasingly more complex. Under these conditions, the next generation of airplanes will undergo substantial changes and will make significant technical progress to improve operational safety. This vision is entirely consistent with the adoption of Integrated Vehicle Health Management (IVHM) technology which uses merging of interdisciplinary trends to carry out safe and effective vehicle operation. Hitherto, IVHM has made much progress in the realm of maintenance and operation, but little on safety assessment. This paper discusses the issues around how IVHM could be used to aid the operational safety assessment in the aviation industry. Special attention is paid to existing safety assessment methods, and some challenges and promising research directions are highlighted.