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Joined-up thinking

Physical data, such as this dumbbell test can be costly to reproduce

Guillaume Boisot, head of ICME, e-Xstream engineering, part Hexagon’s Manufacturing Intelligence division, looks at how fragmented data on advanced materials could jeopardise aircraft safety.

Manufacturers are increasingly using novel materials such as advanced composites, which have yet to be characterised or tested in detail. This renders it difficult to predict how they will affect the performance of each component part or how they will cohere into a final product. Even worse, different materials for different parts are often designed and tested in silos, duplicating effort and not sharing valuable knowledge.

Reverse engineering data, such as fibre alignment analyses from CT Scans can be captured alongside virtual material tests and performance test data Credit: Volume Graphics

Materials engineering is only one part of the manufacturing process. Yet it is the one on which all the others depend. The science of (composite) material selection dictates the rest of the product’s design: its manufacture, its performance and ultimately the customer’s perception and brand reputation.

This means a critical flaw in the part or even the material microstructure could have a dangerous domino effect across the rest of the product, such as an aircraft or vehicle. One flaw in the microstructure of an advanced composite used for a safety-critical component could jeopardise the safety and performance of the entire structure.

Keeping track of data

To develop sustainable products most efficiently, manufacturers need to consider how the plethora of available materials and processes can help them achieve their goals. Keeping track of what’s available on the market is a challenge for anyone who is not a specialist, and fragmented material data raises barriers to innovation by making it difficult for manufacturers to mix and match materials and processes to create novel workflows and products that improve performance and cost-effectiveness while maintaining or improving on safety standards.

Moreover, the lack of data on materials and processes also prevents design teams from confidently applying modern Computer Aided Engineering (CAE) methods to parts that could be designed more efficiently from the start to meet those parameters. It is crucial that large organisations have a single point of truth for material data and process insights. Valuable lessons can be learned from already-conducted trials, failed prototypes, or material and quality testing, that are often not effectively shared among departments, resulting in a greater risk of unsuccessful prototypes and, in the worst case scenario, faulty or unsafe products.

Materials lifecycle management plays an essential role improving productivity and improving the use of materials throughout product development and manufacturing

The solution to this chronic loss of knowledge and data falling through the cracks is an intelligent, centralised system that can record information across the lifecycle of a product or material, in a way that is accessible to all that need it. Effective, informed materials engineering is vital to safety, cost and the customer’s experience.

e-Xstream engineering’s MaterialCenter is an example of such an enabler. We developed it to address engineers’ concerns over developing products that are fit for purpose, using materials that are capable of withstanding each product’s unique stresses and requirements. MaterialCenter is highly scalable, and enables manufacturers to store and manage their materials data, so they do not waste time retesting or recreating materials, and all teams have full oversight of the materials’ processing characteristics and potential performance.

Bridging the information gap between material engineers, design engineers, IT and manufacturing professionals, MaterialCenter is simple to use and fundamental to enabling the transition to Integrated Computational Materials Engineering (ICME).

ICME has been a topic of cutting-edge research since the late 20th century because of its power to accelerate the discovery and application of novel materials; many material engineers will be familiar with it as a proof of concept. 10X ICME implements that research using the latest technology and connecting the digital ecosystem required.

10X ICME enables design, materials, and manufacturing professionals to collaborate virtually to develop products using detailed proprietary material models and process definitions from material and machine suppliers, OEMs, R&D institutes, and end users. It combines mature modelling, accessible computing power and technology ecosystems and, with MaterialCenter as its foundation, a wealth of material insight.

Atom to aircraft

A great use case for this is Boeing, which coined the phrase “atom to aircraft”. It wanted to design and exploit materials to their full potential from the chemical composition to the microstructure, coupon and manufactured part. In practice, integrating these scales meant integrating historically siloed disciplines for the optimum result. Their goal is to enable the engineer designing a part to predict the effect that their colleague’s choice of material and manufacturing process will have on its performance and achieve a significantly optimised design.

Effective use of materials lifecycle management is the backbone of ICME, giving manufacturers the ability to analyse everything from the chemical composition to the microstructure, coupon and manufactured part and its impact on the performance of the whole. By applying physical and virtual data, parts can be designed with accurate foreknowledge of the way that every material will perform across the entire product.

For example, the Progressive Damage Model based on Professor Camanho’s research enables aerospace composite performance to be accurately predicted from coupon to part. This gives engineers greater trust in performance predictions because advanced composites aren’t treated as ‘black metal’ but the complex interconnected systems they are, and it enables engineers to virtually test numerous configurations of resin/reinforcement combinations quickly and affordably. Using material lifecycle management, they can work with materials specialists to review the correlation of physical and virtual tests and apply those margins to their designs to ensure it meets all necessary safety requirements.

With tools like these, materials engineers can work with production to – for example – compare 3D printers and never-used materials against historical data on materials, processes, and suppliers to develop a shortlist of options. The material candidates can be analysed directly in CAE tools to explore design concepts and perform basic assessments.

Once shortlisted, the product development team can request access to the precise proprietary material system models and machine toolpaths from the suppliers. Armed with such accurate data, materials professionals can virtually explore the performance limits of the material ‘as manufactured’ using multi-scale models so engineers can make optimal use of that particular manufacturing process to produce a better product with less waste.

On demand access

This workflow integration gives manufacturers instant on-demand access to insights from virtual testing and development and subsequent physical testing so that knowledge is continuously transferred from one use-case to another in a virtuous circle. Integrating material and process data into product development—from concept to customer—will help build confidence in new techniques and spur the design of bolder products without risking safety or compliance.

A manufacturer’s choice of materials has an enormous impact on a product’s performance throughout its lifetime. Recognising the fundamental role that a material’s properties play in product performance is critical for the safety and longevity of a product, and failures occur through engineers’ unfamiliarity with the behaviour of materials and processes. Predicting and preventing these flaws at the design stage requires accurate material, process, and machine data to feed into design and virtual tests, and in many cases that information does already exist – it just needs to be made actionable.

www.e-xstream.com

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