Intelligent Optimisation


However, tolerances and precision in the

aerospace industry (where optimisation is an established tool) are astoundingly tight because of the high degree of regulation and safety required. As a result, errors and deformation from thermal cycling that occur on the micron scale during manufacturing processes can render a part unusable. Manufacturing Technology Centre

Optimisation is everywhere. It’s prevalent in our day-to-day decisions as we choose the

fastest route to work, the cheapest product or service for our needs, or the healthiest snack (or, maybe, the tastiest) when hunger arises. It’s also inherent to optimise the designs, processes and services that shape our lives through a range of evolving simulation techniques and applications. As such, optimisation is finding a new place in the additive manufacturing market and is helping manufacturers meet rising demands for lighter and more energy efficient products by optimising mass distributions.

Bjorn Sjodin, VP of product management at Comsol, explained: ‘3D printing, or additive manufacturing, is probably the current strongest trend within the optimisation space. Here, shape and topology optimisation are important methods, and they result in new shapes and designs that the human mind could never envision without the help of computational tools. It is an exciting area that we are very active in, with respect to customer interactions and implementation of new tools for the future.’ Consequently, topology optimisation is finding a new lease of life in the 3D printing and additive manufacturing markets. Jeffrey Brennan, chief marketing officer at Altair, explained: ‘Topology optimisation, with its generation of efficient, non- traditional, organic-like designs, serves as a perfect complement for 3D printing, given the manufacturing flexibility that it offers. But it goes beyond that to include the design and optimisation of even complex lattice structures using different optimisation disciplines.’

30 Scientific Computing World October/November 2018

(MTC) is working to optimise the achieved precision in its additive processes and overcome this challenge. Using Comsol Multiphysics modeling and simulation apps, MTC has created an app that predicts the deformation of parts and allows designers to build deformations directly into their designs. The implications of such apps are wider

reaching, according to Sjodin, who added: ‘The field of simulation apps also opens up the door for a variety of optimisation opportunities, such as supporting a sales

“3D printing or additive manufacturing is probably the current strongest trend within the optimisation space”

team, or product optimisation with non- simulation experts, to name a few.’

Digital twins Optimisation is now helping companies create digital twins with the integration of machine learning techniques. Brennan explained: ‘As things mature, optimisation algorithms will combine with learning algorithms to improve product design. ‘For example, if we have a product out in the field such as a wind turbine, data will be gathered on its performance in various conditions. This puts a load on that device, which starts to make the baseline design struggle for its normal longevity of product duration, particularly during adverse conditions.’ Brennan added: ‘That data can be

used the next time a structure needs to be placed in that same place, under the same conditions. That new structure will then withstand that environment better because of the information provided to the digital twin version with data from the field. That’s a form of optimisation that takes place over years – after the product leaves the manufacturing plant and is in service. Product improvement still hasn’t stopped because the data is taken from the environment of true operation to inform the next generation of that product.’

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