Australian Manufacturing Needs Help. Hail the Digital Twin.
It is no secret that Australian manufacturing is in decline. In fact, according to a report from Conry Tech, no industry in the past fifteen years has seen a sharper downward trajectory. To avoid falling deeper into the dig-and-ship trap or thinking that the inflation of real property will somehow ensure Australia’s future prosperity, we must re-invigorate Australian manufacturing. But how?
Digital twins represent one key and powerful path forward to innovate and manufacture our way to a much better future. A digital twin is a virtual representation of an entity or system, that can simulate its behaviour and performance under various scenarios and conditions. Done well, digital twins are among the most powerful decision making tools technical and commercial innovators can have. They enable innovators to test, optimise, and improve their products and processes, without the risks and costs of real life experiments and trials. This also means improved profitability, because it becomes possible to measure the impact of the tech stack on the cost of manufacturing, and then determine where the innovation effort should be focused from an ROI perspective.
Digital twins can also provide valuable insights and feedback, that can help innovators make better decisions and enhance their creativity. As noted by Accenture in a report on the value of digital twins: “A digital twin’s ability to enable progressive learning and capture tacit knowledge provides a key, differentiating benefit: it stores and structures information in a way engineers and operators can understand.”
Digital twins are also a useful solution to a challenge that many manufacturers face with digital transformation: Manufacturers face challenges with scaling up and adopting autonomous solutions and managing the massive data generated by them. Digital twins allow the manufacturer to extract the value that they’re making in technology investments while avoiding the need to “rip and replace” before they’ve confirmed the approach.
In short, it can be an enormously effective and efficient way to test products for commercial and technical readiness, and scale towards production and commercialisation. Digital twins support a boost in speed to market too, with many manufacturers realising benefits in three to six months.
Unfortunately, digital twins are also very difficult to get right. As noted in a report published on the NIH: “Scale and fidelity are significant digital twin challenges, as is the availability of open, real-time, high-quality data. Data ownership, data management, data interoperability, intellectual property rights, and cybersecurity are also key considerations.” Managed poorly, digital twins can expose an organisation to risk, and become a significant cost burden.
There’s no way around this – developing digital twins requires an incredibly high level of skill and competency in digital technologies, right across the gamut of data analytics, artificial intelligence, physics and chemistry, financial rules and markets, and the connections between these things can be enormously complex, especially given that they’re all areas where professionals tend to specialise, and might not be as familiar with the other areas.
However, it’s worth noting that much of the complexity with digital twins comes from building them. With the right expertise in support of that part of the process, actually utilising the digital twins themselves is reasonably straightforward for decision-makers.
Unfortunately for Australian innovation, these skills and competencies are scarce and underdeveloped in the innovation ecosystem. CSIRO has had limited capacity to build digital twins, though it has undertaken some projects with government departments in recent years. Australian universities are struggling to keep up with the latest developments and best practices in digital twin technology. [and even less cohort of people are skilled to build these class of assets to accelerate development and commercialisation of new products, where an acute need for balancing fidelity with stage of maternity of new product and innovative businesses that take the product to market.]
Our team has been focused on tackling the digital twin challenge, developing competencies and methods that can be scaled across the entire innovation lifecycle. We have been leveraging digital twins to help support our partners since our inception and to test and prove commercial and technical (CRL/TRL) readiness.
One recent example is the work that we did to build a solution that allows for the infamously polluting lithium to be refined and utilised in an environmentally sustainable and more economically efficient way.
To achieve this, we have been deploying digital twins at every stage, from the earlier stages of mining exploration, to the conceptual design of the solution, flowsheet selection, feasibility analysis, flowsheet validation, and continuous performance monitoring. The results have been a greater resource yield with fewer contaminants, and higher quality battery-grade lithium products.
Our approach can be applied to other resources in refinement, and could assist in Australia transitioning from a nation that focuses on resource extraction to one that has expertise in refinement, pushing the national resources sector much higher in the value chain. For miners and manufacturers to make that transition, however, utilising digital twins to model the commercial and technical readiness is a critical step.
For Australia to move up the global ranks of innovation and entrepreneurship – and remember, on both metrics we’ve been low for quite some time now – developing capabilities and expertise in testing the market readiness of products and businesses is going to be key. In an increasingly complex world, digital twins are a cornerstone of those capabilities to accelerate innovation and de-risk investments.