Industrial internet of things (IIoT) has made it easier than ever to improve business results with data.
By 2028, the global IIoT industry is expected to be valued at approximately $438 billion, up from today’s estimated value of $116 billion. As manufacturers continue to embrace technology to improve their processes, products and human workforce, it will be imperative for manufacturing companies to also adopt digital twins.
With more than 22 billion connected IIoT devices anticipated to be used in just a few short years, digital twins will be critical in turning collected data into a competitive advantage.
When it comes to data, it’s no longer about collecting it, but rather transforming it into a usable format for fast, relevant insights that lead to improved business outcomes. Digital twins come in various contexts. However, the ideal goal is to have a digital representation of anything using data from sensors, systems and assets. It’s a virtual representation of the physical that encompasses all of the information related to that specific thing.
Digital twins save teams from the manual work of cleansing and contextualising data from siloed systems and capture the precise conditions that went into making each product. They represent physical products and the processes and systems that created them.
Improvement efforts, such as reducing cost and waste are important, especially in today’s uncertain and increasingly volatile times. Having easy access to information about what happened during production, as well as the ability to capture the ideal settings for current and future production, will increase a manufacturer’s capacity for digital transformation – a key initiative of nearly all competitive and forward-thinking manufacturing businesses around the world. Ultimately, these insights can help companies not just produce more, but actually produce better with fewer resources.
But if today’s companies are generating plenty of data, why do they need another technology like digital twins? There is no limit to the amount of data a company can generate, yet those that are advancing most quickly realize that it comes down to quality, not quantity. Having the right, formatted data, available to the right person, is why manufacturers are adopting new strategies. It’s about harmonising data from different systems, formats and locations into a structured, automatically updated model.
With the ongoing labour shortage and skills gap in manufacturing, some companies collect too much raw data but don’t have the resources to do something meaningful with it. This may include having employees that don’t know what to do with data or struggling to retain top talent when manufacturing expertise is hard to find. Other companies lack data connectivity, making it hard to piece together a full picture of production.
The overriding issue is that, even if data exists, many companies get stuck with poor information. Many manufacturers try to optimise their materials, processes or machines. Despite their best efforts, though, they can’t find some of the less obvious optimisations. This is to be expected as technology should upskill human abilities.
There will never be a replacement for human capital. Yet today’s tools, like digital twins, are reimagining the ways in which manufacturers make use of data. Digital twins should be purpose-built for manufacturing business use cases. A company should find a digital twin that is designed for specific outcomes: improved quality, reduced cost and risk, or process optimisation.
In one case study, a manufacturing company had been incorporating Six Sigma and Lean manufacturing processes, which were affording them production gains. However, when they reached an improvement plateau, they turned to new tools to help uncover additional improvements to their complex processes. Digital twins enabled them to uncover optimal operating parameters, resulting in savings in time, resources and operational costs.
Digital twins, a smart IIoT platform and business intelligence applications can help all types of manufacturers uncover opportunities within their own processes. The future in manufacturing is here.
Paul Pinaut is vice president of IIoT market strategy at Braincube