We’ve been in the process of transitioning to Industry 4.0 (aka the fourth industrial revolution) ever since the German government coined the term in 2011. It’s proven to be a long and complex journey. The World Economic Forum has estimated that the worldwide impact of Industry 4.0 will reach US $3.7 trillion in value by 2025.
Cloud computing and the Internet of Things have already had a significant impact on the manufacturing industry, increasing automation and the amount of data generated during the process. The natural next step on the journey will be to enhance those processes using AI and machine learning (ML), to facilitate increasingly sophisticated techniques such as real-time analysis and predictive analytics.
Crucial to the success of these transformative processes is edge computing: data processing that takes place on the periphery of the network. Processing data closer to the source reduces the physical distance it must travel, therefore reducing the latency and the implicated cost. And that’s where processing at the edge really comes into its own: the potential for near-real-time insight.
For manufacturing, that insight has the potential to completely transform production lines of all sizes. And that transformation couldn’t come soon enough. Our move towards an on-demand culture, with consumers expecting products to be delivered quicker than ever, means companies need to respond to that demand as efficiently as possible. And in the future, even a fast response won’t be fast enough. We expect to see a significant shift towards anticipatory production, where manufacturers will be able to forecast customer demand, understand how that demand will change over time, and manage resources accordingly. According to a recent Dell Technologies and Institute for the Future survey, more than 75 per cent of international business leaders expect to be able to do this by 2025.
Edge computing seamlessly integrates IoT devices into a network infrastructure, and coupled with ML and real-time analytics, can gather, analyse and apply valuable data at speed. This immediacy allows for predictive maintenance and real-time quality control and can also highlight areas that could benefit from increased automation.
A local example in practice is the Springboks rugby team. Their head coach and coaching staff have made use of CCTV and AI to really look at what the players are doing and how they could improve their game in the future. With Dell being the technology partner of the Springboks it is clear that at this level of sport whereas little as a 1% improvement could mean the difference between winning or losing the World Cup, data adds huge value. So, it is the culmination of talent, training, mental strength and preparation and the use of data that can help athletes and teams improve and become world-class.
What’s particularly exciting, though, is how accessible this technology has become. Previously, it would only be available to multinational corporations with the biggest budgets. DataProphet is a locally based startup business making use of its own developments and making them available to enterprises of all sizes, globally. Setting the organisation up to compete globally and against bigger global players.
The same level of access and innovation has also led smaller businesses to take advantage of 3D printing. 3D printing allows small-batch prototyping and production inconceivable until very recently. The 3D printing market is forecast to account for more than US$20 billion in spending by 2025 and will only continue to transform further the manufacturing landscape, whatever the size of the business.
The exceptionally urgent demand for products witnessed in recent months has certainly tested the manufacturing industry. And without doubt, increased use of open-source software and data-sharing through edge computing will have played a role in the startling level of agility and innovation many have achieved. The creation and sharing of prototype tools, technologies, processes and services has facilitated a “cottage industry” of high demand products to emerge. New players in the market – or old players in a new market – have been able to quickly and inexpensively manufacture products and sell them globally.
The availability of increasingly sophisticated forms of on-demand, iterative production continues to unleash new opportunities. But what might that mean for the future of manufacturing? For larger companies, the results of this democratization of innovation are paradoxical. Low-cost do-it-yourself (DIY) alternatives to traditional product development and manufacturing may well make gains in a market traditionally dominated by industry giants. But the hope is leaner, more agile ways of bringing new products to market will catalyse adoption by the industry’s large and small manufacturers.