The fourth industrial revolution, underpinned by smart manufacturing or Industry 4.0, is unprecedented in the way it will disrupt industries and totally transform entire systems of production, management and governance, according to the World Economic Forum. It is of little surprise, therefore, that in a recent report, McKinsey forecasts that the economic repercussion of Internet of Things (IoT) applications in 2025 will be between $3.9 and $11.1 trillion. From these figures, around $1.2 to $3.7 trillion will be apportioned to IoT applications in the manufacturing industry.
Currently, a large amount of this data isn’t being used to its full advantage, maintains McKinsey. Much of it is being utilized to detect and control abnormalities in systems, not for optimization and prediction where it holds greatest business value.
Capturing the full data potential of IoT requires a change in business models, technologies and analytics talent. But the landscape is changing. Gartner, for example, predicts that the worldwide business intelligence and analytics market will hit $22.8 billion by the end of 2020. This is being driven by enterprises looking to use data generated by machines, sensors and people for faster decision making in real time. Smart manufacturing is no exception.
Smart supply chains
Industrial IoT and big data are starting to work together to create smart supply chains, providing manufacturers with greater insight into their requirements, partners, suppliers and customers, such as improved predictability of demand.
Real-time communications between smart factories, logistics providers and suppliers can provide vastly improved visibility of the supply chain from end to end. This can improve asset utilization, parts traceability and waste reduction. This data can also address compliancy and regulatory issues, such as emissions.
With data harvested from IoT, companies can also easily track returns and warranties and provide predictive maintenance. Orange Business, for example, has delivered an IoT platform on Microsoft Azure that allows boiler specialist e.l.m. leblanc, part of the Bosch Group, to increase customer satisfaction through remote monitoring and predictive maintenance. The remote monitoring solution collects the boiler’s data and alerts technicians if there is a malfunction. Preemptive alerts can be raised by the platform through predictive maintenance algorithms.
Less silos, more intelligence
Smart supply chains will break down the siloed steps we see in areas such as development, manufacturing and distribution and integrate them into a transparent ecosystem. They will be connected 24/7, continually producing data.
The network supporting the smart supply chain will be built around many key elements, such as smart procurement, smart warehousing, autonomous logistics and advanced analytics. This intelligent network will provide a responsiveness, the likes of which manufacturing has never seen before. Supply and demand signals will appear throughout the chain, alerting manufacturers if there is a shortage of a component, for example, in real time.
To gain the most value from this constant stream of data, some companies have adopted the concept of the digital twin. A digital twin is basically a virtual replica of the smart supply chain’s physical assets, processes, systems and solutions. The physical process feeds real-time data, such as component delays or dramatic changes in weather conditions, into the digital twin where it is logged. The digital twin provides a virtual picture, which accelerates reaction times and enables the network to be optimized accordingly.
Customization goes mass production
Henry Ford is famously documented for saying that a customer could “have any color so long as it is black.” This isn’t the case today. Big data and modern technologies have made customization available on a massive scale.
Big brands like Nike offer specialized web portals where customers can customize their own trainers. Adidas has gone a step further and plans to sell sports shoes this year with 3D printed soles that are bespoke to a consumer’s weight and gait. Previously, 3D printing was too expensive for this kind of venture, but Adidas has teamed up with start-up Carbon, which uses a technique that prints with light-sensitive polymer resin that is then baked to make it strong.
In the cosmetics industry, chemical giant BASF has set up a smart factory in Germany that can manufacture customized soaps and shampoos. When an order is placed, radio-frequency identification tags (RFIDs) attached to soap containers send the customization specifications to the production line to be made up and packaged.
Automakers like Ford and Mazda are allowing consumers to create their own cars, choosing not just the color, but the features they specifically want using artificial intelligence (AI). A smart supply chain is essential for fast inventory turnaround and real-time access to suppliers to manage lead and delivery times on made-to-order cars.
The future of smart factories
The concept of the smart factory is taking off fast, driven by the productivity gains that manufacturers are envisaging. The Fraunhofer Institute for Manufacturing Engineering and Automation estimates that the automotive industry can achieve up to a 20% reduction in costs of manufacturing, logistics, quality control and maintenance and a 70% reduction in complexity costs.
But to achieve this kind of performance, manufacturers must embrace big data, centralize it and make it work for them. Only then will they be able to share it and make better, smarter decisions.
To find out more, download our brochure, Factory of the future: The IoT and data revolution.