Digital technologies are powering a new era in manufacturing innovation. The term Industry 4.0 was coined to refer to a combination of several major innovations in digital technology which are now starting to make sense – due to greater reliability and lower cost – for scalable industrial applications.
These technologies include cloud computing, advanced analytics and machine learning, theiot solutions, human-machine interfaces, and digital-to-physical transfer.
For manufacturers to sustain competitive advantage, they will need to grow, adapt and evolve to meet the changing needs of their customers, and the new business opportunities of tomorrow. When surveyed, 86 percent of more than 2,000 manufacturers said that they expected to see both cost reductions and revenue gains from their advanced digitisation efforts in the next five years*.
* Industry 4.0: Building the digital enterprise. PwC, 2016
https://www.pwc.com/gx/en/industries/industry-4.0.html
Here are four fundamental pillars of digital transformation.
1. Engage customers
Take advantage of the integration of digital technologies to shift focus from assets to customers.
New sources of data – customer interactions, product performance, social networks – and ways to integrate the data with operational systems, allows customer insight to inform every part of the business.
Increasingly, products as varied as aircraft engines and software are being offered as services, often on a subscription basis. Digital transformation makes the value chain more responsive, enabling manufacturers to reach end customers more directly and adjust their business models accordingly. It also makes possible business models that take advantage of the economics of mass customisation, where one-off product configurations are as efficient to produce as a batch.
For example, the appliance manufacturer, Haier, makes its washing machines and refrigerators in China to order. Customers specify the features they want on their computers or phones, or at kiosks in Haier’s retail stores, and those specs are transmitted directly to the assembly line.
2. Empower employees
Empower people to manage assets and processes in real time by connecting them with the information they need anytime, anywhere and on any device.
Powerful new collaboration, simulation and design tools, such asMicrosoft HoloLens, allow geographically dispersed design teams to work virtually side-by-side. Cloud-enabled big data hubs drive multi-tier visibility across supplier and customer networks empowering new levels of decision-making at all levels of production, operations and sales.
Volvo Car Group, for example, is not only using HoloLens to revolutionise its design processes, but is also making the technology an integral part of its sales function, enabling sales staff to offer customers a detailed and immersive virtual experience.
3. Optimise operations
Dynamically adjust production to meet changing customer demands.
Manufacturers can access insights on production line and component behaviour in real time. With the availability of advanced cloud analytics, the time and expense of analysing large amounts of data from smart sensors is no longer prohibitive to all but the largest enterprises. Manufacturers of all sizes can now take advantage of powerful data analysis and machine learning capabilities to identify areas of waste, improve cycle times, speed up automation processes, maintain equipment more predictability and proactively, and increase turn-times for inventory across the value chain.
Jabil, the design and manufacturing solution providers, created digital factories using machine learning, predictive analytics and the cloud to analyse millions of data points from machines. Before they even occur, they are able to identify disruptive errors or failures with 80 percent accuracy.
4. Transform products and services
Give engineers the tools to make better roadmap decisions, to strengthen product usability and improve design elements.
Rather than wait days or weeks for feedback on products and services, manufacturers are able to respond, innovate and execute change in real time using insights based on telemetry data gathered from actual live product performance and customer usage.
Industrial IoT capabilities combined with powerful machine learning models and data visualisation tools enable manufacturers to ingest data from any source and in any format, allowing companies to offer more personalised products and higher-margin customised solutions. Revenue gains can also be achieved from offering new digital features and products, or from introducing analytics and other new digital services to customers.
Industrial products that track their own activity also provide powerful insights into those who use them: how they operate, where they face delays, and how they work around problems. Manufacturers can use this data to develop profitable new products and services.
Rolls-Royce built a scalable data analytics system to transform how it uses data to better serve its customers. By collecting and aggregating on-engine health data, air traffic control information, and fuel usage and processing information in real time, Rolls-Royce is able to help its aviation customers improve fuel usage and maintenance planning and reduce flight disruptions saving potentially millions of dollars annually.
Making a success of Industry 4.0 digital transformation requires major shifts in organisational practices and structures. These shifts include new forms of IT architecture and data management, new approaches to regulatory and tax compliance, and most significantly, a new digitally oriented culture, which must embrace data analytics as a core enterprise capability.
