In Germany, for instance, BMW has cut by 80% the time required to deploy new applications at its Regensburg plant, where it made nearly 320,000 vehicles last year.
It has done so in large part through the use of a group Internet of Things platform that allows ‘plug-and-play’ set-up of various use cases with minimal installation effort to allow rapid identification of optimal solutions.
But Industry 4.0, which refers to the integration of automation and data into manufacturing, is not only for large organisations. Rold makes locking mechanisms for domestic appliances, and has improved its turnover by more than 7% through techniques including ‘digital dashboarding’.
Both examples are cited in Fourth Industrial Revolution: Beacons of Technology and Innovation in Manufacturing, a report from the recent World Economic Forum prepared with the cooperation of consultancy McKinsey. The report has identified seven ‘lighthouse’ companies – four in Europe, two in China and one in the Middle East – that can act as exemplars of Industry 4.0 best practice and achievement, adding to eight from last year.
But the report also makes it plain that many companies encounter difficulties in implementing Industry 4.0 programmes – in fact 70% fail to move beyond the pilot phase – and therefore seeks to highlight best practice that will ensure project success.
Key factors to aim for
Enno De Boer, head of manufacturing for McKinsey, identifies three key enablers. “The Fourth Industrial Revolution is driven by three technological megatrends of connectivity, intelligence and flexible automation,” he says. “Connectivity creates links between discrete areas of an organisation, increasing visibility. Intelligence automates event recognition and translation to guide decision-making. Flexible automation incorporates response mechanisms and remote movement,” he says. “It is the manufacturing sites that have adopted technologies in these three areas that have seen a step change in performance.”
The report identifies five essential ‘value drivers’:
Big data decision-making, which means using the data produced by connected machines to improve operations, thereby removing error from decision-making.
Democratised technology that allows workers to create their own solutions. “New app-creation tools allow manufacturing problems to be addressed by key stakeholders who understand them,” De Boer explains. “Such tools identify new opportunities for improvement and taking swift action, rather than waiting for cumbersome IT projects.”
Agile working models that facilitate the implementation of new use cases in a short period, enabling projects to move from pilot to scale-up in weeks rather than years. “Some organisations drive this rapid innovation through using a model factory of experimental technology,” De Boer adds.
Minimal cost. “Most of the lighthouse organisations have undergone a digital transformation with existing technology augmented by technology such as sensors, which require minimal capital investment,” says De Boer.
New business models that complement and/or disrupt the traditional business and value chain. “Digital technologies allow for the creation of business models that help companies to remain competitive by engaging customers in the design stage, lowering lead times, and executing an order of one, but at the price of mass-production,” says De Boer.
Harness people power
De Boer emphasises that people count every bit as much as technology. “Leaders act as role models for change, communicating a clear change strategy and ensuring that all employees feel part of the journey,” he says.
“For example, Schneider Electric in France gave employees the opportunity to create their own solutions on the shop floor with a focus on benchmarking and analysis to drive improvements.”
De Boer is confident that the examples set by the lighthouse companies provide a universally applicable set of models.
“Manufacturing leaders should see the results as an urgent call to action,” he says.
Content published by Professional Engineering does not necessarily represent the views of the Institution of Mechanical Engineers.