The Columbus Manufacturing 2020 report highlighted rising adoption levels of advanced technologies such as IoT and analytics among manufacturers, as physical and digital operations begin to overlap. Some in the industry still struggle to develop an effective digital strategy – but it is clear they must make the jump to stay competitive. Stephen Fox, Business Development Manager at Columbus UK explains why digital is no longer a choice in manufacturing, drawing on the experiences and insights from digital leaders at top UK manufacturing organisations.
The recent Industry 4.0 Exchange held in Derby, brought together digital leaders from some of the UK’s great manufacturing organisations from Astra Zeneca, BAE, Dyson and GlaxoSmithKline to Jaguar Land Rover, Rolls Royce and Toyota. Hosted by the ‘Father of Industry 4.0’, Henrik von Scheel, the event brought together these industry leaders to share and delve into their digital ambitions for manufacturing.
Leading industry insights
The top three digital business drivers for manufacturers are operational efficiency, competitive pressure and profitability. These drivers are still the ‘business constant’ that will almost certainly never change.
But it was clear there is significant appetite among all companies for greater and continued digitisation. The event revealed some interesting pointers as to where manufacturers are in their respective digital transformation journeys – particularly now that digitisation is seen as a necessity instead of an optional benefit. Here’s the key takeaways on where manufacturers are focusing their digital transformation efforts, and current progress on the journey to becoming a truly digital organisation.
No ‘one size fits all’ approach
Digital transformation in the manufacturing sector is a never-ending journey of continuous improvement, but certain aspects are simply constants. What we do know is each company will be starting from a different position and level of infrastructure maturity, and that requires careful management. Green field manufacturing sites offer the chance to create a digital template while legacy sites are advised to ‘cherry pick’ from this template as their needs will permit without adversely affecting existing processes and operations.
Although the promotional language used among technology advocates in the manufacturing industry is largely unchanged over the past decade, recent developments in emerging technologies and their associated price points are seriously changing what can realistically be digitally delivered for manufacturers. IoT is in the driving seat.
IoT is the clear leading digital initiative
Despite the emergence of further advanced technologies such as AI, machine learning and augmented reality, the top three digital project initiatives are firmly focused on generating maximum operational value from the Internet of Things (IoT), data automation and data analytics. Ubiquitous, low-cost connectivity and cheap devices have transformed the ability for companies to embark on IoT projects that will deliver genuine return on investment (ROI). This has in turn opened the door to the ‘data ocean’ that businesses now have to collect, automate and analyse.
This data ocean consists of unmodelled data gathered from every corner and department of a manufacturing organisation, stored in a single repository for future analysis. Applying advanced analytics tools will be the next step towards pulling valuable insights from this vast volume of data, whether this is to identify improvements in business-wide processes or pursue advanced applications such as predictive maintenance for manufacturing equipment.
The ‘predictive wave’ is still on the horizon
Many manufacturing organisations are yet to adopt truly predictive processes and technologies. There are teams in the Facilities Maintenance side of businesses who are actively looking to IoT for preventive maintenance initiatives but for the most part, manufacturing leaders at the Industry 4.0 Exchange along with host Henrik von Scheel agreed that the industry is only at the stage of collecting data of past events – even if this is perhaps only milliseconds past the event.
IoT the trigger for AI and Machine Learning
Manufacturers already have ways to diagnose and monitor most issues found on the shop floor, largely using a few simple, low devices that will measure the same conditions. To date advanced technologies such as AI and Machine Learning are not broadly used for this. Despite this, manufacturers can still make great use of collected data through analysis to identify faults, weaknesses and corrective actions that will have a significant effect on operational efficiency.
The next likely step for the industry will be widespread adoption of AI and Machine Learning as it becomes clear human processing power is simply not agile or perceptive enough to help businesses achieve competitive insights.
More than a digital copy: it’s the digital backbone of the business, so look after it
As we continue to strive for operational efficiency, we are going deeper into automating the data flows and creating an ever more extensive ‘digital twin’ of our real-world business. But a twin or duplicate is not an especially accurate description because, when challenged, it is now the case that manufacturers can physically stop a factory in real-time just as quickly with a digital data breakdown as with a physical world breakdown.
A better term than digital twin is the ‘nervous system’, a vital organ for the physical world to be able to work. Today’s high levels of digitisation mean that one cannot work without the other, and it is the new ‘business as usual’. It is therefore vital to apply the same level of robust care for these digital nervous systems to remain healthy, monitored, fed and watered to ensure continuous service, as is the case for physical world manufacturing operations.
Without skilled people to unlock insights, digitisation achieves nothing
Deploying simple IoT devices and realigning data ‘along the timelines’ is a significant step towards achieving major efficiency improvements – but detailed analysis of large data sets is a new skill set that will be crucial to make full use of data.
There is currently limited employment of internal data scientists among the larger manufacturing organisations, but the ever-rising volume of data being generated, collected and processed by enterprises means internal data science expertise to unlock insights and value from large datasets is becoming a necessity.
Well-trained, digitally savvy people – rather than technology – are the critical component for making any digital-driven operations successful.
It’s business as usual, only now it’s digital!
Digital ambition is not a top-down initiative whereby a strategy is dictated from above. It requires extensive engagement with people across all levels of an organisation to be successful. Whether it is new or not is a moot point. The digital push is very much part of the continuous drive for operational efficiency, only now adopting newly cost-effective technologies to achieve these gains. This is why digital is now routinely viewed as being business as usual.
The digital infrastructures being built by manufacturers are not simply duplicates of physical equipment and infrastructure – they are the nervous systems that underpin continuous successful operation of physical operations. A measured, calculated approach to digital transformation will be vital to ensure long-lasting business success.