Industry 4.0 is all about enterprises transforming their entire digital value chain through the power of analytics and AI to harness and unlock the inherent value of their data.
With these technologies, all the ingredients exist to make digitalization a really powerful rainmaker but it requires a highly innovative approach to harnessing data. That demands commitment, focused effort and an equally committed, expert partner. A partner who is conversant with both technology and industry; and deeply entrenched in combining the two for real impact.
THE PROMISE OF DIGITALIZATION AND INDUSTRY 4.0
The concept of autonomous manufacturing plants has been a human dream for many years now. Science fiction idolized it until as recently as 3 decades back. Over the past 5 years, rapidly emerging concepts in self-reporting, self-performing equipment have fired the imagination of manufacturing enterprise management and plant operators worldwide.
On the face of it, Industry 4.0 is driven by automation alone. This perception is not erroneous. Smart sensors and the Internet of Things (IoT) have been amongst the most visible harbingers of this new wave of industrial transformation.
But automation itself isn’t the propellant. It has been around for some time. At ABB, the top managers claim they have been at the forefront of automation innovation for over a century. The true change agent is the scale and sheer ubiquity of automation today. And the bigger one is data.
How we capture it, store it, contextualize it, analyze it; and how we create insights from data spread across functions and across systems – whether IT, OT, ET, geospatial or any other such source.
As we have witnessed progressive levels of automation through the course of industrial history, the most recent watershed moment is when we moved from high levels of computerization and networking to increasingly using data for monitoring, reporting and analysis. This moment defines the cusp between Industry 3.0 and Industry 4.0.
Today to succeed, Industry 4.0 principles and techniques are key. How we use artificial intelligence and machine learning; and how we truly maximize the power of analytics is the true secret to getting entrenched, completely, into the Industry 4.0 era.
WHAT’S STOPPING THIS TRANSFORMATION
At ABB’s Industrial Automation division, the experts have been in constant conversation with the industry – customers, analysts, their own market engagement and delivery teams. The trends are telling.
Despite the fact that digital transformation is delivering an average of up to 40% increase in productivity where implemented, as much as 73% of data in enterprises is not being used for analytics.
Over 80% of implementation effort, typically, is spent on the solution provider understanding industry processes and data sources; and designing methods to capture data. This involves complex change management. And implies delayed RoI – invariably leading to decisions to deploy just point solutions which can never match the impact of enterprise-wide transformation.
WHAT’S THE ANSWER
To start with – understanding that what really makes the difference is the word “industrial” – “industrial analytics” rather than just “analytics”, “industrial AI” rather than just “AI”, and “Industrial IoT” instead of just “IoT”.
Unless technology is deeply integrated with operational processes, the path to Industry 4.0 will remain slow. That is the effort at ABB Industrial Automation’s Digital practice – to ensure that the company uses all of its expertise and knowledge of industry-specific practices to create something truly relevant as it transforms.
When it comes to choosing a solution, adopting the path of least resistance is a good start – solutions based on open architecture which can easily connect with existing systems and minimize the need for immediate change management; such that the move to digitalization is a well-planned one.
In choosing the solution and approach, it is also prudent to factor in scalability, if an enterprise solution isn’t being implemented – solutions that are extensible from edge to plant and eventually to enterprise level ensure complete coverage over time.
To gain from digital transformation that is completely customized to the company’s needs and operating environment, culture, it helps to choose a solution which has been built on deep industry understanding. This leads to quicker adoption and faster RoIs. It would also help if the solution is modular and therefore organizations can choose from a set of modules, with a strong foundational platform of course, to get a best fit combination.
Other aspects to consider should be coverage – the widest range of functions encompassed from input source and impact perspective; and security, data privacy.