When the ISA-95 model was created, it laid the foundations for a risk-averse approach to manufacturing processes. This was a critical pre-work for what followed more than a decade later with the inception of Industrie 4.0 (Industry 4.0), a.k.a the Fourth Industrial Revolution. While Industry 4.0 could seemingly appear as a leap from ISA-95, it could be a well-crafted journey if done the right way.

In manufacturing, the stakes are so high that a diversion from a proven line of thought always draws skepticism and inertia. And with Industry 4.0, we are talking innovation[i] that encompasses process changes, broader market evolution, technology disruptions, and growing incongruities between expectations and results.

The Incremental Innovation Path

Starting from a position of safety is an approach that many manufacturers have adopted in their overall strategy to reach their Industry 4.0 goals. Manufacturing Execution Systems (MES) have been the trusted system for over three decades now to streamline manufacturing operations, improve shop-floor visibility, and to act as a common management system in an industrial setting. So, it is logical to shoot for incremental changes in a known and trusted system, like MES, until it is not.

The true essence of Industry 4.0 lies in unlocking the full potential of industrial data with a larger focus on automations driving efficiency at enterprise scale. As systems became more and more connected in manufacturing, the concept of IoT in industrial (or IIoT) started becoming relevant – optimized for industrial use cases. IIoT thus is the pathway to Industry 4.0. Now the question begets if an MES can deliver on all the IIoT use cases. After all, an MES was designed with a specific set of requirements in mind to fulfill mission critical applications.

MES solutions are built on proprietary capabilities designed to deliver a robust and centralized manufacturing operations management solution. As we talk about exploiting data to fulfill greater initiatives around efficiency, cost optimization, and improved worker safety among others, it requires a more holistic platform approach to unify all underlying industrial systems along with enterprise tools and technologies. One way could be to integrate additional software and tools with the MES to resolve IIoT use cases. This approach, however, opens the floodgates of potential security loopholes, data redundancy and consistency challenges, tool and data overheads, vendor lock-ins, and worst of all the inability to scale across multiple sites amidst several other technical implementation difficulties. On a positive note, it offers the convenience of a known system which minimizes internal organizational inertia and a potentially shorter learning curve for existing stakeholders.

The More Radical Path

With the rise of cloud technologies and unprecedented connectivity, digital transformation became top of mind for every executive and business leader. The manufacturing industry was somewhat of an outlier in this regard. But the pandemic fast tracked the need for digital transformation in manufacturing. Leaders in the industry realized they are sitting on a growing mushroom of data that had enormous potential if harnessed in real-time for decision making. And before long, the manufacturing industry was more ready than ever before to walk the talk on Industrial IoT.

Umpteen numbers of vendors have popped into the market with point solutions for specific IIoT use cases or solving a particular pain point. From machine-to-machine connectivity, data collection, aggregation, modeling, visualization, to analytics, each of these IIoT solutions address one or more problems with factory automation, operational efficiency, improved visibility, process control, quality control, predictive maintenance, among others. However, most of these solutions need manufacturers to adopt either a cloud-first strategy, introduce new data infrastructure complexities, or worse expand the security threat landscape.

To capture the market, several mission critical system providers have jumped into this space trying to bootstrap their solutions as an IIoT platform. The result is too many manufacturing companies have burnt their fingers driving home the message that IIoT is capital-intensive and demands a lot of work[ii].

The best of both worlds

Going back to basics, the ISA-95 model still holds a lot of relevance even when IIoT is all about trying to juice data at every layer of the model. This essentially means that the ideal IIoT platform should sit “on the edge” of the ISA-95 data model. The IIoT platform can supplement the PLCs, SCADA, Historian, MES, ERP, and other enterprise systems. Ideally, at its core there should be a data pipe or a message broker that supports bidirectional data flow for real-time actionable insights. Several technologies such as MQTT, NATS, and Kafka follow such a publish-subscribe method for data exchange between applications and the platform could use any of them as its core message broker. Each of them has its own pros and cons and warrants a separate discussion. But more importantly, the data pipe should have native connections to all the mission critical systems and popular enterprise applications. This is critical so that manufacturers do not spend time and effort to develop, host, and maintain intermediary applications to publish or subscribe to the data pipe.

A well designed IIoT platform can act as the bridge between the various layers of the ISA-95 model, harmonizing the data from each of the systems and enriching it with valuable context. An IIoT platform coupled with all the data sources in an industrial setup can unlock the potential of data, which was not previously possible.

The manufacturing industry is at an inflection point today. There is still a lot that remains to be done. And each player in this ecosystem has a role to play. And this play needs to be that of partnership and technological cooperation. Because if it is not now, then it will never be the era of Industry 4.0 in its true sense.

Author: Suranjeeta Choudhury, Director of Product Marketing and Industry Relations at Litmus. Suranjeeta brings nearly two decades of experience in the Wireless communications, Industrial IoT, and Automotive space leading high-performance teams in start-ups, large multinational conglomerates, and Fortune 500s.

[i] The Discipline of Innovation by Peter F. Drucker https://hbr.org/2002/08/the-discipline-of-innovation

[ii] Three Industrial Internet of Things (IIoT) myths that need busting by Dan Matthews https://businesschief.eu/technology/three-industrial-internet-things-iiot-myths-need-busting