Imagine a factory in which all machines, all sensors, and all tools communicate with each other. A defective assembly component is automatically detected, the manufacturing process is automatically adjusted, and maintenance jobs are performed preventatively before downtimes occur. Today, that vision is no longer pie in the sky but a reality. The key to that evolution lies in interoperability.

About the author

© VDMA

Andreas Faath, Managing Director of the VDMA Machine Information Interoperability (MII) department, is responsible for VDMA’s interoperability activities. That makes him an important voice of worldwide mechanical and plant engineering in terms of interoperable information exchange and digital transformation. He represents mechanical and plant engineering and their wishes and needs on the boards of various expert committees.

Interoperability – what’s behind that awkward word?

Interoperability describes the ability of different systems and components to seamlessly work together and exchange data without requiring special adjustments. In industrial settings, for instance, that means ease of communication between robots, sensors, and control systems made by various manufacturers. An electric drive system can transmit its data directly to robots made by manufacturer B that in turn transmits its data to the control unit of a machine tool from manufacturer C.  

In the context of a digitized factory in which many machines “talk” to each other, interoperability is essential. It’s not for no reason that interoperability, besides control and sustainability, is one of the major action fields of Industry 4.0. If robots, electrical drive and control systems in a factory cannot “understand” each other efficient and sustainable manufacturing that minimizes the consumption of resources is inconceivable.

Advantages of standardized communication

An investment in interoperable systems pays off in several ways:

• Efficiency enhancement: Automated data exchange eliminates the need for manual input, reducing efforts and accelerating processes.

• Flexibility: New machines or systems are easier to integrate. The company remains fit for the future and can respond faster to market changes.

• Cost savings: Although initial capital expenditures may be high, efficient processes and reduced error rates will lead to cost savings in the long run, both generally and in terms of integrating new equipment into existing interfaces.

No digital transformation without collaboration between machines

Today, after nearly 15 years of digital transformation, we’ve largely crossed the threshold to the fourth industrial revolution, aka Industry 4.0. This new era is primarily characterized by the possibility of complete connectivity of all manufacturing components and systems. Yet this connectivity confronts companies with major challenges: In many factories, machines made by various manufacturers and of different ages exist side by side.

"Without a common “global manufacturing language” overcoming this linguistic barrier and enabling smooth communication production-related IT systems cannot process machine-generated data and use them for monitoring or optimization purposes."

Andreas Faath, Managing Director of Machine Information Interoperability at the German Mechanical Engineering Association

Many of them “speak” their own language in a manner of speaking and produce data in numerous formats. Standardizing the wide variety of data entails a major effort but one that’s necessary nonetheless because without a common “global manufacturing language” overcoming this linguistic barrier and enabling smooth communication production-related IT systems cannot process machine-generated data and use them for monitoring or optimization purposes.

The importance of standards

A key aspect for achieving interoperability is standardization. Internationally standardized architectures such as OPC UA (Open Platform Communications Unified Architecture) form the foundation for interoperable systems. They define how data are to be structured and transmitted.  

Via standardized extensions, the so-called OPC UA Companion Specifications, various information models for a variety of sectors, equipment, or applications have been defined. These specifications, which are frequently defined by working groups of organizations like the OPC Foundation or industry associations such as VDMA, enable greater interoperability by ensuring that data by various providers can uniformly be understood and exchanged.

Let’s take a milling machine for example: For logging the machine’s production data (e.g., control values, measurements, parameters), OPC UA are used for forwarding the data to other systems in the first place. To enable manufacturer-independent processing of this information for these systems, Companion Specifications are used which semantically standardize that information. In addition, these semantically interoperable data can be shared with the machine manufacturer, for example, to perform potential improvements or enable predictive maintenance.

The smart factory represents the production site of the future in which smart connectivity and automation lead to a self-optimizing factory floor. Interoperability plays a fundamental role in this regard that goes far beyond mere data exchange.

In the future smart factory, not only machines communicate with each other but the manufacturing data of the relevant product are logged and shared with other production resources and super-ordinate planning and logistics systems. Each product receives a digital image of its individual product history. When an automobile, for example, passes through the assembly line it has been captured which production steps may be optimized based on what actual parameters and what processing steps based on the production information collected so far may still be pending. This can only happen when all the systems involved – from the production resources to production control to quality assurance – speak a common “language.”

The relevance of interoperability becomes particularly clear in terms of predictive maintenance. Sensors continuously monitor the condition of machines while gathering data, for instance, about wear, temperature, or vibrations. These data not only need to be logged but also analyzed across systems. Only if sensor data can meaningfully be correlated with production schedules, maintenance histories, and quality data can reliable predictions be made of necessary maintenance jobs. Methods of artificial intelligence are already enabling new potential in this regard today.

Future prospects

The importance of interoperability is going to continue to increase. That’s why VDMA’s Machine Information Interoperability (MII) department has set itself the objective of promoting the use of existing standards and the compatibility of a wide variety of technologies such as OPC UA and AAS. After all, interoperability is a key pillar of efficient digital transformation because only through value chains and data eco-systems designed for interoperability can information be used and shared with ease, reliability, and in scalable ways.

“That’s important particularly in the context of new technologies such as AI and Machine Learning because they require large data volumes that can be provided only by seamlessly connected and, above all, interoperable systems. In addition, cloud and edge computing open up new potential for (AI-based) data management and analysis.

Conclusion

Interoperability enables companies to fully exploit the advantages of the fourth industrial revolution. For businesses, this means that the implementation of interoperability should not be seen as a necessary evil but as a strategic investment in the future. The road toward achieving that goal may appear to be complex but with proper planning and step-by-step execution it’s feasible for any company.