Exceptional role of data in manufacturing
Data has long been precious fuel for manufacturing, driving efficiency improvements, reductions in waste, and incremental profit gains. These days, such notions as “big data” and “smart data” create new dimensions to the value of research on industrial data bridge.
As a consequence, data is no longer used for reporting past activities only - it allows manufacturers to predict future events, risks, as well as to investigate their extended value chain, improving the delivered customer experience. Data now presents the businesses with multidimensional capabilities and broader horizons, guiding them towards numerous exciting ways for manufacturing growth.
Industry 4.0 – industrial data from start to finish
Industry 4.0 is all about data or, to be more precisely, actionable data which leads to information, knowledge, valuable insights and any other form of data-driven intelligence and analytics where artificial intelligence and cognitive science come into play. This data has objectives stretching across the entire value chain and product lifecycle: from ideation, prototyping and development to maintenance, production and ecosystems of information driving innovation, logistics and pretty much any industrial process, all the way to disposal or recycling.
So, why industrial data bridge presents a challenge for the manufacturers?
Bridging IT and OT might resemble learning a new foreign language. Although OT people are used to Fieldbus protocols (based on serial communication principles), they are not very familiar with systems in an enterprise environment that use TCP/IP based protocols to efficiently transfer information over the Internet, store it in datacenters and manage the data in a way that enables them to retrieve information through the visibility of a much bigger database.This is the domain of the IT people, but they are usually unaware how the data from a single sensor finds its way into the enterprise world.
The same happens in the other direction when it comes to giving commands towards devices in the field as a result of complex analyses done in data centers. These commands, of course, also need to be converted into a format OT people can understand and manage.
One of the main challenges the manufacturing faces today is to develop foundation for successful IIoT and Industry 4.0 implementations by connecting even legacy devices and making the data available and understandable for people in both worlds.
Let’s face the beast OR 3 top industrial data challenges and how to overcome them
Industrial IoT (IIoT) is currently struggling with the following obstacles :
- Connecting devices in the field and making the data available in private and public clouds to be utilised by OT and/or IT systems. One needs the devices to forward the data acquired in the field on sensor level and translate them, so that they are understood by the big number-crunchers up in the cloud. The biggest issue is the lack of standards that can be applied to streamline the access methods.
- Making sure the acquired and transferred data is protected and is available for the specific user only. The main idea is to ensure cyber security when protecting the environment from attacks, to avoid unauthorized access to machines, the production environment or even the complete plant, respectively.
- - Assuring that the data transfer happens in a predetermined way and in real time to enable full control. It’s of utmost importance to ensure data integrity, especially via the use of Time Sensitive Networking. The different TSN standards can be grouped into three basic key component categories that are required for a complete real-time communication solution: time synchronisation; scheduling and traffic shaping; selection of communication paths, reservation and fault-tolerance. TSN will play an important role in the future, but it still needs to be widely adapted in order to become effective.
However, in the most information management and data environments, silos represent the biggest problem. In Industry 4.0 and industrial data, these silos range from ERP (enterprise resource planning) and industrial control systems to traditional documents, both digital such as good old spreadsheets and still in paper format too.
Silo issues need to be solved by people who clearly understand the gaps, can formulate a solid strategy, understand the processes, and put you on a path of the journey and vision called Industry 4.0.
All in all, manufacturers have the ability to harness the power of all their data. They can find a good balance between constant production upkeep, assurance of just-in-time delivery of goods, and high yield management on the one hand, while reducing cost of product quality on the other.
The priority should be to consider the phenomenon of the so-called “industrial data bridge” seriously and from different angles. When IT and OT world understand each other and, eventually, merge, it will be possible to work toward a common goal in a more cost-and time-efficient way. Finally, lots of shared issues, tasks, and requirements will serve as a starting point for a fruitful cooperation.