IT and OT convergence is essential in Industry 4.0

Industry 4.0 technology initiatives include collaboration platforms, connected assets, Artificial Intelligence, robotic process automation (RPA), warehouse and service robotics, ecosystems, and networks. Each of these technologies requires some level of information technology and operational technology (IT/OT) integration to be successful.

Top 5 Goals of Industry 4.0

Improvements in operational performance are the top priority for investing in IT/OT integration, including improved performance and service reliability achieved at the same or lower cost. Improved product or service quality is second, encompassing faster response to product and service problems and problem prediction. Improved personnel and public safety, more comprehensive security coverage, and cost reduction through the ability to share resources between IT/OT complete the top 5 goals of IT/OT convergence.

The continuous flow in Industry 4.0

It is a framework for building resilient data-driven operations. This continuous flow is based on a series of activities to meet Industry 4.0 initiatives and can take place in: -Assets and products to improve your ROI and enhance your capabilities. -Workers with increased decision-making and skill development. -Reorchestration of processes or a more dynamic approach to detect and react to change, whether voluntary or involuntary. The stages of continuous flow are digitize, monitor, diagnose, control and be autonomous: -Digitize: Convert analog signals and knowledge into digital and establish secure network connectivity. -Monitor: Monitor assets or processes remotely through a digital interface. -Diagnosis: Combine asset or process data with contextual data to identify root causes. -Control: Use a digital interface to remotely control or configure an asset or process. -Being Autonomous: Organize an asset or process through rules or triggers based on events.

Changing investment priorities

The emphasis on edge computing and security will unlock the value of cloud-based analytics and on-premises decision making while meeting the requirements of both. In these changes you see a more grounded and realistic approach in which companies that have been testing many technologies for a few years are now going back to fix their foundations and use all these new capabilities at scale. Security and IT/OT integration are key learnings from recent years that companies are investing in now.

Obstacles to IT/OT integration

The main barriers to IT / OT integration in organizations have to do with legacy skills and technologies. The incompatibility of legacy applications and the lack of experience on how to achieve integration is one of the main concerns in companies, just below the security ones, which always tend to appear in the lead. The main IT / OT challenges have to do with the complexity of the technology landscape, skills and personnel gaps, and strategy. Companies are looking for partners and suppliers in search of experience to help them overcome these barriers and that is where consultants such as Hexa Ingenieros acquire the greatest sense both for their knowledge and for the experience developed in the market.

The future of IT/OT convergence

Within a very few years, most industrial organizations will integrate data from Edge OT systems with cloud-based reporting and analytics, moving from a single asset view to global operational awareness. Operating models are changing and companies are integrating more with their ecosystems to implement technologies and manage both the technologies and the assets that are connected through them. Legacy systems are difficult to untangle and integrate, so this is a key area where services are being deployed. As part of an extension of that, preparing legacy data and non-OT architectures for a scalable analysis strategy is an area where extra help is needed. Continuous asset management is becoming more heterogeneous as OEMs offer managed services, third-party service providers are increasingly connected and integrated, and managed services around continuous digital component management is also a key area of ​​interest. It is estimated that within a couple of years, around 25 percent of new industrial assets deployed will take advantage of preconfigured digital twins to order assets 50% faster, enabling digital twins for all processes and configurations. of operations. For companies looking to advance their asset management strategies, the greatest challenge lies in the time and effort required to get up and running and manage asset models in the future. As the number of connected assets increases, many processes become unmanageable. And vendors are rapidly creating digital twin libraries and markets to accelerate that commissioning cycle. The complete set of data required to model and analyze an asset often comes from a dozen or more applications. Each of them carries valuable context, but you don’t need to model all that data to get started. The digital twin model is all about a scalable and repeatable methodology for a data model that captures that context and improves analytical results. In a survey conducted prior to the Covid pandemic, more than 70% of industrial respondents recognized digital twins as important or very important. A fact that aligns with the need for frameworks to improve decisions with data.]]>