Modern industry is a complex ecosystem of equipment, sensors, and systems, each with its own specific interface and communication protocol. This diversity is a result of technological evolution and the need to meet different production requirements. However, this diversity also poses significant challenges in terms of automation, integration, and data analysis.
Control of these devices can range from electromechanical panels to complex controllers with automated embedded systems. Therefore, remote monitoring must adapt to a wide range of instrumentation options—from simpler panels to embedded controllers that, in turn, have distinct communication protocols such as Modbus, MQTT, OPC-UA, EtherCAT, and others. The biggest challenge is to centrally and unify all application variations.
Industrial Interoperability with Bridgemeter: Integrating Sensors, Controllers, and Systems in the IIoT with Flexibility
Integrating different devices, protocols, and systems can be complex. Some tools available on the market focus on a specific application or piece of equipment, which restricts connectivity and increases the number of control systems. Plant convergence is essential to generating a rich database capable of providing insights based on applied intelligence.
The initial challenge is choosing a communication device compatible with the sensor or controller's physical interface. A single model is ideal because it facilitates exchange between different points in a monitoring network and reduces the overall cost of the solution. Furthermore, all field devices must be capable of communicating via their protocols through the same chosen communication device. Otherwise, it is unfeasible to manage such a wide range of devices, thus reducing the scope of the application.
Lack of flexibility is one of the main limitations of many traditional management and monitoring solutions and systems or those developed internally by the company.
They are typically designed to meet a specific set of requirements or types of readings, which can make them difficult to adapt to changes. Additionally, they don't allow for rapid and dynamic changes and are unable to predict and notify failure events predictively and proactively in real time. This can result in operational inefficiency and, ultimately, non-compliance with the SLA (Service Level Agreement).
Bridgemeter an IIoT (Industrial Internet of Things) Cloud solution developed by Above-Net , solves all these challenges. Its flexible architecture allows communication with a variety of devices with different interfaces and protocol support, making it compatible with any sensor, whether analog or digital, or device, regardless of its controller.
The key to Bridgemeter's flexibility is its 100% customizable interface and layered architecture. This allows for the structured separation of connection, data, and process functionalities, ensuring interoperability and convergence on a single platform.
Additionally, Bridgemeter offers more than 150 types of protocols, allowing the application of the Plug and Play concept to any equipment or sensor.
Intelligence for more efficient operation and maintenance
But interoperability is just the beginning. Bridgemeter also offers a number of other benefits that make it a valuable tool for operations and maintenance teams.
One of these benefits is the ability to anticipate failures and report them in real time. This is possible thanks to intelligent rule configuration, which allows Bridgemeter to continuously and autonomously manage operations. This intelligence empowers maintenance teams to act even before a customer calls or the control center detects an issue, saving valuable time and resources.
Bridgemeter also integrates an automated task management system for triggering field maintenance processes. This means maintenance tasks can be scheduled and managed in a standardized manner, reducing downtime and improving operational efficiency.
Furthermore, Bridgemeter is compatible with SCADA systems, adding value and intelligence to operations and transmitting information in real time to legacy systems. The data collected and stored in a structured format can be analyzed by BI or other market tools, providing valuable insights that can be used to improve efficiency and productivity.
Conclusion: The Reality of Predictive Maintenance and Operational Efficiency
With the implementation of Bridgemeter, the paradigm of predictive maintenance and operational efficiency is no longer distant. This robust tool proves indispensable for operations and maintenance teams, bringing with it the reality of condition-based maintenance at any collection point complexity, creating a more connected, intelligent, and resilient industry.
Interoperability, once seen as an insurmountable challenge, is now a tangible and accessible reality, ready to be exploited to the benefit of the industrial digitization process.
*The term digitization is used to define 100% digital processes that do not undergo digitalization processes.
