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 brings significant challenges in terms of automation, integration, and data analysis.
The control of this equipment can range from electromechanical panels to complex controllers with automated embedded systems. Remote monitoring, therefore, needs to adapt to a multitude of instrumentation options – from simpler panels to embedded controllers that, in turn, have different communication protocols such as Modbus, MQTT, OPC-UA, EtherCAT, among others. The great challenge is to aggregate, in a centralized and unified way, all the variations of the application.
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 fundamental to generating a rich database capable of providing insights through applied intelligence.
The initial challenge lies in choosing a communication device compatible with the physical interface of the sensor or controller. A single model is ideal as it facilitates the exchange between different points in a monitoring network and reduces the overall cost of the solution. Furthermore, all field devices must be able to communicate using their respective protocols via the same chosen communication device. Otherwise, managing such a wide range of devices becomes impractical, 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 generally designed to meet a specific set of requirements or types of readings, which can make them difficult to adapt to changes. Additionally, they do not allow for rapid and dynamic changes, and they cannot anticipate and notify failure events in a predictive and proactive way 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 equipment with different interfaces and protocol support, making it compatible with any sensor, whether analog or digital, or equipment, regardless of its controller.
The key to Bridgemeter's flexibility is its 100% customizable interface and a layered, structured architecture. This allows for the structured separation of connection, data, and process functionalities, ensuring interoperability and convergence on a single platform.
Furthermore, 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 range 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 notify them in real time. This is possible thanks to the parameterization of intelligent rules that allow Bridgemeter to take care of the operation continuously and autonomously. This intelligence empowers maintenance teams to act even before the customer calls or the control center notices, saving valuable time and resources.
Bridgemeter also integrates an automated task management system for triggering field maintenance processes. This means that maintenance tasks can be scheduled and managed in a standardized way, 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 way 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 regardless of the complexity of the data collection point, leading to a more connected, intelligent, and resilient industry.
Interoperability, once seen as an insurmountable challenge, is now a tangible and accessible reality, ready to be explored for the benefit of the industrial digitization process.
*The term digitization is used to define 100% digital processes that do not go through digitization processes.
