Modern industry is a complex ecosystem of equipment, sensors and systems, each with its specific interface and communication protocol. This diversity is the 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 – for simpler panels, or even embedded controllers which in turn have different communication protocols such as Modbus, MQTT, OPC-UA, EtherCAT, among others. The big challenge is to aggregate all the application variations in a centralized and unique way.
Industrial Interoperability with Bridgemeter : Integrating Sensors, Controllers and Systems in IIoT with Flexibility
Integrating different devices, protocols and systems can be complex. Some tools available on the market focus on a specific application or equipment, which restricts connectivity and increases the number of control systems. The convergence of a plant is essential to generate a rich database that is capable of providing insights based on applied intelligence.
The initial difficulty is choosing communication equipment compatible with the physical interface of the sensor or controller. A single model is ideal as it facilitates exchange between different points of a monitoring network and reduces the total cost of the solution. Furthermore, all field equipment must be able to communicate through their protocols via the same chosen communication equipment. Otherwise, it is unfeasible to manage such a wide range of equipment, reducing the scope of application.
The 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 it difficult to adapt to changes. Additionally, they do not allow quick and dynamic changes and are unable to anticipate and notify failure events in a predictive and proactive way in real time. This can result in operational inefficiency and, ultimately, failure to meet the SLA (Service Level Agreement).
Bridgemeter , an IIoT (Industrial Internet of Things) Cloud solution, developed by Above-Net , solves all these challenges Bridgemeter 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% parameterizable interface and layered structured architecture. This allows the separation of connection functionalities, data and processes in a structured way, 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 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 notify them in real time. This is possible thanks to the parameterization of intelligent rules that allows Bridgemeter to take care of the operation continuously and autonomously. This intelligence empowers maintenance teams to act even before the customer calls or is noticed by the control center, saving valuable time and resources.
Bridgemeter also integrates an automated task management system for triggering field maintenance processes. It means maintenance tasks can be scheduled and managed in a standardized way, reducing downtime and improving operational efficiency.
Furthermore, Bridgemeter is compatible with SCADA systems, as it adds value and intelligence to the operation and also transmits information to legacy systems in real time. The data collected and stored in a structured way can be analyzed by BIs or other tools on the market, 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 to be indispensable for operation and maintenance teams, bringing with it the reality of maintenance under condition whatever the complexity of the collection point, with 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 to benefit the industrial digitization process.
*The term digitization is used to define 100% digital processes that do not undergo digitization processes.
