A major revolution in the field of instrumentation and control technology is well underway. Research, development and deployment activities are focused on making quantum leaps in industrial automation performance. Called Industry 4.0, this includes a new generation of low-cost wireless sensors, improved real-time data analytics and control systems, and advancements in high-fidelity process modeling. These innovations will include systems that improve industrial manufacturing efficiencies, and integrate and network subsystems across manufacturing processes.
Advanced sensor technologies: New sensors that can function under high-temperature/pressure, heavy vibration, extreme pH and abrasive conditions would greatly reduce manufacturing energy use. Improved sensors are needed to monitor steam, cooling water, waste, process flows and humidity in dry batches. New detection capabilities, especially for high temperatures, combustion/flue gas monitoring, and in-situ refractory integrity or chemical composition, would benefit multiple industries.
Big data analytics: Energy-intensive manufacturing industries are often monitored with low-accuracy or poorly calibrated sensors that generate huge amounts of unused data. Big data analytics provides an opportunity to address these issues with process monitoring, anomaly detection and adaptive control algorithms that can respond in real time. This technology can achieve optimal performance that will reduce equipment failure and optimize energy usage and other resources.
Industrial Internet of Things (IIoT): The IIoT is the nervous system of factories of the future. Advanced manufacturing means data-driven manufacturing. The adoption of IIoT in manufacturing has been slow. To overcome adoption barriers, both suppliers and end users will have to do a better job of pairing the technology with industry needs and then measuring and documenting cost savings. This will require enhancements in industrial-strength wireless networks and cyber-physical security.
Industrial controls and drives: Industrial processes are characterized by complex, time-varying dynamics, including dead times, that make the use of traditional control approaches (such as proportional–integral–derivative control) challenging. The future will bring more effective industrial controls and drive technologies that will reduce process variability. This will be accomplished through a distributed, hierarchical sensing and control architecture that integrates sensor data, advanced control algorithms and predictive analytics to improve performance.
Modeling and simulation: Process modeling and simulation are often lacking in industries such as primary metals and cement production, biomass conversion, and pulp and paper, despite their use in other industries. The use of more rigorous thermophysical models and databases will support developments around phase equilibrium calculations and calorimetric properties to support energy monitoring.
Smart energy management: The development of new technologies for energy delivery and management will include the application of advanced sensors, communications and driver interfaces. This will support data-driven management topologies that have not penetrated the broader manufacturing industry on a large scale.
The culmination of these new innovations is that manufacturing facilities will be able to turn large volumes of unused data into highly useful knowledge. Industrial pumping will be a major beneficiary of these advances since they can now become part of the automation architecture, with embedded sensors and controls. The future of industrial automation, control and monitoring is bright.