Five edge technology trends that can improve operational insight
There are several edge technology and digital transformation trends within the industrial sector that could impact manufacturing.
Factory digitization insights
- The manufacturing sector is being transformed through digitization with key technology trends such as automation, electrification, digitization, and the connected enterprise, next generation industrial technology, and security driving investment in edge technology both hardware and software.
- These trends are enabling agile manufacturing, reducing energy consumption, enabling localized decision-making and machine health monitoring, and addressing security concerns in interconnected factory automation networks.
The manufacturing sector is being transformed through a new world of digital factories. Ubiquitous sensing and connectivity at the edge are yielding data that opens the door to new depths of operational insight. Simultaneously, key technology trends such as modular system design, localized decision making and ubiquitous sensing, are key enablers of digitization, allowing manufacturers to reduce energy consumption while driving critical business goals.
As we catalyze and re-engineer a sustainable industrial future, we can expect to see five key technology trends emerge, which will drive new investment in edge technology both hardware and software.
Across the industrial landscape more and more automation is now being deployed, via robotics and configurable systems with the purpose of increasing productivity, quality and to address workforce shortages. More automation equipment means that more hardware and software technology is being deployed. One example is seamless configurability and connectivity from the edge on the factory floor to the cloud. Unique software-configurable analogue front-ends, paired with digital connectivity technologies for direct IP addressability, are creating nimble connectivity networks for real-time automation control. This enables the concept of truly agile manufacturing which brings to life quick configurability and drives overall asset utilizations.
Electrification of the factory and the use of mixed energy sources such as renewables to reduce dependence on fossil fuels is driving a three-fold increase in energy demand. The answer is to use the energy we already have today more efficiently. For example, retrofitting boilers and furnaces to move from fossil fuels to high temperature heat exchangers. Each time a change is made new control and automation equipment is needed further up the chain and better monitoring and control within the boiler is required to operate in its zone of efficiency. Each new device will be fitted with more intelligent sensors, processing platforms and optimized machine learning (ML) algorithms to enable real time monitoring, ensuring operation in its zone of efficiency. This is driving demand for higher processing power while retaining low power consumption to enable devices run via low power supplies, such as batteries or Single-Pair Power Over Ethernet.
3. Digitization and the connected enterprise
This requires deployment of more intelligence to enable localized decision making. Industrial automation machinery now has the intelligence to dynamically respond to real-time operating conditions, based on the health and status of a network of sensors located across the factory floor. As well as enabling local optimization, this network of sensors is providing insights to centralized artificial-intelligence (AI) units that can identify manufacturing bottlenecks and points of failure and optimize manufacture cell output. This is driving the need for AI/ML and higher capability processing technologies at central control levels to process the data feeds in a fast manner.
4. Next-generation industrial technology
This addresses the new capabilities that are coming on stream to enable machine health monitoring. One example is condition monitoring, where you are ensuring the asset is operating in its zone of peak performance or efficiency, helping to maximize the life of assets. Examples include motor performance and providing motion insights on loading profiles in real time to ensure the highest efficiency operation with motor fault analysis for anomaly detection.
With the connected and interconnected factory automation networks comes the need for security. This is driving the need for features like secure boot, secure software update, authentication, and root of trust. The root of trust is a set of related security functions that control the cryptographic process in the devices as a largely separate computing unit. All connected factory devices will now require some elements of security to prevent them being identified as a vulnerability in system networks.
– This originally appeared on Control Engineering Europe’s website.