Energy efficiency is a prime directive of Industry 4.0 driven by the need to improve manufacturing productivity and lower costs—all while reducing the environmental impact. These smart factories require a range of components, including power management ICs (PMICs), processors and sensors to handle the task of monitoring, collecting and analyzing data to determine the best way to optimize production processes and reduce energy consumption.
“Processors, PMICs and sensors all play a crucial role in improving manufacturing productivity, while helping to meet sustainability goals,” said Raj Khattoi, senior director of sensor systems and IoT at Infineon Technologies.
“Powerful processors enable real-time data processing, complex analytics and automation that are needed in smart manufacturing,” Khattoi said. “They help in optimizing processes and increase efficiency. And by improving quality control, enabling predictive maintenance and reducing downtime, they increase overall energy requirements to help meet sustainability goals.”
Khattoi explained that processors work in tandem with PMICs, which efficiently regulate and distribute power, reducing carbon emissions and lowering electricity costs.
Sensors are also an integral part of smart manufacturing, he added. “They provide real-time data or various parameters like temperature, pressure, humidity, vibration and more. These sensors help increase efficiency, prevent equipment failure and enhance productivity, while minimizing energy consumption and material waste, hence improving sustainability.”
Increased demand for energy-efficient manufacturing continues to drive advances at the component level. But it also translates into deployment challenges.
“Achieving the goals of Industry 4.0 will require deploying smart sensor platforms to monitor assets. Given the deployment challenges the industry has seen for these systems, one of the most important features will be simplifying the deployment of these intelligent systems,” said TDK USA Corp. CEO Jim Tran.
“Thus, how can we enable these devices to provide actionable information with minimal user interaction during setup?” Tran asked. “The goal is to deploy and utilize the smart sensors’ capabilities and intelligence within robust networks to enable users to mount these devices on the asset, configure itself and begin reporting back to the system or individual in a rapid fashion.”
Driving increased productivity, which overlaps into environmental impact, is one of the key areas of Industry 4.0.
Part of it includes increasing automation, such as by using vision systems for product inspection and to automate safety processes, said Jeff Steinheider, VP and general manager of Industrial Edge Processing at NXP Semiconductors.
“When there are a lot of manual processes, it’s very difficult to know exactly what’s happening in every stage of your factory,” Steinheider said.
By adding more sensors and information points, you can create a digital twin of the factory and have a much better understanding of what the factory’s doing. With real-time information, you can also understand what it’s doing at a much more granular level, he added.
This can help in several areas, such as capacity planning when checking for a supply gap. “I don’t want to build ahead everything else if I’m missing the ‘golden screw,’” Steinheider said. “It’s wasting material.”
Application factors for product development
Component manufacturers agree that it’s important to consider both the features of the new device and the requirements of the end customer when developing new devices that will be used in manufacturing environments to optimize and automate production processes and improve efficiency and power consumption. Features range from intelligence and connectivity to safety and security.
“Understanding the specific needs of the application drives the system design,” Tran said. “This includes the type of sensing, operational environment factors, rate of sensing and providing actionable insights, network integration and power source requirements. These and other factors drive the architecture and specific component design/selection to assist in a solution.”
In terms of power management, it’s “a support function that exists within a system context,” according to Tom Truman, VP and general manager of Performance Digital Power at Renesas Electronics. “The system definer typically focuses on the end customer use cases and designs the system to support those uses. Power management requirements, in most industrial use cases, are derived from the system objectives rather than being directly visible to end users.”
Infineon’s Khattoi said the right power architecture is key to reducing energy costs and environmental impacts. “From a device development standpoint, it is important to optimize power consumption, edge processing power and connectivity.”
However, he added that “the overall strategy should be focused on improving factory efficiency and helping meet their sustainability goals. A combination of sensors and edge computing capabilities including highly efficient algorithms can also help increase productivity and efficiency and reduce overall energy costs. An iterative development process, especially on the processing side, will allow customers to get the best performance possible.”
Transforming factories with sensors
Sensors in smart-manufacturing applications enable the continuous and real-time collection of data to monitor the operational status and condition of equipment.
Sensors contribute immensely to the transformation of industrial factories and are critical in producing and collecting data, impacting every step of factory automation, said Simone Ferri, general manager of STMicroelectronics’ (STMicro’s) Analog, MEMS and Sensors Sub-Group.
“In the most efficient factories, companies are using sensors to optimize efficiency, increase productivity, improve safety and advance security,” Ferri said. “Our last sensor solutions with edge computing play an important role in implementing enterprise execution solutions in a sustainable way because processing data locally helps offload the processors and cloud.”
He said this can drastically reduce the infrastructure’s requirements and its energy consumption at the system level. Sensor local processing can also ease the management of data privacy and decrease the latency of the overall system.
Machine learning (ML)/AI is expected to play a bigger role in smart factories and factory automation.
Sensing is fundamental to digital transformation as it enables an understanding of the physical world in the digital domain, Tran said. “Practically speaking, increasing the ability to include AI in these sensors to create smart sensor platforms is critical to enabling digital transformation.”
Adding intelligence to sensors changes what these devices can do, from basic sensing to entirely new functionalities. As an example, TDK acquired Qeexo and its AutoML tool to enable non-ML experts to easily create ML applications as part of its smart sensor platforms.
“With the addition of intelligence at the edge, these smart sensor platforms will provide actionable information to improve the efficiency of assets, extend equipment lifetime and significantly reduce costs by reducing maintenance costs and eliminating unplanned downtime,” TDK’s Tran added. “To that end, edge-based platforms will also reduce power consumption, latency, privacy issues, etc., relative to purely cloud-based solutions.”
Similarly, Ferri believes “the most successful state-of-the-art smart factories are using ML and AI building blocks to help the factory collect data through sensors by monitoring processes, products and assets.”
MEMS sensors, equipped with ML capabilities, can sense and analyze many parameters and make smart decisions that can then help improve efficiency, reduce cost and increase productivity, he added.
“The latest MEMS sensors generation, equipped with ML capabilities, high accuracy (including wide bandwidth) and with an open ecosystem shortening the time-to-solution in the factory, can sense and analyze many parameters and make smart decisions in the sensor, offering the best system power efficiency partitioning.”
One example cited is the vibration monitoring of machines that can provide information about operational conditions. In this case, the MEMS sensors can capture vibration frequencies up to several kilohertz of bandwidth, as part of condition monitoring and predictive maintenance, which can help minimize line-down time via early detection and treatment of potential problems with little impact on energy consumption.
However, a variety of sensors will be used together to collect a wide range of data for factory optimization.
“Smart sensor platforms for Industry 4.0 will include a variety of sensors depending on the specific machine/activity they are monitoring,” Tran said.
Tran cited several examples, including accelerometers for machine vibration detection, temperature sensors for detecting overheating and operation faults, humidity and other atmospheric condition sensors, and magnetic sensors and microphones to detect sounds related to anomalies like scraping.
Khattoi expects that multi-modal sensors with the ability to provide comprehensive data to the processors, including for predictive maintenance, will become important in the future, along with miniaturization, robustness and enhanced durability to withstand harsh conditions.
Processor applications and features
Processors play a big role in factory automation, enabling the efficiency and intelligence in smart factories and addressing real-time workloads. They also contribute to the safety and security of the systems.
Embedded processing is used in a wide range of applications that call for a mix of features. These can range from handling low-power processing and data rates to computationally intensive processing and high data-rate requirements.
Energy efficiency is also key as smart manufacturing systems often operate continuously, said Marc Dupaquier, managing director of Artificial Intelligence Solutions, General Purpose Microcontrollers Sub-Group at STMicro. “Processors must help minimize energy consumption and extend the lifespan of devices, contributing to overall sustainability and cost-effectiveness.”
Embedded processing in smart factories involves integrating microcontrollers and microprocessors directly into industrial equipment and systems, and plays a crucial role by enabling efficient and intelligent automation, Dupaquier added.
“Smart means being able to exercise real-time monitoring and control of machinery, allowing for precise and responsive adjustments based on data from the sensors. This helps optimize production processes, minimize downtime and improve overall efficiency.”
In addition, the data can be used to identify patterns, detect anomalies and derive actionable insights for predictive maintenance, Dupaquier said.
Processor manufacturers also believe that edge computing will become even more important in the future, along with computing performance and security.
“The most important features for processors in these applications are high performance, edge computing capabilities and robust security,” Khattoi said.
Edge computing will continue to become more important to reduce latency and enable real-time decision making, along with ML algorithms optimized for the edge (TinyML) and robust security to protect against cyber-attacks, he added. Dupaquier agreed.
“By bringing computational capabilities and AI techniques closer to the data source, factories can reduce latency and bandwidth requirements,” Dupaquier said. “This enables real-time decision making at the edge, minimizing dependence on cloud-based processing and facilitating faster response times for critical operations. It also reduces the energy demands since edge processing requires less data to be transmitted and processed by cloud computing infrastructure.”
For embedded processors, key features include a range of processing power to handle the complexity and demands of the individual part of the manufacturing environment where they are embedded, such as the ability to execute real-time control algorithms, perform data analysis, run edge AI algorithms and handle communication efficiently, according to Dupaquier.
As an example, STMicro offers high-performance MCUs and an MPU with dual cores with the top of the range STM32H7 MCU achieving up to 3224 Coremark. STMicro also provides developer tools to port edge AI solutions onto the majority of its MCUs for a range of expertise in AI development.
NXP is incorporating neural processing units in many devices and running ML at the edge, so some of these devices are gathering information from the machines, making decisions and applying these in real time, Steinheider said. “You want to make sure that you’re getting responses fast enough to keep things running at the rate that everyone wants.”
Real-time response is critical for factory-automation capabilities.
“If you’re working with a PC or a consumer device and you press a button and it takes an extra half a second or a quarter of a second for an action to happen because of the operating system and how the system was architected, that’s not important,” Steinheider explained. “But in a factory setting, it’s incredibly important that machines get regular communication on regular cycles and that you respond to every message, so having the networking capabilities that ensure delivery of messages, having the tight synchronization of all the systems and having the real-time response of the processors is really important.”
In some of these applications, like driving big motors, better processing can deliver improvements like faster cycle times within some of the industrial networks.
“It allows the machines to run at a higher rate, so that drives productivity and increases efficiency,” Steinheider added.
Safety and security are also considerations with new processor designs.
Embedded processors enable seamless connectivity between different components and systems within the factory environment and to the cloud, contributing to the security and safety of smart factory systems, Dupaquier said.
Security becomes more critical as smart manufacturing systems become more interconnected,” he added. “Embedded processors must include robust security features, including encryption, authentication mechanisms, secure boot and secure firmware update capabilities. This ensures protection against cyber threats and helps safeguard sensitive data and intellectual property.”
Security has become almost of prime importance in the last couple of years, driven by the Industry 4.0 path of connecting everything and being able to connect to the cloud, Steinheider agreed.
In a world of industrial IoT where everything is networked together, there are a lot of different attack points, according to Steinheider.
“We’re seeing a push for everything to be secure because it is all going to be interconnected,” he said. “So having the capabilities like secure boot, the ability to authenticate messages and the ability to have keys that are embedded in the products to ensure they are authentic products signed off by the manufacturer and that someone hasn’t been able to slip something in or install malware on the device is incredibly important.”
Also important is being able to recover from attacks and having ways to recognize that there’s an issue, he added.
Power management
Power management is also taking on a fundamental role in Industry 4.0 and factory automation to meet energy-efficiency requirements. Power management solutions monitor energy sources in real time to optimize energy consumption, while ensuring a safe and reliable power supply.
“Generally, the most important power management capability is producing a clean, well-regulated power supply to the devices being powered, across a wide range of environmental conditions, such as temperature, humidity, shock/vibration, noisy input power, etc., and throughout the end equipment’s intended useful life,” Truman said.
“Energy-efficient power conversion is the second most important capability,” he added. “Beyond those two fundamental needs, the specific application dictates the priority of features and functions.”
Khattoi said “devices that maximize energy conversion to reduce power leakage are absolutely important in this space.”
Other features include dynamic power scaling, as well as power monitoring and control, which includes PMICs with integrated power monitoring features, he said.
This article was originally published on EE Times.
Gina Roos is Editor in Chief of Electronic Products. She previously founded Electronics Advocate, an online magazine covering design and supply chain issues in the electronics industry. It was sold to MMG Publishing UK in 2010. Gina also co-founded EPS News, which AspenCore, a unit of Arrow Electronics, bought in 2017. She has covered the electronic components industry, supply chain issues, electronics purchasing strategies, technology trends and electronics distribution for longer than 30 years. She served as a contributor to EE Times’ eeProductCenter component website for 13 years.