Data Connectivity How the IIoT is Changing Manufacturing

Related Vendors

Taiwan Machine Tool & Accessory Builders' Association (TMBA)

Wuxi InfiMotion Technology Co., Ltd.

Industry 4.0 significantly enhances the productivity and quality of traditional manufacturing and automation practices. Data connectivity is the key to success in this process.

The first computers revolutionized factory automation at the end of the 1960s. They ushered in an era of computer-aided design (CAD), consistent manufacturing of complex components, increased automation through programmable logic controllers (PLCs), and higher productivity. This period is considered the third industrial revolution, following the impact of steam engines, and after machine tools, electrification, and the internal combustion engine boosted productivity.

The next phase of the revolution is now in full swing: Industry 4.0 is introducing automation of traditional manufacturing and automation practices on a larger scale. This involves widespread machine-to-machine communication (M2M), edge computing, and the transformative potential of artificial intelligence (AI) and machine learning (ML).

Gallery

Gallery with 5 images

All of this is coordinated through the Industrial Internet of Things (IIoT). Its data connectivity, in turn, forms the foundation for Industry 4.0. Through wired and wireless/radio-based networks connecting machine tools, PLCs, sensors, distributed computers, industrial PCs (IPCs), and the cloud, every part of the factory can collect and process data and exchange information with every other part as well as the internet. The availability of this information source enables developers to revolutionize the manufacturing of all kinds of products—from cans to vehicles, screws to smartphones, and jigsaws to jet engines.

Bridging the Gap Between Development and Manufacturing

During Industry 3.0, development and manufacturing benefited from digital automation. However, there was no connection between the two, so they worked more in isolation from each other. Engineers took CAD outputs from the design office and used the information to manually program machine tools in the factory. Apart from being labor-intensive and error-prone, this separation between development and manufacturing prevented any possibility of refining a product design for easier, more cost-effective, and faster production.

Today, the IIoT bridges the gap between the IT networks used for development (Information Technology) and the OT networks used for factory automation (Operating Technology). Through M2M communication, development computers can communicate with machine tools to directly program them for part production. Conversely, machine tools can communicate with development computers to inform them about bottlenecks in the manufacturing process. This allows products to be redesigned for easier manufacturing without compromising functionality.

The free flow of information enables developers to design products that can be manufactured quickly and cost-effectively without compromising quality and minimizing waste. Additionally, machine tools can feed manufacturing information back to the design office to ensure that the next product iteration includes improvements to make processes even more efficient and increase productivity. A central computer can leverage all design and manufacturing data to determine the best method for producing future products that are durable, easy to repair, and easy to recycle at the end of their lifecycle.

Unite Wired and Wireless Connections

Industrial Ethernet is a proven networking technology for factory automation. It is robust and reliable and supports established industrial automation profiles such as Ethernet/IP, Profinet, and Modbus TCP. The wired technology will likely continue to form the backbone of the factory communication network in the coming years.

The downside of Industrial Ethernet is that expanding the infrastructure can be expensive and disruptive. Cabling and connections need to be housed within the building, and the associated electronics for managing the protocol must also be installed. Managers can justify this when adding new large machine tools or production lines—but it is a less practical solution when sensors need to be added to monitor machines and conditions, to track the movement of parts or assemblies in the factory, or to transmit design and manufacturing data to the cloud.

For these applications, wireless connections like Bluetooth LE, low-power Wi-Fi, and cellular-based IoT (NB-IoT and LTE-M) are more practical alternatives. The protocols are based on international standards and are continuously updated to introduce new features as IoT evolves. The sensors powered by these wireless techniques are cost-effective, compact, easy to install and configure, and can be powered by batteries for months or even years.

Bluetooth LE is suitable for mesh networks to ensure that hundreds of sensors can communicate from one end of the factory to the other. Low-power Wi-Fi can be used to power sensors with higher bandwidth needs (e.g., cameras) and is also useful as a location technique to keep track of assets. Cellular-based IoT provides a long-range communication protocol for gateways that collect information from sensor networks and transmit it to the cloud.

Close Monitoring With ML

To ensure productivity and quality, detailed process control is required. Wireless sensors and cameras can monitor machines and measure finished parts to detect minor deviations in the product and correct the process before tolerance is exceeded. Beyond the actual manufacturing process, many other factors can affect productivity and quality, so additional sensors can monitor aspects like vibrations, temperature, humidity, and air quality—all of which can negatively impact a manufacturing process.

However, continuous and large-scale manufacturing generates a massive stream of sensor data. Much of this data will not change—sending it to computers for analysis is time-consuming, costly, and energy-intensive. Instead, today's powerful wireless system-on-chip (SoC) and system-in-package (SiP) components from Nordic and other providers include powerful embedded processors and ML software that help detect significant deviations and forward only this information for further action.

Nordic's nRF52 and nRF53 series multiprotocol SoCs contain Arm Cortex-M4 (nRF52) and Arm Cortex-M33 processors (nRF53). They support Edge Impulse's TinyML—an optimized form of ML supported by compact, battery-operated sensors.

Avoid Externally Caused Problems With ML

ML also helps to avoid problems caused by external factors—such as increased humidity from employees arriving at the workplace, airflows from open windows and doors, and temperature fluctuations throughout the day and night. Machine settings can then be adjusted before these factors affect the process. Finally, specialized vibration and acoustic sensors can monitor machine tools to ensure they are in perfect condition. Unusual vibrations, temperature rises, or increased power consumption can be reported before a failure occurs, allowing for early maintenance and preventing unplanned and costly production downtime.

IIoT in Action

Nordic's multiprotocol and cellular-based IoT solutions are used worldwide for IIoT applications. The recently introduced low-power Wi-Fi series nRF70 is being integrated into asset tracking devices that will soon hit the market.

Modbus Cloud Connect from Grandcentrix enables all devices running the Modbus RTU industrial Ethernet protocol to wirelessly connect to the cloud using cellular-based IoT. This uses Nordic's low-power SiP nRF9160. Modbus RTU is a common industrial automation protocol for M2M communication that allows for the reporting of manufacturing data or maintenance issues to a central device or server.

Similarly, the IoT gateway Prylada from Tymiq uses the nRF9160 for LTE-M connectivity between the device and a cloud platform. The gateway offers numerous connection interfaces through which telemetry data from a variety of sensors is collected, including temperature, humidity, light, liquid leakage, air quality, and motion detection. It uses the Arm Cortex-M33 processor of the SiP to monitor the sensors and gather the relevant data.

TZero uses the nRF9160 to provide long-range wireless connectivity and computing power for its MachineMailbox tool for network connecting machines. According to TZero, the solution turns any product into a connected IIoT sensor/machine solution without configuration. MachineMailbox uses the Arm Cortex-M33 processor of the nRF9160 to manage and execute the complex proprietary algorithms needed by multiple sensors, as well as to send the data to the cloud.

The Atom from Atomation is designed for predictive maintenance and is equipped with Nordic's nRF52840 SoC. It features a range of sensors that monitor machine variables such as temperature, vibration, humidity, pressure, distance, tilt, and impact. The Atom utilizes the computing power of the Arm Cortex-M4 processor of the SoC to determine if the sensors detect abnormal values before transmitting the data.

The IIoT Will Usher in Industry 5.0

Both Industry 3.0 and 4.0 utilize digital data processing to increase productivity. The difference is that earlier computers helped humans make better decisions, while Industry 4.0 uses the same information (and much more) to optimize processes largely without human intervention.

Wireless technology reduces the costs of networking in Industry 4.0 and facilitates the reconfiguration of networks when manufacturing is modified and expanded. The long-term savings through better product design and improved manufacturing are significant, as productivity increases and product defects decrease.

Industry 4.0 still has some time to develop. However, the vision for Industry 5.0 is clear: sustainability. According to the EU, the next leap will "take the industry beyond efficiency and productivity as sole goals and reinforce the role and contribution of industry to society, whilst respecting the production limits of the planet." This is a commendable goal, but a great challenge. Yet, as with the challenges of Industry 4.0, the IIoT will help us in solving these.

About the author

Lorenzo Amicucci is a Business Development Manager at Nordic Semiconductor in Oslo, Norway. He supports Nordic's sales team in developing new solutions in collaboration with leading partners and customers from various industries. Before joining Nordic, he worked in the telecommunications industry, focusing on radio/microwave network equipment, and served leading customers providing critical radio infrastructure. Amicucci studied at universities in Italy, China, and Sweden, and holds a master's degree in electrical engineering from Politecnico di Milano, specializing in analog/RF IC design.