Discover the innovative game plan to manufacture like a well-oiled machine

The Internet of Things (IoT) focuses on interlinking devices to create cooperative networks. This trend marks a departure from traditional, unified machinery to more fragmented systems. IoT emphasizes miniaturization, breaking down larger systems into multiple smaller components. This approach simplifies network management, upgrades, and maintenance.

The Industrial Internet of Things (IIoT) plays a crucial role in the manufacturing sector. A key aspect here is IoT analytics. Manufacturers rely on data to assess their operational performance and identify bottlenecks. This information is key to enhancing business efficiency. Integrating IIoT with artificial intelligence can further streamline this process through automation.

However, the application of IIoT technologies demands thoughtful consideration. Innovatively combining various technologies is a strategic approach to staying ahead in the competitive business landscape. As we move through 2024, it’s vital to understand the current manufacturing IoT trends to use the potential benefits for your business fully.

1. The era of connectivity

One of the exciting opportunities for manufacturing in the Internet of Things is the potential for enhancing bandwidth capacity. This presents us with a valuable area for growth and improvement.

This concerns the volume of data exchangeable among devices within a network. Enhanced data transmission capacity bolsters system efficiency, particularly in diverse setups. Network speed is crucial for real-time applications and edge computing. Yet, high bandwidth might not be imperative for less urgent data transfer. It's crucial to assess your manufacturing needs to select optimal connectivity solutions.

Wired IIoT offerings

For robust and rapid connectivity, wired IIoT networks are superior. They are ideal for integrating numerous IoT devices. Protocols like EtherCAT, Ethernet/IP, and Profinet are common in these setups. While USB connections offer limited speed and range, category cables expand this scope. For longer distances, fiber optic cables link industrial sites miles apart.

Wired solutions, being more established than wireless, provide dependable performance and resistance to interference. The major drawback is their physical nature. Installation can be space-consuming, environmentally constrained, and time-intensive. Additionally, the cost of cabling is an extra consideration.

Wireless IIoT offerings

For flexibility and straightforward installation, wireless networks are more advantageous. Despite their potential for fluctuating performance, the reliability of wireless connections varies with the type of technology employed.

Several wireless technologies are emerging and gaining prominence in 2024 for manufacturing IIoT systems:

• Bluetooth stands out for its efficiency over Wi-Fi and Zigbee, particularly for portable, battery-powered devices. However, its energy-saving nature limits data transfer volume. BLE also faces potential interference within the 2.4 GHz frequency band, which it shares with traditional Wi-Fi networks, potentially impacting device performance.
• Zigbee offers an alternative for battery-powered sensors with low data requirements. It operates through interconnected nodes, forming multiple pathways. This system requires a central hub coordinator, adding complexity to the setup.
• Wi-Fi, particularly with 5 GHz access points, is increasingly viable for machine sensors in industrial settings. These access points facilitate high-speed connections to devices as far as 190 feet away. For comprehensive coverage, deploying multiple beacons across the factory floor is effective. This setup is particularly beneficial for IIoT sensors that are cable-powered and stationery.

As it eliminates the need for additional communication cabling, setting up IIoT sensors to monitor machinery becomes more straightforward. High-speed Wi-Fi connections will emerge as a leading solution for IIoT applications in factories, particularly in 2024.

2. Proactive system upkeep and insight analytics

In manufacturing, ensuring equipment reliability can lead to substantial cost savings and operational efficiency. Predictive maintenance, powered by artificial intelligence, can lead to substantial savings for businesses. Yet, the effectiveness of industrial machine learning algorithms is contingent on the availability of high-quality data from the machines being monitored.

Industrial Internet of Things sensors gather data across a network of machines, facilitating the identification of equipment requiring preemptive maintenance. These sensors also track variables like temperature, vibration, and power consumption to predict future failures.

3. Streamlined automation in quality control

IIoT networks have transformed quality assurance in manufacturing, enabling remote and automated monitoring. This advancement significantly boosts productivity and efficiency. Real-time alerts enable quicker responses to issues such as unexpected machine failures.

IIoT devices also enable real-time video connectivity, aiding artificial intelligence in automated visual inspections. This technology allows AI to identify and remove defective products from production lines before dispatch. Such AI-driven visual inspection systems rely on IoT sensors and cameras to provide the necessary observational data for decision-making processes.

4. Edge computing

Edge computing is emerging as a trend in the IIoT. Traditionally, many industries have been offloading data processing from local devices to distant servers, which, while reducing local device processing, incurs time and bandwidth costs. Edge computing seeks to do the opposite by maintaining processing as close to the source as possible.

In manufacturing, edge computing allows factory-based devices to process data locally rather than sending it away for processing. This approach is not only quicker and more efficient but also enhances security. Since data remains within the factory, it's safeguarded against external interception or recovery.

Progressive industrial firms are integrating edge computing with AI to create edge AI. This approach enables AI computations at the edge of the IoT network, close to the user, instead of relying on cloud processing. Edge AI brings real-time intelligence to industrial operations, bolsters privacy and cybersecurity, and reduces costs while continually enhancing manufacturing processes.

5. Location tracking

Location tracking, powered by IIoT technologies, has diverse applications in manufacturing. GPS is well-regarded for outdoor environments, but indoor positioning and areas with GPS interference, like densely built-up urban areas, present some hiccups. Outdoor location tracking typically benefits logistics, whereas indoor tracking is more relevant to manufacturing.

Real-time location systems (RTLS), utilizing wireless technologies such as Wi-Fi, BLE beacons, UWB, and RFID, are instrumental in manufacturing. They enable pinpointing product locations on the factory floor and tracking their journey through production. This capability not only aids in quality assurance but also supports the development of digital twin applications by providing comprehensive data.

6. Sustainable energy management in industry

The concept of motion-sensing light switches in a dark room illustrates a fundamental principle of energy efficiency – activating only when necessary. This idea is central to energy optimization in the IIoT. Beyond just lighting, the question arises: how can we optimize the energy consumption of other devices in a factory?

Energy optimization encompasses various strategies, including managing temperature control systems and industrial machinery. Optimizing energy use is environmentally beneficial and leads to substantial cost reductions.

IIoT energy optimization sensors, which monitor the electrical status and usage of devices and machines, enable factory operators to refine processes and automatically adjust energy consumption. However, this is just a fragment of the solution. Developing more sustainable manufacturing processes requires a broader approach than just employing IoT sensors and processing electrical data.

The upcoming wave of IoT in manufacturing

Acquiring and implementing IIoT devices remains feasible, and there is ample scope for enhancing existing systems. In periods of such disruption, innovation becomes crucial. While the chip shortage may constrain market expansion, businesses capable of innovatively utilizing existing hardware and resources are likely to maintain their competitive edge during and beyond the shortage, potentially leading to greater achievements in the future.

That is why having a software development team that aligns with your vision and understanding of innovation is essential.