What are the benefits and challenges of integrating PLC programming with IoT, cloud, and AI technologies?

IoT and IIoT are fairly broad terms. For the purpose of this contribution, I'll define it as devices that communicate over Ethernet/IP or Profinet depending on the PLC platform. The opportunity for PLCs lies in being able to communicate with other devices on the same and upper levels - PLCs, SCADA, MES, and ERP systems. When it comes to field devices, more of them are being enabled with network protocols which unlocks the capability of extracting data into a PLC. Data is a significant component of any manufacturing operation when implemented correctly; in almost every instance, getting that data is heavily reliant on the networks within the facility.

IoT and IIoT have expanded in the past few years as marketing terms for sensor communication with the main purpose being data collection. IoT devices are typically wireless devices using communication methods in more efficient formatting for things like cellular networks with protocols such as MQTT instead of industrial protocols like Modbus.

With IIoT Gateways you can also access, program and download/upload from a PLC. And using the right solution can guarantee a very low cybersecurity threat. This brings remote maintenance into the game, which can save tons of money and time and reduce downtime even more.

Integrating IoT with PLC programming offers real-time data exchange between devices, enabling better monitoring and control. For example, in industrial automation, IoT sensors connected to PLCs can provide data on equipment health and performance. This facilitates predictive maintenance, reducing downtime. However, challenges may arise in ensuring the security and reliability of IoT data, requiring robust encryption protocols and secure communication channels.

Are wireless sensors really becoming a thing because I was wondering how industries would respond to using cellular communications in its processes?

Cloud vs on-prem vs edge is a constant debate within the industrial automation community. The reality for a manufacturer is that they should understand and evaluate all options as they're not all made equal. If you have on-prem hardware, you can easily prototype solutions, but it's costing to maintain, upgrade, and keeping it secure. If you're using close services, you're probably spending more for a variety of services, but you're able to easily scale up down, and to use apps that aren't available locally. Edge solutions help in various ways - buffer data, provide a faster response time, host apps that are production critical, etc.

Cloud integration with PLCs allows for centralized data storage, analysis, and remote access. For instance, cloud platforms can store historical PLC data for trend analysis, and engineers can remotely monitor and troubleshoot PLC systems. The challenge lies in ensuring low-latency communication between PLCs and the cloud, especially in scenarios where real-time response is critical. Bandwidth considerations and potential security vulnerabilities must also be addressed.

First thing: you should never perform a PLC firmware update remotely unless it is a last resort. Could services should be used alongside PLCs to enhance data analysis, storage, and occasionally operation. Deployment of a SCADA system on a AWS server is a prime example of how cloud systems can be used effectively to host applications involving remote monitoring and control. If you’re using a cloud system connecting to your PLCs, make sure you have a robust and secure network architecture.

Most PLCs have very proprietary operating systems and much less computing power than a conventional computer, but are designed for use in real-time conditions. Running AI networks directly on the PLC is therefore usually impossible and additional edge devices are required. If you use PC-based PLCs, such as Beckhoff, it is however possible to run an ONNX network directly on the PLC. This enables image processing including AI directly in the real-time environment of the PLC. The use of AI directly there opens doors to very exciting applications in process automation.

AI algorithms can analyze historical PLC data to predict system behavior and optimize control strategies. However, challenges include the need for substantial computing power, especially for real-time AI applications. Additionally, the integration of AI models with PLCs requires careful consideration of compatibility and the potential impact on system stability.

When you mix PLC programming with AI, it's like giving your factory a brain boost. Suddenly, your machines can predict when they'll need a check-up, figure out the best times to ramp up production, and even adapt on the fly to changes in the environment. But, getting there isn't a walk in the park. You've got to make sure all your data plays nice together, train your systems properly, and ensure that the decisions your AI makes are safe and reliable in real-world situations. It's a bit of a juggling act, but if you can nail it, the rewards are huge for making your factory smarter and more efficient.

Integrating PLCs with IoT technology can prove to be a challenge, as IoT is a new methodology for doing things, and a lot of off the shelf PLC hardware won’t directly support it, however, manufacturers are implementing “IoT Functionality” in a lot of their devices at an incredible rate. In the interm, there are hardware and software bridges we can employ to establish compatibility. Also, all of these technologies require a different skillset, or more advanced knowledge of different technologies branching away from standard industrial applications, to which your staff will have to learn and understand before any type of development happens.

Cybersecurity must be a top priority in any connection of any industrial device that plays an important role or is connected to other devices. Before starting any IoT or cloud integration in your system, always make sure that the necessary certificates, standards and procedures (like NIS2 which is a must for critical infrastructures) are included in the process.

In as much as there are concerns of cyber security, I believe there are sufficient controls and standards to achieve a reliable and relatively secure PLC environment with high integration of Cloud, IoT and AI. I have worked in Oil & Gas Industry before where the safety of human being is critical. Armed theft, chemical poison and fires have been documented before in the pipeline company that I worked for. I normally advise planners in this sectors to use as much technology as possible to reduce direct or close human interaction with oil tank firms. AI, Cloud and IIoT give a better efficiency and RoI for remote and cloud monitoring far way from the risk of proximity to the equipment and site than on premise and edge combined.

Always remember that a "Cloud" is someone else's Hard Drive where your data is kept or copied to. Leaving your equipment open to the Internet without firewalls, VPNs, and other protections can leave you to the mercy of hackers, just like what happened to the oil pipeline on the East Coast a year or so ago

Technology come with pro's and cons. Integration of IoT ,AI give benefit of high productivity, easy access to data , great analytics, better maintenance and stock utilisation but to get all these benefits we should Always keep PLC in DMZ or behind the firewall...directly exposing the PLC can lead to catastrophic of plants in view of cybersecurity. We should always play between Risk to take vs Features to use. Using edge gateways/devices provide some benfits instead of exposing PLC directly. Creating a network and exchanging data should use cybersecurity IEC62443 ISA99/95 standards to be secured. If using cloud from vendor be aware you are using someone's else disk to store data. "Anything is secured till it is not breached"