The Industrial Internet of Things (IIoT) is moving from vision to reality, and manufacturers want in.
Creating a connected network of people, devices, machines and assets will improve several factory processes, including:
1. Quality control: Based on the sheer volume and variety of products now being assembled and distributed, QC is becoming more challenging every year. As a result, rather than relying on humans for in-process inspection and quality control, for example, cameras powered by computer vision algorithms are being implemented to sense defects immediately and identify the cause.
Using smart devices for anomaly detection and automated QC processes allows manufacturers to identify and resolve failures and problems on hundreds of units in seconds, rather than hours, and get ahead of failures before expensive delays pile up.
2. Predictive maintenance: Like a car getting its oil changed every three months regardless of how much it’s been driven, industrial equipment is often serviced on a fixed schedule, no matter the operating conditions or hours it’s been through. When equipment servicing is only scheduled based on a calendar or time model and performance variables are not considered, this can result in increased labor costs and creates the risk of unexpected and undiagnosed equipment failures. Once outfitted with sensors and networked with each other, devices can be monitored, analyzed and modeled for improved performance and service
3. Demand-driven production: Errors in estimating consumer demand lead to lost revenues, through either stagnant inventory or lost sales. Instead of producing goods reactively, manufacturers can achieve real-time demand visibility by connecting consumer purchases and industrial IIoT.
4. Safety: Even though many different devices, machines and people move around a manufacturing floor, sensors will allow everything to be interconnected. Obstructions or safety issues can be detected immediately, employees alerted to avoid, or equipment shut down.
IIoT will not flourish, however, until manufacturers adopt more secure and highly reliable network infrastructures to ensure the interconnected sensors, devices and machines operate flawlessly and in real time.
IIoT Connectivity and Network Requirements
Artificial intelligence in a factory requires all devices to be connected in a secure manner, enabling both edge computing for real-time decisions and cloud computing. The typical hub-and-spoke architectures of cellular and Wi-Fi will no longer work in an environment where all devices, both fixed and mobile, need to be connected together in a dynamic, self-healing and resilient architecture.
Robots, forklifts and manufacturing machines all need to be connected to be monitored for efficiency in real time to avoid downtime, direct robots to store the finished goods in the right location, and monitor the forklifts to send them to the right location for pickup and shipping – all while monitoring for machine health.
Typical hub-and-spoke technologies require line of sight, which is not always possible in such a dynamic environment, requiring a manufacturer to update to an IIoT-ready network that is mobile, reliable, scalable, and future-ready.
- Mobility is essential. Everything in a manufacturing environment – people, assets, devices and machines – is constantly moving, and the network must be able to move with its environment in order to be truly functional.
- The need for reliable connectivity is critical: All devices and machines (mobile and fixed) must communicate seamlessly; providing an uninterrupted data flow is critical to a safe and productive environment.
- Scalability and future-proofing mean that a network can grow with a business over time without affecting network traffic – more devices and nodes can be accommodated without impacting network performance and reliability, now and in the future.
- The need for capacity on all networks will continue to increase, especially as more IoT devices join a network and demand for data grows. Network traffic will creep from kilobytes to megabytes to gigabytes, so having a network infrastructure that can support that growing demand is imperative.
Preparing for the Future: Best Practices
First, focus on edge computing and the cloud. Automated applications and connected devices require both edge computing for real-time decisions and cloud computing for network-wide monitoring and optimization.
Edge computing provides machine learning, which takes into account historical machine performance to optimize the machines, so every IoT device can perform more efficiently; additionally, with automation these improvements can be made in real-time. Cloud computing simplifies network monitoring; further, having the perspective of historical performance enables real-time optimization of the entire production floor (people, processes, and systems).
Next, focus on a converged network infrastructure that allows you to connect all your devices – not just today, but also 10 years from now, when the manufacturing floor will look very different. It’s important to invest in a communications infrastructure that can grow with a business, giving a manufacturer the ability to benefit from cost and efficiency improvements.
Finally, remember that plenty of new applications on the horizon aren’t yet on manufacturers’ radars, so it’s ideal to have a network that can increase its capacity in order to handle the application requirements and data capacity of new future solutions. A network that can scale also can handle more devices as they get added to the IIoT, ensuring that the network doesn’t slow down as more devices join it.
About the author: Shawn Lemley is Director of Sales, Industrial Markets, for Rajant. He has more than 25 years of experience with wireless/satellite communications and complex networks. He can be reached at [email protected] or on LinkedIn. Follow Rajant on LinkedIn or Twitter for more information.
Edited by
Ken Briodagh
