An Industrial IoT platform is a rapidly growing segment of IoT technology comprising a collection of functions for edge device management, IoT data analytics, modern sensor technologies and connectivity solutions that enhance industrial equipment and industrial operations with remote monitoring, predictive maintenance, and extensive device data analytics.
On a broader scale, an Industrial IoT platform is a key enabler of Industry 4.0, otherwise known as smart factory, which combines modern cloud computing, IIoT and AI to create intelligent, self-optimizing industrial equipment and production facilities.
When considering the Industrial Internet of Things (IIoT) from a practical business perspective, manufacturing companies that implement IIoT enjoy increased value to customers and improved cost-efficiency of internal operations. For example, devices with smart features minimize field service effort and reduce TCO (Total Cost of Ownership) by allowing for remote performance monitoring, issue investigation, and troubleshooting. Furthermore, in an IoT enabled factory where individual but interdependent components of a production line are aware of each other’s activity in near real time, the entire manufacturing process becomes more efficient and much easier to monitor and administer.
Additionally, IIoT promotes flexibility through open architectures that support customization and streamlined software upgrades across tens of thousands of devices. All these benefits of Industrial IoT have encouraged equipment manufacturers to produce new equipment models that include smart features out of the box.
Kaa is an enterprise IoT platform, which has been also extensively used as an Industrial IoT platform, that functions as a cloud application manager for connected industrial production facilities. One key feature of Kaa is that it is hardware and transport-agnostic, which enables it to easily integrate with a broad variety of sensors, controllers, machines and device gateways in order to readily support any existing industrial infrastructure.
Once in place, Kaa can provision new devices, manage their lifecycle, receive and store telematics and sensor data in the cloud, execute remote commands, run over the air (OTA) updates, analyze device data and create rules for smart alerts.
Kaa’s out-of-the-box connectivity and data processing features utilize popular protocols such as MQTT and can be used together with popular data management systems and databases to integrate with your existing backend.
Kaa’s open APIs simplify integration and DevOps tasks, allowing you to rapidly assemble end-to-end IoT applications for industrial system automation, predictive maintenance, and remote monitoring. Kaa also features a user-friendly web dashboard tool for configuring data visualization widgets that perform production monitoring routines.
Early detection mechanisms and fault prediction capabilities are crucial to prevent equipment from unnecessary damage and shutdowns. Smart industrial systems equipped with IoT sensors make early fault detection possible. In this scenario, Kaa collects detailed information transmitted by sensors to keep track of equipment status, efficiency, security, and much more. As soon as a fault is detected an alert is sent to the operator, potentially preventing a more serious fault from occurring. An additional benefit is the collection of historic information about your equipment, which with the help of machine learning and AI, results in increased efficiency of equipment audits and maintenance.
With an Industrial IoT platform, a diverse list of production assets become accessible for conducting remote inspections at any time.
Field operations, in particular, stand to gain drastic increases in efficiency by adopting IIoT. Telemetry data collected from connected field equipment contains a wealth of actionable information for technicians. Analysis of this data eliminates much of the guesswork in the field, greatly reducing inefficiency resulting from overservice and excessive truck rolls.
In cases when equipment does require physical service, efficiency is also improved from having precise and expedited failure root cause analysis obtained from sensor data and the electronic service history record.
An Industrial IoT platform can prevent failures before they occur. In most cases, properly configured analysis of data feeds from equipment can flag likely future malfunctions so that appropriate preemptive maintenance actions can be performed before the malfunction actually occurs.
According to the World Economic Forum’s Industrial Internet Survey, optimizing asset utilization ranked as the top reason to adopt IIoT technology, with 79% of respondents citing this as “extremely important” or “very important” for near-term adoption.
By enabling cloud capabilities for your equipment with Kaa, you’ll be able to monitor and control your workflows remotely, as well as set up automation rules to optimize asset utilization. You can also take advantage of comprehensive performance analytics to introduce timely adjustments to your production routines and use historical data to optimize future planning.
Additional cost savings can be gained by adopting dynamic energy use policies, managing energy usage during peak, off-peak, and zero service periods.
A Smart Factory is the ultimate goal for manufacturing operations. In simple terms this is accomplished by applying Industrial IoT methods within your operation. However, achieving this requires strategic adoption of several keystone technology trends. One of them is known as the “intelligent edge”. It is based on the paradigm of decentralized networking within the Industrial IoT ecosystem - meaning edge devices perform their part of data processing workloads before transmitting results to the cloud. Such network topology enables sophisticated IoT workflows within limited network resources, ensures devices can operate without interruption if they go offline, and reduces latency for critical operations.
Another essential technology needed for smart factories is AI and machine learning. Currently the most popular AI applications are voice and image recognition, robotic process automation, quality control, and autonomous robots. As AI algorithms gain more traction, industrial systems continue to optimize operations and discover new possibilities to achieve autonomy. AI is expected to be able - via automation - to program and configure millions of industrial devices, thus accelerating the evolution of IIoT and smart factory innovations.