The manufacturing industry is undergoing a new age of evolution, with major changes occurring on multiple fronts. Companies keen on digital transformation are taking inspiration from the Internet of Things (IoT) to power their factories of the future. As a growing subcategory of IoT, the industrial Internet of Things (IIoT) leverages smart sensors and actuators to connect humans and machines with the Internet, boosting manufacturing and industrial processes in terms of efficiency, productivity, and safety. Along with cyber-physical systems (CPS), cloud computing and cognitive computing, the IIoT is key to building the Industry 4.0 era.

The market opportunities for IIoT are massive. Markets & Markets reports the global IIoT market is expected to grow at a CAGR of 7.39 percent to reach US$91.4 billion by 2023, with the manufacturing industry holding the largest market share.

Successful adoption of IIoT systems is built on devices and technologies such as networking, sensors, RFID, cameras, GPS/GNSS, smart beacons and monitoring systems. AI-powered computer vision, machine learning, natural language processing and big data technologies are expected to continue to deliver breakthroughs in IIoT research, development and deployment.

The IIoT will have far-reaching effects (from altizon.com)

IIoT in manufacturing & Smart Factories

Widely applied in sourcing and production, assembly and packaging, warehousing and supply chain management, IIoT solutions enable a fully-connected factory where information and operational commands can be directly sent to suppliers, manufacturers and distributors. Smart factories can achieve improved manufacturing efficiency and quality, enhanced human activity support and reduced energy consumption and costs. Many industrial and tech companies are venturing into IIoT product development, aiming to bring innovative IIoT solutions to smart manufacturing.

Siemens’s MindSphere provides a “Predictive Maintenance” solution to manage the health of machines and maximize their performance. Through real-time monitoring and analysis of data from automation systems and production assets, the predictive maintenance system can evaluate machines’ health state and proactively identify the cause of any predicted machine breakdowns. MindSphere machine learning models for predictive analytics are built for each individual machine based on its historical health variables (e.g. vibration, temperature, cycles, load and pressure, etc.).

ABB’s Ability platform enables design, troubleshooting and optimization of a new production line using modeling and virtual commissioning without disturbing existing production operations. The system can build up a 3D process simulation wherein robots can be programmed and connected to automation networks, with all their operations tested in a virtual world. The solution can significantly enhance engineering efficiency and productivity with less risks and costs compared to deployment in a factory.

Key Players — Top IIoT Solution Providers

Players in the IIoT market are primarily tech giants and world-leading industrial vendors like Cisco, GE, Siemens and ABB. Below are 10 of the leading companies with significant IIoT platforms and strong industry partnerships.

Challenges and Trends

In recent years manufacturing companies have built a much better understanding regarding the value and benefits of the IIoT. They do however still face challenges in adopting IIoT solutions in their factories. One of the biggest issues is securityvulnerability, the risk that hacking could cause data breaches, privacy violations, or have a damaging impact on the OT system and factory operations. Another critical challenge is the high cost of hiring human experts and deploying hardware, software and high-speed network infrastructure for IIoT connection — especially considering the relatively long payback period. Overcoming these hurdles is crucial to accelerating IIoT deployment in manufacturing.

A number of new trends are emerging in IIoT and industry 4.0, mostly enabled by the rapid development of cutting-edge AI-powered technologies. One example is the combination of edge and cloud computing for data management: The edge platform enables basic analysis to be performed close to the user with near zero latency, reduced data exposure and increased resiliency; while the cloud provides high data storage capability and enormous computing power. Another trend is digital twins, which integrate IIoT, machine learning, and software analytics with spatial network graphs to create a dynamic virtual copy of a physical system for its real-time optimization.

The Markets & Markets report identifies key IIoT manufacturing sectors as Automotive, Machinery, Food & Beverages, Chemicals & Materials, Electrical & Electronics, and Pharmaceuticals.