IIoT trends for 2022

The global Industrial Internet of Things (IIoT) market size was estimated at $216.14 billion in 2020 and is expected to reach $266.50 billion in 2021, at a CAGR of 23.63%. Maintained this rate of growth, it could reach $772.08 billion by 2026, in ResearchAndMarkets’ projections. 

The rapid digital transformations that occurred as a result of pandemics are among the main factors for this aggressive growth rate. IIoT equipment manufacturers continue to find cheaper and more affordable ways to develop sensors and processors to meet the demand for increased automation.

Yet despite favorable winds, decreasing computing power costs, and improvements in the integration, connectivity, usability, and management of IIoT platforms, few manufacturers have successfully scaled their IIoT-enabled use cases in a way that achieves significant operational or financial benefits. A combination of technical and organizational challenges are often cited as causes. 

On the technical side, according to McKinsey research, many organizations are still grappling with long-standing issues, such as grappling with heterogeneous systems and application scenarios or how to determine which functions (e.g. supply chain management, manufacturing operations management, plant maintenance, or asset management) should be supported by which applications and technical systems (e.g. enterprise resource planning or IIoT platforms). There is also the question of where these systems should be deployed – at the network edge, at the manufacturing site, or in the cloud – a question rooted in governance between IT and operational technology (OT), factories, and corporate functions.

On the organizational side, companies often fail to modify business processes or optimize IIoT solutions to enable wider application, leaving significant value on the table. People and processes must change to capture the benefits of the data-based insights that IIoT can generate and maximize the value of the technology. This requires leadership commitment to ensure that IIoT is not simply an IT or OT initiative but, rather, an organization-wide effort.

In any case, as a growing number of companies lean towards automated assembly lines and operations, as well as other “unified digital human workforce” strategies, the IIoT is expected to grow in virtually every global industry.

IIoT Benefits

IIoT connects different tools, data, and user points in industrial environments and offers several important benefits once implemented:

Automated Manufacturing – Automation is one of the key benefits that IIoT offers its users. IIoT is designed to collect and manage data so that it can be trained, or train other tools, to perform the manual work normally done by human workers on an assembly line. IoT industrial automation limits the room for user error and decreases manual task work for a skilled workforce.

Maintenance And Safety – IIoT is often applied for automated predictive maintenance and safety monitoring on assembly lines. Through their low latency, constant collection of performance data, IIoT sensors offer companies the ability to analyze different aspects of performance and determine if equipment needs to be upgraded or replaced or if a worker is coming into contact with hazardous working conditions. IIoT sensors can also track certain environmental factors, such as temperature and air quality, to ensure the safety of equipment and products manufactured in transit.

Real-Time Efficiencies – Because IIoT focuses on collecting as many real-time data points and insights as possible, it is often used as a precautionary tool that can prevent unnecessary downtime caused by equipment outages and other performance issues. Less downtime leads to greater workplace efficiency and overall productivity.

Workforce-Equipment Connectivity – In a more traditional factory or industrial environment, human workers operate equipment, and automated machines act according to their own programming. IIoT is one of the few technical solutions that break down silos between the workforce and their equipment. Users gain more direct insights from their tools and allow tools to learn from human intervention over time.

Hence, the manufacturing industry is leveraging IIoT devices such as sensors, drones, industrial robots exponentially to help increase reliability and improve the efficient use of machines in places with minimal human intervention.

Known for increasing efficiency, the IIoT empowers companies with inventory management, workforce management, asset maintenance, and field service. Because IoT provides better visibility into a company’s supply chain, manufacturers can monitor product conditions in transit and verify transit schedules. The most significant benefit you get from IIoT is the ability to automate and increase the overall operational efficiency of manufacturing processes. Some other benefits of IIoT are:

• Improved asset usability through predictive machine maintenance;
• Efficient use of energy due to better control of temperature, ventilation, lights;
• Effective organization of the factory as a result of optimal warehouse utilization;
• Improved workforce management based on personnel data;
• Structured logistics optimization through informed decisions on downtime, order status, and routes.

Pandemic COVID-19 also highlighted how the IIoT can increase organizational resilience in the face of catastrophic events. Digital management and connectivity tools, for example, have enabled companies to react to market changes faster and more efficiently, allowing for quick adjustments in production capacity while supporting remote operations when access to a facility is hampered.

2022 trends

There are some important trends we see emerging in the market that will play a big role in 2022:

Focus on sustainable manufacturing – While sustainability is highly complex, embracing sustainable manufacturing is not. A simple dashboard can provide the insights you need to, for example, know when a critical part should be replaced to reduce the number of rejected products. A quick start to reduce waste!

Sell services, not technology – more and more suppliers are striving to offer the best service during the warranty phase and then create a performance overview report. When the warranty period is over, you can sell it as a premium service;

Understanding of cybersecurity risks – because of the increased threats and high costs of a breach, it is becoming increasingly obvious that everyone plays a role and must have a basic level of security knowledge. Ongoing vulnerability monitoring, secure configuration, and third-party scrutiny of security logs fall on manufacturing units. It is not a question of whether IIoT networks will be attacked; it is a question of when and how expansive. Therefore, increased spending on cybersecurity is no longer a choice, it is an obligation;

Demand for customized solutions – to keep pace with rapidly changing technologies and market demands, your IIoT solution needs to be flexible and scalable. This concerns both the solution provider and the product itself. Make sure the company is continually innovating, uses cutting-edge technology, and has maintained APIs to enable integrations;

Focus on so-called “condition monitoring” – Anyone who hasn’t built it into their application roadmap is already late. 2022 will be the year when machine manufacturers – who have already started collecting data – take the first steps towards a condition-based strategy. IIoT-enabled devices can be used to monitor equipment so that any issues that might cause a shutdown can be addressed. Temperature sensors on a robot can warn when an essential component is about to fail. In addition, the robot can initiate maintenance to reorder a new component through the Internet of Things (IoT), avoiding unnecessary maintenance and downtime.

Focus on smart solutions – Whether it’s enabling Industrial AI to detect corrosion inside a refinery pipe, providing real-time production data to discover additional capacity in a plant, or accelerating new product development by feeding operations and service data back into the product design cycle, the IIoT – and the solutions driven by it – are delivering business results. Successful implementation of an ML-based solution for Industrial IoT (IIoT) involves many aspects, including but not limited to: placement of appropriate infrastructure for timely and accurate collection of data from multiple sensors; aggregation of data in gateways/cloud; development and adoption of advanced AI algorithms; and hosting of ML-related tasks at the network edge. AI and hybrid edge computing solutions are expected to dominate the IIoT in the coming year.

Digital Twins – coupled with other technologies such as Big Data & Analytics, enterprise asset management, smart supply chains, augmented reality, and artificial intelligence, digital twin technology promises an emerging world of predictive maintenance and proactive operations.

Undoubtedly, companies must embrace automation through smart devices at all endpoints to succeed in the future. In addition to paving the way for the next generation of industrial automation, a growing interest in sophisticated robotics and automation platforms is increasing factory efficiency and productivity.

Invariably, there is a large volume of data and the IIoT provides the route to optimizing it in a secure but visible way. Recognizing new pathways and developing technology to incorporate into your company’s operations as quickly as possible can go a long way to helping you gain a competitive advantage.

By combining machine-to-machine communication with industrial data analytics, the IIoT is expected to help generate unprecedented levels of efficiency, productivity, and performance. And as a result, industrial companies in power generation, oil and gas, utilities, manufacturing, aviation, and many other sectors will experience transformative operational and financial benefits.

No matter where you are on your Industrial Internet journey, industrial software can deliver innovative business outcomes with simplicity, speed, and scale. Empower today’s modern industrial workers, become more predictive and profitable with Industrial AI-based solutions, and transform your business to solve your toughest challenges by putting industrial data to work.