The Industrial Internet of Things (IIoT) is still in its initial stages, but the potential for a wide-scale digital transformation of industrial automation has many companies looking into the future. The Internet already allows for access to a large quantity of data, but once IIoT becomes commonplace, this quantity will grow exponentially.

Machine learning and artificial intelligence can leverage this information to allow an organization to adapt to changing industrial applications, improve productivity and generate insights for strategic decision making. No one is entirely sure what industrial automation will look like in 10 years, but there are a few key areas to consider.

The Key to IIoT

Machine-to-Machine networking (M2M) and nanotech sensors create an environment where IIoT can thrive. Increased data generation and distribution allows devices to go beyond real-time processing and take an adaptive approach to manufacturing. These sensors may end up working synergistically to create a cohesive ecosystem within the industrial environment.

Widespread wireless connectivity has led some industry leaders to call this shift Industry 4.0, due to its far-reaching implications for the process by which things get done. It marks an era where digital-physical systems are being routinely used to monitor both physical and software components, towards an unparalleled level of productivity and output.

One company that’s embracing Industry 4.0 head-on is automotive and industrial supplier Schaeffler. Deputy CEO and CTO of Schaeffler, Peter Gutzmer envisions a future that’s hyper-connected and smarter than ever. Gutzmer describes “connectivity between vehicle and media technology” as being a core goal for the next five to ten years, stating “[Schaeffler] will network much more closely in the future: chiefly between manufacturers and suppliers, but also within the supply industry at large.”

Industry 4.0 marks the transition to self-regulating parts that are not only capable of monitoring their own performance, but can automatically order replacement parts. This ability enables machines to operate with a unprecedented level of autonomy. The implications are profound and should usher in a level of efficiency that was nearly inconceivable in the past.

Distributed Automated Factories

Business Process Automation already has plenty of utilization, but companies have not yet been able to make the leap to fully-automated factories: though they come closer to it being a reality every day. Companies are already using IIoT and automation to monitor internal environments of production facilities and predictive modeling to minimize energy usage for lower manufacturing costs. IIoT is changing the entire industrial landscape in multiple ways, and its impact will only continue to increase.

Additionally, a company no longer needs to centralize its facilities, due to the expense of equipment or logistics associated with having multiple locations. These factories can now be connected to each other through the IIoT and positioned near distribution or resource centers. Industry 4.0 means large pools of relevant data can be stored and processed in the cloud.

Whether on- or off-site, manufacturers will be able to monitor equipment with complete accuracy for heightened performance. Any errors or glitches could be pinpointed and flagged for swift action. While infrastructure will become much more complex overall, operational efficiencies will likewise increase substantially.

The supply chain will also benefit from this environment. Automated factories will integrate with logistics partners to keep your products moving steadily and the supply chain system, with access to the data generated by the manufacturing equipment, will know exactly what is being created at any given time.

If a company’s needs change suddenly, the supply chain system could then pass this data to the automated factory to increase production for specific parts or products. In a perfect future IIoT world, this entire process happens seamlessly, without any outside input. This final stage would consist of fully autonomous manufacturing, where every step of the process is completely automated. Though that is still a distant goal, the rate of innovation that’s currently happening could make it a reality in the not so-distant future.

Higher Processing Speeds

Adapting cutting-edge technologies to implement IIoT invariably means higher output in less time. Take for instance the milling machine company Makino. Their primary focus is building machines that are capable of reaching new productivity levels through dramatically reducing cycle time. Makino’s most powerful Super Geometric Intelligence software is capable of reducing cycle time from anywhere between 20 to 60 percent, depending upon the complexity of the shape, while maintaining the standard level of accuracy. By continually looking for ways to better automate demand, companies like Makino will be crucial to furthering the refinement of production and just-in-time delivery.

Multi-Equipment Compatibility

One challenge facing widespread adoption of IIoT is the sheer number of equipment manufacturers in the market. Systems can’t network with each other across companies and locations if they use different platforms and technology. Standards need to be defined to unify IIoT communication in order to truly make use of this new technology, which requires integration and cross-compatibility. Once this is achieved, equipment can be monitored via this communication rather than through sensors specifically designed for each piece.

This is a primary concern for plant managers, where in an ideal world, every piece of machinery and equipment would follow the same protocols for implementation.

Comprehensive Analytics

Data drives the IIoT world and gives detailed analytics throughout the entire organization. When the sensors work together, the operator can remotely monitor the health of every factory without being on the ground. This enables adaptive intelligence, allowing technology to adjust as needed for changing conditions, giving organizations superior business agility. By using devices such as smart helmets that can communicate with manufacturing equipment, safety and working conditions could also be improved.

Without having to invest entirely in new equipment, a structured technology foundation can enable organizations to optimize operations as needed, based on data collected by the factory itself, to produce an overall more efficient and safer work environment for all.

A Bigger Focus on UX

In the never-ending quest for bigger and smarter data, one aspect often overlooked is UX design. While consumer-based IoT technology such as Bluetooth tracking and smart home products are designed with the user in mind, this hasn’t necessarily been a priority for IIoT. What’s the reason for this apparent disconnect? It’s simple: user interface is usually the last thing on a company’s mind when creating a smart factory or monitoring the various components of an oil pipeline. Although the entire premise of automation and machine-to-machine communication is to minimize the need for humans, human oversight continues to play an integral role. As IIoT becomes more sophisticated and far-reaching, UX will take precedence. This is a natural aspect of the evolution of IIoT: in fact, companies like Infiswift are already implementing UX A/B testing to optimize the design process.

Growing Security Concerns

If a downside exists to this type of technology, it would be the inherent security risks that come with the territory. The large volume of data being exchanged creates obvious concerns for industrial operators. The main problem is that many IoT devices have very minimal security controls directly from the manufacturer. With security flaws abound, cybercriminals who have noted these security flaws would naturally seek to shut down the production process or procure sensitive insider information.

Distributed denial of service (DDOS) attacks and ransomware are two of the most common threats companies are facing. Understanding and assessing all of the potential security risks and vulnerabilities that can stem from this process is essential to IIoT deployment. Upholding rigorous security standards requires both a financial investment and long-term commitment, and is far from a one-time thing.

Security standards will continue to rise as IIoT reaches maturity. Frequently, companies will even have dedicated teams with the sole responsibility of overseeing network security in the future.

Increased Funding

An effective way to gauge the growth and collective interest in a particular area is to look at how much financial backing it has. In the case of IIoT, it’s clear that investors are funneling in more money than ever: funding more than doubled from $1.2 billion in 2011 to nearly $3 billion in 2015. The market as a whole is poised to experience dramatic growth over approximately the next five years. Research by IndustryARC predicts “the IIoT market will reach $123.89 billion by 2021.” As cloud technology becomes more sophisticated and consistent improvements are made, larger investments will follow.

The Intersection of Devices and Processes

When everything is connected in the IoT, there will also be a mindset shift. Devices and processes cannot be separated when they’re so closely linked together. The way organizations and people think about infrastructure must change. Each unit contains a wealth of information that will iteratively and reflexively inform the new processes. Disregarding this interconnection will limit the full potential that IIoT has to offer.

Workforce Changes

Full automation and widespread connectivity change workforce needs as well. Mechanical engineers and highly skilled IT professionals must keep up with the latest developments, when dealing with an enormous infrastructure with millions of moving parts that are all talking to each other. If not properly structured, new problems will emerge throughout the manufacturing organization.

The most talented professionals will be in higher demand than they already are, and Industrial 4.0 will not reward a talent shortage. Investing in professional development programs while watching for new hires is a necessary strategy when facing the coming world of full IoT.

Increased data processing demands will also require considerable preparation. Big data requirements now are nothing compared to what they’ll be when every piece of a factory has connectivity and sensory capabilities.

While full maturity of IIoT technology is still a long way off, it’s already having a significant impact on industrial applications, and as new business models drive towards improved capabilities and increased insight into a company’s industrial operations, they will unlock new business opportunities to adapt to new and more efficient enterprise paradigms.