Editor's note: This article is part of the State of Smart Manufacturing theme week.

Some of the most valuable connections in the industrial internet of things (IIoT) aren’t with things at all — they’re with people.

Increasingly, workers in manufacturing and industrial facilities are doing more than simply logging or checking data on connected devices. Rather, they’re becoming a sensing and transmission point, an integral part of the IIoT themselves.

Wearables, like augmented reality (AR) glasses, biometric monitors and GPS are delivering timely information to and from workers on the factory floor, in the warehouse, and in the field, as the broader promise of smart manufacturing and Industry 4.0 continues to unfold.

This fusion of employees within the IIoT is creating new strategic use cases, opportunities for unprecedented workforce visibility and collaboration that not only increases worker effectiveness but can drive the kind of efficiency and employee satisfaction that directly bolsters the bottom line.

Approaches to connecting employees

The success of integrating employees hinges on the seamless blending of technology with the employee’s workflow. By definition, frontline workers operate on the edge — they are the furthest link in the chain of cloud-connected systems. It’s where workers can leverage both smart and dumb devices to support complex tasks, while also returning information about their performance, heightening real time operational visibility of the workforce to managers.

Industry is increasingly adopting smart technologies for workers. These can range from simply RFID or NFC tags, which can track employee whereabouts, workstations and more, to more intensive AR/virtual reality (VR) systems or biometric sensors, which can feed important metrics or data to employees on the spot or help keep them safe among busy factory machinery.

IIoT sensors, wearable devices and existing programmable logic controllers (PLCs) can all feed data back to platforms in the public or private cloud. Integration with enterprise resource planning (ERP) systems and the manufacturing execution system (MES) can provide additional context to support artificial intelligence (AI) recommendations for improving processes, speeding root-cause analysis (RCA), and optimizing all aspects of workflow.

Delivering digital information that’s truly actionable in real time means optimizing its presentation to users, and that almost always means making it visual and intuitive. AR/VR systems, for instance, can overlay interactive images directly in the worker’s eyeline of a maintenance site or a product, allowing them to view and interact with the composite image through a smartphone camera, or wearable AR headsets — a significant level up from merely presenting CAD drawings on a tablet.

Figure 2. Source: Nanci/Adobe StockFigure 2. Source: Nanci/Adobe Stock

Identity verification

Many are familiar with digital badges, which offer visual identification of the user, but also provide access to doors and machinery with a quick swipe. Logs of these activities can offer factory engineers the opportunity to uncover where productivity lags — such as long trips between workstations or bottlenecks due to low capacity.

Increasingly, biometric ID systems are being used to provide this access. Although it only saves a few seconds versus a card swipe, it is a more secure method, as cards can be lost or stolen. It also offers the added benefit of assessing the user’s physical state. Drowsiness and liveness detection ensures that alert users are at the controls, and if not, shuts machinery down.

All of these factors can help assess employee satisfaction and safety. For example, employees who spend needlessly long trips walking between workstations are likely to be more tired. Tired employees are less productive and less aware — and less safe — than employees whose ergonomics and fatigue has been accounted for.

In truth, devices at the edge can consist of myriad other specialized machines — whatever best serves the use case.

Guiding employee activities

Delivering digital information that’s truly actionable in real time means optimizing its presentation to users, and that almost always means making it visual and intuitive.

Slowly but surely, this has progressed in recent years. It is no longer uncommon to see maintenance technicians and engineers monitoring machines or browsing data sheets on a tablet, perched next to the machine under inspection. These types of technologies enable greater collaboration with vendors and service providers, who might be able to remotely diagnose and troubleshoot machinery issues with those already on site.

These are also great training tools for employees, who are able to learn about technologies at facilities while a real-world example lives in front of them. Interestingly, this is also an effective tool for training robots. Manufacturers are placing greater value on robots that can be easily redeployed for new production needs — and OEMs are offering models that can be reprogrammed in a VR or AR environment.

Pros and cons considered

Clearly, increasing complexity in manufacturing demands expert human intervention. But this overlooks some of the challenges that are unique or fledgling in this area, although these alone may not be deterrents to deploying IIoT where it makes sense.

Pro: Increased productivity and efficiency

When IIoT-connected workers can access a wealth of information and guidance directly from their wearable devices, they can play a key role in minimizing disruptions and downtime. Letting users interrogate procedures in situ, tailored to both their specific role and narrowly targeted to the context of their current location, can cut down mistakes and speed troubleshooting, driving efficiency and productivity.

That can be especially powerful in light of recent advances in generative AI (like Chat GPT) and large language models (LLM) that can ingest existing procedures and policies and allow workers to interrogate information in a conversational way.

Con: Privacy concerns

As workers become nodes in the network, their every move can be tracked and analyzed. This raises significant privacy concerns, with the risk of surveillance extending beyond the workplace if not carefully regulated.

But surprisingly, workers are often receptive to the benefits of wearables and monitoring, provided it’s all left on the shop floor. A 2022 survey conducted by Truce Software found that many employees view connected tools as positive on their productivity and flexibility. It found that employees highly value work/life balance while privacy at work is a lesser concern, as long as the boundary of monitoring is left there. Moreover, by monitoring only what manufacturers absolutely need to best understand the employee’s workflow, and being transparent about it, employees feel respected and supported instead of watched.

Pro: Enhancing safety

One of the most valuable benefits is the ability to monitor health and safety in real-time. Wearable devices can track vital signs, detect exposure to hazardous conditions and trigger alerts in case of emergencies. This immediate responsiveness can significantly reduce workplace accidents and mitigate health-related issues. Measuring exposure over time can also mitigate longer term concerns — radiation, asbestos and other environmental hazards with effects that only show up down the line. In addition to vital signs, wearable sensors for hand-arm vibration (HAV), whole body vibration, environment noise, gas and dust are becoming more sophisticated, and when combined with fixed area monitors they can provide a holistic assessment of hazards in real time.

EEG sensors and brainwave technology detectors coupled with AI analysis can even infer aspects of a worker’s cognitive state, like waning levels of focus and attention.

As OSHA and other regulations evolve, IIoT is not only a critical tool for compliance, but also a tool of ethical and human-centric management that protects valuable employees regardless of regulation.

Con: Data security

Cybercriminals looking for a payday extort companies with ransomware that disrupts operations until demands are met. Or worse yet, they part out employee personal financial information on the dark web.

Even as IIoT supports compliance with health and safety regulations, the proliferation of connected devices increases the attack surface for cyber threats. Sensitive personal and operational data could be compromised if adequate security measures are not in place, posing risks to both individuals and the organization.

This is not a new threat, but rather one with growing significance as companies with low cyber skills increasingly move operations to digital networks.

Pro: Personalized training and development

The integration of AR and VR technologies can also offer personalized, immersive training experiences that can adapt to the worker's pace and learning style. This not only accelerates the learning curve but also enhances the retention of complex information, directly contributing to the overall skill level and performance of the workforce. That may include upskilling existing workers or quickly onboarding new workers, providing managers with a more agile workforce, and giving managers more control, even compensating for minor deficits in skill sets.

Training becomes a routine and natural part of workflow. All that makes it easier to cope with changes in product and incorporate AI-generated refinements in procedures.

Con: Potential for overreliance

Some experts worry about the risk that the heavy reliance on technology could de-skill workers over time, making them overly dependent on automated systems and devices for decision-making and problem-solving. The phenomenon of de-skilling is as old as the cotton gin, in some cases it’s regarded as a natural artifact of innovative automation, in others as an unintended side-effect. More knowledge-intensive or high-dexterity roles are less susceptible to automation, but a worker’s skills can atrophy when they become reliant on systems that support them.

Similarly, automated safety monitoring has the potential to reduce a worker’s situational awareness.

Managers need to address the risks of de-skilling directly, with regular testing and assessment of worker proficiency. That just means that mitigating de-skilling risks is part of the plan, rather than a reason not to enhance workflows with IIoT. They’re the kinds of natural artifacts that come with adoption of any new technology.

Managing connected workers and data

With the myriad sensors, both wearable and location based, that can return data from the worker, there is a clear need for dedicated tools to help manage and make sense of telemetry from the edge. That’s made possible by data acquisition platforms that collect data from your workers, sensors, and machines and feed them to a central database.

This immense quantity of data is often called big data, and dedicated software analysis tools help refine and optimize the data using AI-driven insights. It’s the platform’s job to make sense of that data and deliver context relevant information to decision makers. Those insights help optimize processes, minimize downtime, speed troubleshooting and drive more effective RCA, thereby maximizing productivity even while ensuring the well-being of employees who work at the edge.

The fact is that integration of workers into the IIoT ecosystem holds vast potential for industries looking to harness the full spectrum of sensor and AI technology to promote manufacturing excellence. However, navigating the ethical and practical challenges requires a balanced approach. Policies and practices that prioritize privacy, consent and data security, alongside the development of robust cyber defenses, are essential. A human-centric approach to industrial productivity can’t help but show up on the bottom line and push an organization ahead of the competition.

About the author

David Bean writes on a diverse range of science and technology topics. Bean previously directed enterprise software projects for government, healthcare and gaming. He graduated from Cal Poly University with a degree in aerospace engineering and is based in Palos Verdes, California.

To contact the author of this article, email GlobalSpeceditors@globalspec.com