The Connected Worker: Leading a Revolution in Safety and Productivity

Artificial intelligence (AI), analytics, robotics, and other disruptive technologies are already enhancing the capabilities of white-collar workers. Sports reporters and financial analysts, sales and marketing professionals, insurance claims adjusters and lawyers are all using these technologies to work more accurately and efficiently. But how far behind are blue-collar workers?

In reality, blue-collar workers were early adopters of technologies such as robotics, using it to improve efficiency for mechanical tasks that include palletization, welding, stamping, trimming, deburring, and molding machines more than two decades ago. Now, with improvements in connectivity and sensor technology, blue-collar workers in industries as diverse as energy, utilities, manufacturing, construction, and mining are about to take the next big leap. Their use of sophisticated sensors, networks, data sciences, and analytics is resulting in quantum improvements in productivity, decision making, and safety.

Blue-collar workers have traditionally been resistant to technologies that track and monitor performance, but this is changing with the usage of these technologies in other spheres of life. The widespread consumerization of technology and pervasive connectivity has lowered resistance. The blue-collar demographic is now more comfortable with the concept and benefits of being connected.

Even more critical to the acceptance of data sciences and analytics is the change in shop floor work contracts. Workers are increasingly being compensated based on output. This makes tracking the number of hours worked, quality, output, and reporting a crucial requirement.

Another compelling driver of the coming change is the number of individuals affected by work-related accidents. According to the latest figures available from the U.S. Bureau of Labor Statistics, compensation as a result of workplace injuries in the natural resources, construction, and maintenance occupations alone account for 3 percent of total compensation costs in the United States. A number of ways to make the workplace safer and reduce the unnecessary cost of medical compensation are being urgently explored.

Clearly, blue-collar workers are primed for the adoption of AI, virtual reality (VR), augmented reality (AR), analytics, and robotics. Industry 4.0 is knocking at their doors, and executives responsible for safety, productivity and costs are opening their doors to the new technologies.

Safety First
The good news is that many of the solutions in terms of connected networks, sensors, software, algorithms, and analytical engines and data storage already exist in generic forms. These solutions just need to be shaped for industry-specific situations and use cases. For example, a construction site needs to keep workers safe from equipment that is moving materials (overhead cranes, welding machines, cutters, etc). Employees must be warned in real time when approaching equipment presents a danger. Sensors placed around the equipment or on the workers in the form of wearables can be used to trigger alarms.

On the other hand, workers in a mining operation may need to be kept secure from gas leaks. Similarly, in situations such as fatigue detection in a worker, companies may need the sensors to sniff out the data to send to a system for analytics. A broad, overall architecture diagram for such a system is shown below. In this example, Sam, a miner, wears a helmet equipped with a bunch of sensors, communication equipment and alert management options. The system monitors Sam’s environment and is capable of making localized decisions for a handful of situations. But when the decision-making is complex, it uses a gateway to send data to a central system or cloud where the data is analyzed and decisions relayed back to Sam. Such central systems can be used to serve workers and emergency response teams (ERTs) in multiple zones and geographies.


The solutions that keep Sam safe need to be scalable and reliable. This means three things:

1. Ensuring the capability of sensors and devices (on helmets, wearables, clothes, belts, loops, operational equipment, and facilities or work environments) remains within a manageable range.

2. The solution must have redundancy in order to remain reliable.

3. The solution must be hierarchical in nature, helping address the time required for a response, the coverage area, and the different levels of decision making needed in a given environment.

This approach covers all possible situations related to safety and productivity. For example, a "man down" gets processed by a helmet using a gyroscope, an accelerometer, and a location-based service to generate an instant alarm. Health monitors that measure pulse, oxygen levels, and blood pressure, on the other hand, can leverage a back-end analytical system to determine alerts for more fuzzy parameters such as worker fatigue.

Productivity Next
The quest for lowered cost and reduced equipment downtime in the energy, utilities, manufacturing, construction, and mining industries is never ending. With the arrival of the connected worker, delivering on both counts has become easier.

Take the need of aeronautical engineering companies for assembling hundreds of small components with very high quality parameters. Such assembly requires sophisticated training, long years of experience and tools to ensure that precise safety standards are met. However, workers with minimal experience can be equipped with AR visors and now deployed on the shop floor without compromising quality. The AR visor assists workers by overlaying instructions on actual scenarios to guide assembly and assure quality.

In other instances, workers wearing AR glass can team up with remote experts to examine the condition of sophisticated and expensive equipment. The experts, in a central location, can work with on-site workers in different geographies to ensure accurate and timely maintenance. To achieve this, annotated images and videos of equipment are sent back in real time to the experts who then provide solutions. By eliminating the need to maintain on-site expertise, operational costs are brought down and the highest quality of support is made available across geographies.

Again, like safety, productivity solutions must be hierarchical in nature. Systems should be able to assess the level of support required. This means if a chatbot can assist a worker with the first level of troubleshooting, the problem should be escalated to a subject matter expert only when the intervention by the chatbots fails. The overall effect of using chatbots is multifold: problems can be dealt with locally using a bunch of sensors and analytics, while down time can be minimized and costs kept under control.

The data compiled from incidents can then be used for long-term measures that improve productivity and reduce costs. These measures would include imparting better training and capturing root cause to re-design or upgrade equipment and processes.

The Promise of Technology
The technological building blocks to fuse physical and cyber systems – sensors, hardware, equipment, models, data management and analytics – already exist. Sensors are becoming rugged and affordable. Their form factor ensures they can be embedded into practically any equipment, device or location. Edge computing devices are becoming sophisticated. Communication infrastructure and networks reliability have reached a new peak. Cloud-based back-end systems can scale at will. All that organizations must now do is use innovation and ingenuity to bring these innovations together.

Industry 4.0 and its connected workers hold the promise of a safer, more productive, and cost-effective future. The reality is that blue-collar workers can finally join the ranks of their white-collar brothers using today’s smart, new technologies.

Swarup Mandal is General Manager, Manufacturing & Technology, for Wipro Ltd.

Posted on Dec 14, 2017

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