Improving Safety of Industrial Workers and making them more Productive are critical for manufacturing companies in the Digital Age

Safety of workers is of paramount importance to the manufacturing companies. It is important, first from the humanitarian angle, and next from the perspective of running a business. Let us look into some statistics to understand the implications of safety on business operations.

According to the International Labor Organization every 15 seconds, 151 workers have a work-related accident. The global number of non-fatal occupational accidents reaches a staggering 317 million, annually. Even more concerning, 321,000 people die each year from occupational accidents. This is a staggering number by any stretch of the imagination. The societal implications of these incidents are far-reaching purely from the economic impact on the families of the fatally injured workers. The business implications of such incidents are even more serious. In the United States alone, workplace injuries and illnesses cost employers more than $220 billion annually, with 27 million working days lost per year. These rising costs are also hurting insurance companies and influencing coverage rates.

While improving the safety of workers would yield significant business benefits to a manufacturing company, improving the productivity of the workers would also make a dramatic difference to the company’s bottom line. 50% of companies expect significant productivity improvement from connecting the industrial workforce to one another and to the resources of the organization (see the illustration below). 85% expect their field workers to be connected by 2020. Deployment of the connected workforce at Lockheed Martin’s F-35 aircraft assembly plants have already resulted in increasing engineering accuracy by 96% while letting employees work 30% faster.

Given the significant business benefits of safety and productivity improvement of the industrial workforce, it makes sense to explore how digital technologies can help achieve these objectives in a meaningful way.


A number of companies are manufacturing smart helmets instrumented with a variety of sensors. These sensors connect to a local gateway on the helmet and the gateway, in turn connects to the wireless infrastructure of a factory. Hazards can result from many sources. For example, a worker may unknowingly walk into a welding zone, or an area with fast moving conveyer belts, or a high voltage zone, or a zone earmarked for poisonous chemicals.

While these are examples of static hazards, there could also be dynamic hazards as well. For example, a worker might be standing in a perfectly safe area in a plant when a crane moves in with a large block of steel positioned right above his head. In order to identify these kinds of hazards, it is necessary to track the workers and the vehicles within the factory area. Sensors mounted on the helmet can also detect gas leakage in a confined area and alert a worker as well as his supervisor.

Man-down scenarios can also be detected using the sensors, alerting the supervisor on duty enabling him to take an action. Many a time, the industrial workers do not recognize their fatigue and keep working, jeopardizing their own health and endangering others, especially if they are operating industrial vehicles. Tiny cameras mounted on the smart helmet can continuously monitor the eyes and if the percentage closure of the eyes exceeds a threshold, the worker gets a fatigue alert.

His supervisor also receives a notification. Fatigue can also be detected when specific biometric measurements exceed a threshold or when a worker works beyond the normal duty hours. Intelligence can be built into the system in such a way that if a worker removes his helmet during the working hours, he receives an alert from the system, but if he removes the helmet during lunch hours, he does not. A smart helmet with the complete system is shown below:


Industrial equipment are complex and many a time, a worker is not able to perform the required maintenance work. As a result, he physically brings in an expert to help him and that increases the time and cost of executing the maintenance task. There are smart glasses in the market today with built-in support for voice recognition and Augmented Reality (AR). A combination of these two digital technologies can be leveraged to intelligently do the maintenance work in much smaller time and budget. Here is how.

When a worker is not able to do the repair work he is assigned to, he can talk to the smart glass and the AI-powered expert can provide contextual help to the worker. In some case, this kind of automated support works but there are cases where it does not. In such cases, the worker can ask for an expert and the automation can provide a list of experts who have the relevant experience and are available to help.

The worker can then choose one of the available experts and set up a video call with the remote expert. The remote expert sees what the worker sees in the field and can direct the worker to do certain things verbally. If that does not work, the expert can take a picture of what he sees on his device, annotate the relevant part with his finger and send back the annotated picture. The annotated picture when received by the field worker looks like an annotation on the physical equipment, and as a result, it is clear what he should do to fix the problem. The following diagram shows a glimpse of it:


While the Smart Helmet and Smart Glasses are the core components of a Connected Worker solution, they are tied together with the enterprise system using a Platform.

The workflow for a connected worker in the factory consists of (1) work assignment, (2) work execution, (3) performance analysis and (4) safety monitoring as shown in the diagram below. When a worker swipes his badge (which is RFID enabled), he is recognized and his supervisor is notified. The worker, after putting on a smart helmet, swipes his RFID-enabled badge on the helmet and thereby pairs the helmet with his badge for the duration of his work at the factory premises. The supervisor can assign a job to the worker from his system and the worker sees the assignment on his smart watch. This completes the work assignment part. Work execution consists of following the step-by-step instructions associated with the job as seen on the smart glasses. The connected worker talks to the smart glasses follows the instructions as described in the previous section, and takes help from a remote expert to complete his job in the first attempt. An Analytics Engine (described below) analyzes the performance of a worker against that of his peers and recommends corrective actions in case the performance is below the expected level. Safety monitoring is described in the Smart Helmet section.

There are cases when the remote expert determines that it is not possible to repair the equipment at hand until a damaged part is replaced. In such a case, the system automatically places an order for the replacement part via the ERP system. When the part becomes available, the system informs the worker about the availability of the part in the factory warehouse. The worker can go to the warehouse, pick up the part and replace the damaged part with the new part to complete the repair job.

An instance of the Platform that helps tie all these pieces together and makes the Connected Worker system a reality is shown below. The system is comprised of six components:

  1. Device Controller: On one hand, this component interfaces with the environmental sensors, health sensors etc. to receive data; and on the other hand, it interfaces with display and buzzer via control signals. Thus the device controller is responsible for local action at the smart helmet and at the same time, it provides the communication with the edge gateway controller.
  2. Edge Gateway Controller: On the southbound side, it is responsible for discovering the devices, providing access control and provisioning of the devices. On the northbound side, it connects with the central system, provides information from the devices and receives control signal from the central system.
  3. Central System: The intelligence of the Connected Worker system resides in this component as it correlates all the information from sensors and location system to execute both the safety app as well as the productivity app for the connected worker. It also orchestrates the entire workflow for the industrial worker via the operations app.
  4. Location Manager: This system is responsible for computing the location of assets as well as of workers using triangulation algorithm. The Location manager also provides location-aware services like geo-fencing.
  5. Analytics Engine: This analyzes all the raw data from sensors and provides all descriptive, predictive and prescriptive dashboards. One example of analytics is analyzing the performance of an industrial worker vis-à-vis his peers and provide guidance to improve performance in future.
  6. Human Machine Interaction (HMI): This layer provides the voice recognition and natural language processing via various bots, and thereby improves user experience in a dramatic way.


One of the questions that invariably arise in the context of connected workers is that of privacy. Since the connected workers are tracked, the privacy of the workers may be compromised at the factory premise. However, it is because of tracking, the industrial worker’s safety is dramatically enhanced. Given the importance of safety, workers may opt into tracking. If they do not, the same level of safety as provided by the tracking system may not be guaranteed.


Digital systems are not about any specific technology rather they are about the business outcomes. In the context of Connected Worker, the business outcomes relate to multiple parameters. First, a manufacturing company sees higher operational efficiency that results from higher productivity of the workers and seamless integration with the ERP system. Second, there is a significantly reduced operational expense resulting from improved safety of the workers and the faster turnaround time of maintenance jobs. Last but not the least, there is significantly improved user experience resulting from the human-machine interaction using natural language and the remote expert guidance using Augmented Reality. Thus, manufacturing companies embarking on a Connected Worker journey will outperform their peers on multiple dimensions and be more successful in the end.


My sincere acknowledgements go to Jayanta Dey, Swarup Mandal, Ananda Jana, Souvik Dutta, Debasish Chanda and Team for making the Connected Worker solution real.



Sanjoy Paul
Sanjoy Paul

Dr. Sanjoy Paul is the Chief Digital Officer of WIPRO LTD in Manufacturing and Technology Strategic Business Unit and is responsible for driving profitable growth of clients via innovative digital technologies and business process transformations. Sanjoy has over 25 years of experience, most recent 10 years being in the IT industry and remaining 15 in Technology, Internet and Telecommunications domain. Most recently he was the Managing Director in Accenture leading Digital Go to Market for Chemicals, Natural Resources and Energy industries in North America.