Smart robots have often been portrayed as a threat to jobs. But the technology can be used to benefit employees by improving the quality of their work and increasing safety standards.
Artificial intelligence (AI) and the Internet of Things (IoT) are becoming increasingly prevalent in the workplace. Once a source of suspicion among workers, this move towards digitalization is now being seen as an opportunity for adding value to their work.
Recent research by human resource consulting firm Randstad reveals that three-quarters of employees surveyed in the US are not concerned about increasing automation. The study also found that 30% of US workers believe it will make their job better.
This is good news for companies who are actively exploring new ways of digitalising their workforce.
IoT to take industry by storm
It is estimated that 8.4 billion connected objects, from fridges to cars, will be in use this year. That figure is predicted to rise to 50 billion by 2020.
Consumers will receive a more seamless customer experience, while companies can carve out a competitive advantage by harvesting the masses of data that IoT devices produce.
But companies can also profit from IoT technology by using it to monitor employees via sensors attached to their clothing and footwear. The idea is that this will be benefit workers and the business itself.
Improving efficiency with IoT
Tata Consultancy Services (TCS) has been working on a proof of concept (POC) that involves equipping production line operators with connected shirts and shoes.
The POC, which was done in partnership with a start-up that makes smart in-soles, was for the French car manufacturer, PSA Group.
Rishabh Arora, director of industrial IoT at TCS, explains: “We set out to prove the hypothesis that we could actually use AI and machine learning techniques to pick up useful patterns from the data gathered from sensors on operators doing a repetitive task.”
The TCS IoT solution could next be tweaked to establish the ‘correct’ way of working. This could then be used to alert an employee, via a vibration on the sensor, when their posture may cause injury, or when their method of working was inefficient.
“Through the sensors, [the software] can monitor the posture of operators based on their unique biomechanics,” Rishabh adds. “It also has a huge impact on quality and productivity.
“The algorithm could be used to detect if there are certain things that the worker is doing wrong, and these can be fed into the training of the worker to help them.”
High level of accuracy
Humans are far less predictable than machines. This makes it difficult to monitor and analyse movements with a high degree of precision. Nevertheless, TCS’ data model was able to identify actions by production line operators with 91% accuracy.
Rishabh explains: “Just by looking at the raw data coming in from the sensors, our model was able to identify the specific step that the operator was performing, such as whether they were opening the fuel valve, or removing the door from an automotive chassis.”
Every sub-task the operator does has a certain ‘signature’, which is captured within the masses of data collected from the sensors on the operator. TCS’ data scientists were able to apply machine learning techniques to work out these co-relations and signatures, says Rishabh.
“Whenever we are trying to create a data model using machine learning techniques, we [essentially] take dozens of parameters and try to figure out the model that explains how they interact with each other,” he adds.
Humans and machines working in harmony
While this TCS data model is currently only at POC stage, it is hoped that it will be put into action within the next few months.
Another use case being explored by the TCS team is whether the model of the operator can interact with the automation and control systems of the production line to help improve the overall productivity of the line.
As the rate of industrial digitalization continues to gather momentum, the introduction of AI and IoT technologies will become more prominent across all sectors.
But this shouldn’t be a cause for concern, says Rishabh.
“There is a lot of talk about AI and IoT being a threat to jobs, but what we’re doing here is looking at whether [this technology] can actually help us do our jobs better,” he says.