Our Industry Disrupted event on Thursday 17 May was a huge success. Taking a deep dive into Robotics and 3D printing, our guest speakers Josh Barnfather, Alex Youden and Calie Pistorius eloquently explained how these technologies are already transforming industries far and wide.
Josh is the Director of JD Barnfather Ltd, which provides robotics and R&D consultancy services to various industries.
We spoke with him to discuss how we can take inspiration from big data handling in robotics and apply the same concepts to various industries.
Big data is fast becoming a huge challenge in a diverse array of industries. This is largely due to the skills and time required to develop the efficient and intelligent algorithms needed to deal with the information.
However, if we can find a way to embrace big data and use it to our advantage, it can give us a fascinating and constructive insight into an endless variety of technical and business issues. In turn, this can help us to tackle these problems head-on.
Some good examples of handling big data can be drawn from the robotics industry.
“The big data challenges associated with robotics are potentially good examples of how using advanced analytics can help businesses realise some important industrial benefits,” Josh tells us.
Robotics and big data are linked in two key ways:
“For many applications of robotics in industry, particularly in manufacturing, constant environment perception is needed for a robot to complete its task,” he explains. “Actions, such as handling materials, assembling products and welding are achieved through a number of onboard sensors and measurement systems. ”
For this to happen, a vast volume of measurements needs to be constantly acquired and processed together.
“This processing may include the application of noise reduction and data cleansing techniques, as well as predictive Artificial Intelligence (AI) for task optimisation,” he continues. “When developing the algorithms for performing these big data processing tasks, an engineer has a massive amount of mathematical and statistical tools at their disposal, so there is some element of creativity behind finding the best ways to manage it.”
The second link between big data and robotics is in surveying applications: “This essentially means when robots are deployed to environments that are not accessible to humans.”
Josh reveals that not only does a robot have to deal with data used to support its own operation, but it also must collect data as it monitors conditions for predictive maintenance.
“Predictive analytic techniques are crucial to handling large data volumes. They are needed to identify trends, which is particularly useful for performing preventative maintenance and reducing downtime,” he details. “Of course, these prospects can be very attractive for operators of high-value assets, such as wind turbines or small, off-grid gas turbines, as they can be essential to optimising costs and ensuring health and safety.”
By taking a closer look at the relationship between robotics and big data, we can apply the same principles to a wide range of different industries.