All the latest news from the industry weekly compiled by the editorial team for you free of charge.
This eMail is already registered.
An unexpected error occured.
Please accept our Terms of Use.
Registration successful.

Sandeep Dawkhar



4 Ratings


Jan 3, 2019

As we come close to the end of the year, it is important to take a perspective of the changes that have taken place in industrial manufacturing processes this year, as these changes will not only percolate into the next year but will also mature further into hard implementation mode in factories across India.

We saw the advent of Industry 4.0 & Big Data; first as an introduction through Smart Manufacturing conferences and then through projects executed in some companies. What we will now see is the proliferation of projects across industry and challenges for companies that implement such solutions to provide a unique user experience for such solutions. This will mean that companies who operate in this sphere will need to have some USP, be it in the front-end template or Data Analytics or the ease of using the solution. The market will still be big enough to absorb many players in this space for years to come. Machine Learning will be the cornerstone of IoT projects and companies cannot avoid using Machine Learning and Data Analytics to implement process improvements on their shop floors.

As we move towards using Big Data for affecting process improvements, we will be subjected to data security concerns. Though data security solutions have matured over the years and currently use a hybrid approach of behaviour-based anomaly detection for threat identification and rule-based analysis for inspection, companies need to be careful of new threats that might come up with the advent of the huge quantum of data, which will be captured through a plethora of user devices for further analytics. As the number of connected devices and machines go up, so do the consequent challenges to avoid a cyber attack, especially when there are devices and machines using different architecture and platforms.

We will also see a significant change in technologies for robotics in the near future. With robots being used in a big way in industries, not only to do complex tasks but to fuse with other automation systems on the shop floor, the ROS framework will become mandatory for robot manufacturers. There will be an expectation from robots to be smarter, having a predictive maintenance suite. Robots’ self-performance and reporting will be a standard feature, with added system reliability. The major design goals being designed for them for the future are simplification, digitalisation and collaboration.

The acceptability for collaborative robots will go up significantly in the coming years. Most robot companies are already investing in R&D efforts in this space and we can expect companies to launch a few models catering to this requirement in the years to come. For collaborative robots, the challenges related to cost and safety continues. However, hopefully, companies will be able to work and resolve these challenges. Currently, cost and safety are the major two hindrances impeding collaborative robots taking off in a big way.

The future of automation is thus going to be simpler at the front-end for users, but complex to be able to process. Systems will be expected to be extremely reliable and intuitive to user needs. VR & AR technologies will revolutionise product development and manufacturing processes and will thus, provide a support for the design goals of simplification, digitalisation and collaboration.

Companies related to this article
Related articles