Considering industrial equipment manufacturers, life has never been easy for them entirely. Across the globe, the manufacturing sector has experienced the jolt of multiple forces and trends. This makes it inevitable for them to deal with macroeconomic and political volatility along with adapting to an ever-changing legion of disruptive digital technologies. Predictive analytics, additive manufacturing, and the Industrial Internet of Things arising out of ever-growing IT solutions for manufacturing industry are a few of them.
On top of that, one must continuously rethink their overall functioning in the digital era, right from creating a connected workforce to enabling predictive maintenance.
All this must be done along the lines of rising industrial consumerism. A shift where consumer-style expectations penetrate every part of their value chains. Combined, they all add up to a vigorous pressure to innovate. More than half of industrial equipment executives, who are directly or indirectly involved with manufacturing, believe that industry is facing at least moderate disruption.
Artificial Intelligence in manufacturing: fuelling the growth
The thrust of Artificial Intelligence (AI) is thus coming at an ideal time for the sector. It contains the potential to aid industry players perform at unsurpassable speed and scale, as well as facilitate the reduction in costs. This in turn transforms customer experiences for the better.
Artificial Intelligence is a combination of different technologies like a machine and deep learning, analytics, computer vision etc, all working and evolving together enables machines to simulate human intelligence. Computers and machines are able to sense the world around them, comprehend it, and then act accordingly. And all of this, without too much of human Intervention.
Smart machines and computers have replaced labour activities with faster and more accurate intelligent automation, augmenting workers as they perform higher-value tasks, and making the capital stock more productive, AI will undoubtedly bring unseen growth to the industry.
The larger benefits of fusing AI in the industrial equipment sector are crystal clear. Regardless of the mould they fit in, whether in digitally focused innovation, enhancing the user experience, bringing new levels of operational efficiency, or in an entirely new competitive edge, the technology holds huge potential for companies who are ready to take the leap of calculated faith into intelligent operations. There is no shortage of innovative examples that lie in front of them for inspiration.
Today, there are companies portraying inspiring use cases from the electrical equipment sector who are leveraging analytics and deep learning to drive predictive maintenance and breakthrough advances are being achieved by heavy equipment companies all over the manufacturing world.
How can companies surpass this challenge and be prepared for the future
For companies to overcome the rising challenges, industrial equipment companies will need to develop a completely new set of operating capabilities, right from the value chain to procurement and talent to after-sales service.
Marketing & Sales:- More and more companies will adopt a more consultative selling approach, that goes beyond the overall mindset of selling products to working with AI-driven intelligent sales solutions.
After-sales service:- Dealers and shops providing after-sales service will need to keep the technology engineers readily available so as to curb maintenance problems in embedded systems. By successfully developing these capabilities, one will be able to hinge on data. Most of these companies should be ready to capture information in numerous formats from numerous sources like assets, employees, customers, weather conditions, traffic, and, majorly, suppliers.
Manufacturing and design:- In terms of developing the core algorithms behind machine learning/deep learning and developing AI-embedded products, it will be a gigantic task for industrial equipment manufacturers. They will need to develop complex design processes that contain sophisticated prototypes. The data that gets captured from AI-enabled products should be provided back to the R&D development in order to improve the product development process through a continuous feedback loop.
In order to remain competitive and differentiated when companies make investments in AI, they will have to shift their thinking above and beyond short-term gains. These companies which take the lead in overcoming the challenges, and collaborate wisely with their wider ecosystems, are set to be the leaders of tomorrow.
Currently, we are only seeing a fraction of what AI has to offer to us. And, these companies have barely scratched the surface of the potential and possibilities of Artificial Intelligence.