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Garima Bharadwaj


Enlite Research

2 Ratings

TRANSITION OF MANUFACTURING INDUSTRY Deep Tech - Transitioning the manufacturing industry

Mar 8, 2022

IoT and AI will define the future of manufacturing - Garima Bharadwaj, Co-founder, Enlite Research

The last few years have been transformational for a lot of traditional industries. The trend of tech adoption which had been slowly percolating into these massive yet traditional industries has been expedited with the inflection point that COVID brought in. While manufacturing has been the backbone of economic development, volatility was the watchword even before the onset of the pandemic. Now, fast-forward to 2022, there is an increased need as well as desire for digitisation in this industry.

There have been a few tech adoptions that have happened in the manufacturing sector but none like the capability which the deeptech (AI, IoT & ML) will bring to this industry. Putting the smart in manufacturing.

The biggest challenge in this industry is to deliver the finest products and services at minimal costs in the shortest period of time. IoT and AI are creating new opportunities for the industry to enhance service, minimise downtime, increase productivity, while cutting manufacturing costs. With AI & IoT applications and advanced data analytics, manufacturers can access more assets, gain business insights from precise data in real-time and enhance day-to-day operational efficiencies and production performance.

So, where do AI & IoT help?

Predictive & preventative maintenance

One of the largest reasons for production downtime could be the smallest machinery breakdown. Some of the biggest downtimes for a production operation, the offline part or machinery, can be caused by a mechanical or electrical failure. But what if this failure could have been predicted or prevented? Usually, there are maintenance schedules for all individual machinery on documents or excel sheets which could be overlooked or forgotten by the person in charge and hence, the faults or failures occur. Using IoT devices, ML algorithms and digitised processes, the breakdowns could be predicted easily. Even the maintenance schedules are synced and optimised in real-time before the predicted breakdown, in order to keep the machines in working condition & the production floor running smoothly.

Smart manufacturing

IoT-driven manufacturing processes provide full visibility of assets, processes, resources and products in real-time, which can eventually result in streamlined business operations & increased ROI.

IoT enables connecting the equipment that can then integrate diverse industrial data, securing industrial systems for the entire lifespan of the machine. Leveraging connectivity enables data flow and provides the ability to monitor and manage processes remotely & keeping them agile in real-time, as per the need. This not only improves manufacturing processes & reduces wastages but also enhances the quality of the eventual yield.

Resource optimisation

In the manufacturing optimisation of resources, keeping costs under control and increasing productivity is critical. Utilising IoT and AI insights, it’s possible to utilise inputs, like usage data, machinery operational data and environmental conditions, combined with analytics, to provide for:

  • Improving worker safety & get a better workforce management

  • Increased worker productivity

  • Optimised energy consumption

It is no exaggeration to say that IoT and AI will define the future of manufacturing. The connected devices will see an exploding growth and a majority of that will be utilised in the manufacturing sector. AI embedded within IoT devices will inevitably continue to weave its way ever more tightly into all major manufacturing processes.

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