What if you could use advanced analytics to envisage events prior to them happening, utilize real-time actionable insights to increase manufacturing and help your operatives know the right decision to take at any given time?

Industrial IoT is driving such capabilities enabling unparalleled operational efficiency, productivity, and performance like never seen before. Industry experts have predicted that by 2022, IIoT will be a $225 billion market that will have enormous impacts in modern manufacturing including increasing efficiency, fostering streamlined maintenance, asset monitoring and much more to create a new age of industrial growth and competitiveness.

Manufacturing industry leaders residing in IIoT are reporting benefits, such as efficient and increased productivity according to a TATA Survey. It’s thus crucial to be aware that IIoT use cases will progressively expand in future. Here’s a compilation of the best three industrial IoT work with cases in Manufacturing that our IoT consulting team recommends.

Real-time Asset Monitoring

Manufacturing companies are utilizing IoT assets to connect machines and systems together — a paradigm shift that enables real-time asset tracking. Coupled assets offer the chance to monitor gear in real-time for reliability, compliance, and safety.

Asset monitoring is heavily utilized in distant manufacturing where sensors help tracking production procedures and deliver status to the ideal personnel. It also offers a platform to manage and control assets for enhanced operation and manufacturing; enabling proactive and timely manufacturing decisions.

Asset tracking in manufacturing allows easy status monitoring of crucial equipment and final products; to augment logistics, sustain stock and prevent quality issues.

Connected Operational Intelligence

By linking machines/equipment, manufacturers can generate intelligent networks that communicate and coordinate with each other autonomously with minimal involvement by operatives

With this use case, organizations can amass and contextualize data from remote manufacturing assets and systems into actionable applications. As a result, providing proactive perspectives into key performance indicators thereby enabling quicker problem identification to improve operational performance.

Furthermore, through IIoT, companies can currently connect to disparate operational data centers and unify them to enable real-time data visibility across assorted manufacturing systems. IoT enabled machinery thus enables connected operational intelligence, which transmits real-time insights into manufacturing stakeholders enabling them to remotely manage factory units.

Predictive Maintenance of Assets

Millions of dollars go into machine operational and maintenance costs. But if equipment maintenance is done in time, it would prevent pauses on production processes. And if downtime can be detected before it knocks, Manufacturing companies can have substantial decrease in operational expenses. The use of sensors, data analytics, and cameras in IIoT allow machines to predict failure before it occurs.

Such detection aids create strategic maintenance timelines that can be performed only when required — prior to glitches happening — believe repairing a crack in the dike. Manufacturers leverage IoT to include vibrant, capable, and automated manufacturing processes, where maintenance programs are autonomous rather than relying on undependable maintenance personnel.

Thereby, triggering better-planned maintenance processes which promises huge cost savings in turn reducing equipment failure and increasing machine lifetime.

Summary

Industrial IoT has the ability to radically transform manufacturing. As the global market and business dynamics push manufacturers to reconsider operations, smart manufacturing powered by IIoT-driven data analytics is essential.

The reality is that more and more data will be created from increasingly linked gear systems and that to realize critical & valuable actionable insights believed IIoT is infinite.

About the Author

Cesar Agostino

Hardware and Software Design Leader in 4i Platform.

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