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IoT in manufacturing: The four stages of maturity

Suhas Sreedhar | April 3, 2017
Use cases in industries such as aeronautics and chemicals are a proving ground, and a roadmap to adoption is emerging

Although vendor-written, this contributed piece does not promote a product or service and has been edited and approved by our editors.

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Only a couple of years ago, IoT was still shrouded with intrigue and uncertainty. The integration of sensors, connectivity, and big data technologies made sense in the business world, but their true potential, implementation, and use cases were far from clear. There was a lot of talk about when exactly IoT would “hit” businesses. Today, instead of having a single demarcation point for IoT’s acceptance in industry, we’re seeing manufacturers adopt it in chunks. Quietly but steadily, IoT is reshaping different parts of the manufacturing process.

The use cases in industries like aeronautics and chemicals are a proving ground for the real-world potential of IoT. There’s a roadmap to IoT adoption beginning to form. It often starts with Enterprise Asset Management and goes from there, garnering more revolutionary potential along the lines of visibility and automation.

While individual companies will have different approaches to experimenting with and deploying IoT, we can break down the journey towards IoT maturity into roughly four stages:

1. Enterprise Asset Management (EAM): EAM is an approach to managing industrial assets holistically through the use of software.  IoT has already come into play with regards to “asset performance management,” using IoT sensors and connectivity to understand and predict when equipment will need maintenance or risk breaking down. 

By equipping industrial machines with IoT technology, companies can access waves of real-time data regarding performance, workload, stress, and a host of other significant variables. Analyzing this data, it’s possible to correlate factors that lead to equipment failure (including external factors like weather and temperature), and therefore proactively schedule maintenance to avoid costly downtimes.

Such use cases appear to be the gateway to IoT adoption for many manufacturing companies.  Proactive maintenance and real-time performance tweaks produce immediate cost savings, and help optimize output and efficiency. Manufacturers implementing IoT as part of the larger goal of EAM can finally start answering questions such as: what equipment will most likely need maintenance in the near future?  How can we adjust workloads to optimize output while minimizing strain?  What are the external factors most responsible for failures and how can we best control them?

2. Monetizing guaranteed performance: Taking asset performance management a step further, IoT won’t just prevent failures, but will also guarantee outcomes. Companies who primarily used IoT to monetize selling assets will be able to create new business models—forging contracts based on guaranteeing that their industrial assets will perform to a certain level.

Already, companies like GE are taking this approach with manufacturing customers. If executed well, this is a win-win for both buyer and seller.  Equipment companies can use IoT to grow new revenue streams, while manufacturers who implement “smart” machinery can rest assured that their investments will produce tangible results. Profitability will be the key metric at the end of the day. IoT-ensured performance will directly correlate to cost savings and efficiency.


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