How is Data Science on IoT Devices a Game- Changer for Industry 4.0?

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The digital transformation of manufacturing/ production and related industries and value creation processes is so significant that we have started calling it Industry 4.0. It is like a fourth industrial revolution and represents a new stage in the organization and control of the industrial value chain.

With the advancement in the hardware of IoT devices and their capabilities to capture vast amounts of data, there is a need to have comprehensive real-time analytics capabilities to solve the most critical use cases and develop a more optimized process. For example, if you want to understand if the cold chain is being maintained while transporting covid vaccines from India to Barbados, we need sensors to capture the temperature regularly and send us alerts if we go beyond the permissible limits.

“The ability of sensors to understand physics reveals some of the real-time contexts around a given person/assets which if analyzed effectively can enable a huge set of new services.”

Here we will discuss a few such use cases where analytics on data generated by IoT/ Sensor devices (IoT data analytics) can help in significant optimization of the entire supply chain process and lead to substantial dollars of savings.

  1. Predictive Maintenance – This is an essential use case as it can lead to a lot of dollars’ worth of savings. Using all the data generated by the sensors on an asset, we can create models that will help us predict any fault or part failure. Hence, the entire process can be optimized as we can anticipate failures, act before a failure happens, and in turn reduce the downtime. This will lead to overall better performance and better
  2. Digital Twin – This is another critical use case where we create a digital twin of the asset, which essentially means we have a real-time dashboard that helps us monitor our asset’s health and utilization and look out for any anomalies/trends in its working. This ability to have a real-time eye on your asset digitally helps you monitor and utilize it more
  3. Conditional Monitoring – Ensuring On-time and in-full delivery of your products is the most important aspect of any manufacturing process. With modern age sophisticated IoT sensors, we can monitor real-time temperature, tilt, weight, spoilages of our cargo. In cases like maintaining the cold chain and perishables cargo, this helps ensure that the quality of the delivered goods is as per the agreed
  4. Overall Optimized Process – IoT Analytics helps in answering the big four questions in any manufacturing process
    • What to produce?
    • How to produce?
    • When to produce?
    • How long does it take to produce?

Using appropriate IoT devices, one can answer these questions, leading to an overall optimized process.

Altogether, the rise of the cloud, IoT platforms, and powerful AI chips provides a platform for a new generation of software and optimization, which has immense potential to optimize our current supply chain processes and create smart factories and self-adaptive well-connected AI-enabled supply chain management systems.

~ Nishkam Shivam, Data scientist @ Bristlecone | Ex- Walmart | Ex- Accenture

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About the Author

Senior Content Contributor, Emeritus Blog
Varun, a seasoned content creator with over 8 years of diverse experience, excels in crafting engaging content for various geographies and categories. Leveraging this expertise, he seamlessly translates complex concepts into enriching educational content for the EdTech domain. His keen understanding of research and life experiences helps him resonate with students and create fact-based content. He finds solace and inspiration in music, nurturing his creativity for content creation.
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