The Perfect (Technology) Storm for Manufacturing | HCLTech
Manufacturing

The Perfect (Technology) Storm for Manufacturing

The technology conditions are perfectly aligned to create a storm of new activity for manufacturing. IoT technology is generating key data from sensors, PLCs, and scanners. Read the blog.
 
5 minutes read
James Dimarzio

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James Dimarzio
Consultant - HCLTech Manufacturing
5 minutes read
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The Perfect (Technology) Storm for Manufacturing

IOT, Cloud Data, and AI/Machine Learning

The technology conditions are perfectly aligned to create a storm of new activity for manufacturing. The IoT manufacturing technology is generating key data from sensors, PLCs, and scanners. The technology will check and measure many items necessary for manufacturing speed and quality of goods, but they also capture errors, anomalies, and out-of-normal specific conditions of the equipment. Much of this data may never be looked at due to the volume generated every minute as the IoT sensors are monitoring production operations. 

This volume of data has created downstream issues for infrastructure teams trying to store all of the information output. Traditionally these teams were asked to justify capital investments in storage to expand and hold this information in the data center.  Finance teams often raise questions about the capital expenditures needed to keep all of the data since historical use may be minimal. This is where cloud technology is providing a much easier way to expand the storage and justify its use as an operating cost. Assistance with access to the data and security may still be a service needed for many infrastructures and applications teams. Fortunately, HCLTech has been doing this for many companies and can provide a roadmap to ease the cloud data transition.

The analysis of this data as generated by the IoT technology has been done for some critical items. This includes maintaining production line speed, monitoring product quality, improving operational efficiency, and finally supporting quality issues reported by consumers. The maintenance teams at many manufacturing companies are not analyzing this information until an equipment failure. These teams often rely on preplanned timing schedules to perform preventative maintenance services on production equipment. Top companies have found the use of AI and/or machine learning tools as valuable options to proactively identify equipment maintenance needs. This type of predictive maintenance analysis may be considered a low priority due to unfamiliarity with the tools or the initial cost of the investment. Once again HCLTech has the expertise and ability to set up AI/ML tools quickly or even as a proof of concept to determine the real value.

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