Software

Manufacturing with intelligence: A framework for system-level anomaly prediction

It is time to put smarter manufacturing into production. An increase in the data and sensors available to the manufacturing industry has made it much easier to gather data on manufacturing efficiency through the internet of things. However, IoT systems tend to look at sensors at an individual level, which limits the ability to forecast anomalies across a manufacturing operation, as each sensor can measure only a specific part of the operation. To address this issue, a team of researchers has created a framework for system-level anomaly prediction in manufacturing.

Manufacturing intelligence: Keep processes under control

A trend in manufacturing is toward tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production costs, product waste and the need to rework faulty products. To satisfy the customer demand behind this trend, manufacturers must move quickly to new production models. Quality assurance is the key area that information technology must support.

Using edge computing in manufacturing

As manufacturers invest in industrial internet of things-enabled devices to collect more data throughout production processes, many are also deploying edge computing to improve the analysis of data. Edge computing uses dedicated, on-premises resources at the shop-floor level rather than the remote servers that cloud computing relies on. This significantly increases the rate and amount of data that manufacturers can process in real time.

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