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Big data in manufacturing processes

While the use of data in manufacturing processes is not new, the potential shift in scale of the type, volume and frequency of data collection is. This opens the door for new applications but also challenges how larger volumes of data are used.

Big data in manufacturing
Big data in manufacturing

How should big data be collected, handled and processed? According to a new white paper by PMMI Business Intelligence, there are a few areas that should be considered for data acquisition:

Infrastructure investment

Existing sensing capabilities, networks, data acquisition computers and local servers should all be considered. The level of investment varies, as some companies are ready to support a “digital path” strategy while others need to replace or retrofit large parts of the existing infrastructure. Upgrading bandwidth on networks, installation of additional sensing technology, or investment in local or remote data storage (local servers or access to 3rd party infrastructure) are common expenses.

Data collection

Inclusion of sensing on all assets can be extensive and quickly reach a point of diminishing returns. Asset prioritization can help to identify the impact of downtime on equipment in the production processes vs. the cost of adding sensing and networking and the ability to process and work with the additional data.

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