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M2M financial predictions finally begin to garner greater respect for smart manufacturing
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M2M financial predictions finally begin to garner greater respect for smart manufacturing

Posted by Jeremy CowanApril 5, 2014

(Blog) — According to the Cisco white paper, Increase the Value and Relevance of Data in Motion, by 2017 there will be 1.7 billion wireless M2M (machine-to-machine) connections across the supply chain. As Thomas R. Cutler says, embedded in this estimate is the calculation that smart factory technology will create US$1.95 trillion in value by 2022 by improving control, agility, and flexibility in manufacturing processes.  

These data do not reflect money spent, rather money saved due to lean, more efficient practices. Intel has made similar predictions.

This seemingly sudden interest in the Industrial Internet of Things (IIoT), is finally garnering manufacturing the respect and attention it deserves. After being neglected by computer technologists and innovators for the past 15 years, manufacturing and industrial automation organisations have not taken full advantage of the latest advancements seemingly axiomatic for other sectors from medical to media and web searches.

William Sobel, CEO of System Insights and architect of the MTConnect standard remarked, “Even without the love of the technology companies, manufacturers were still able to produce amazing amounts of high quality products with incredible accuracy, but there is a lot of room for improvement.”

Industrial Internet of Things: The next level

The transformation of raw data from manufacturing equipment and sensors to actionable information requires four areas of innovation.

Standards are needed allowing the data to be communicated in common formats so that every application and value added service does not have to independently integrate with every provider of manufacturing equipment and sensing device.

Manufacturers must make use of cloud services – scalable storage and computation solutions – to recognise the patterns and correlations in the raw data that identify quality and production losses without excessive infrastructure investment.

The IIoT solution must provide information in real-time, what Cisco terms “data in motion,” where good and bad patterns can be detected and losses predicted before they occur.

Perhaps of greatest importance is the need to demonstrate, validate, and quantify the value received from the improvements derived from M2M solutions.  This requires an effective business intelligence tool.

MTConnect: The industrial standard

In the manufacturing sector, MTConnect has become the de facto standard and enabled the industry to move from multitudes of custom data sources to a common format and delivery mechanism.

This essential standard provides both security and simplicity for application developers and according to Sobel, “MTConnect provides data in a common vocabulary from every device and reports the numeric values in standardised units. It uses XML and HTTP to make it easy to use and is read-only for security and safety. We can provide a common transport and format for all manufacturing data from all devices – reducing the complexity and increasing the value delivered by applications.”

Big data analytics are the key to uncovering the hidden patterns in the streams of data. Raw data is noise without proper context and understanding of the underlying processes that created it. Only small amounts of value can be created by analysing the data in the absence of the manufacturing process. To achieve the levels of return projected by Cisco, data must be contextualised to the manufacturing process.

IIoT in a manufacturing context

Understanding the tooling used, the type of materials, the cutting conditions, and the operations being performed is idiosyncratic to the manufacturing sector. Understanding the tolerances and constraints on the final product cannot be ignored. The VIMANA platform provides the is first Big Data platform specifically designed for manufacturing; it is used by universities in three countries for advanced manufacturing research demonstrating a unique ability to contextualise the complex streams of manufacturing data.

Thomas R. Cutler, CEO of TR Cutler, Inc

Thomas R. Cutler

The author of this blog is Thomas R. Cutler, CEO of TR Cutler, Inc., (www.trcutlerinc.com). He founded the Manufacturing Media Consortium, and writes more than 500 manufacturing feature articles annually. You can follow him on Twitter @ThomasRCutler.

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Jeremy Cowan

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