Putting Big Data
to Work

October 2013


Technologies ranging from supervisory control and data acquisition to enterprise resource planning have made factories smart, and they are getting smarter every day.

At a missile plant in Huntsville, Ala., for instance, Raytheon Corp. monitors its assembly operations down to the turn of a screw. If a screw is supposed to turn 13 times after it is inserted in a missile component, but it turns only 12 times, an error message flashes, and production is halted until the anomaly is understood and rectified.

Just how much smarter factories can become will be determined largely by the research and development of systems to manage information. Smart factories, after all, are part of the phenomenon popularly known as Big Data.

The challenge of Big Data is that it requires management tools to make sense of large sets of heterogeneous information. In the case of a factory, sources of data include CAD models, sensors, instruments, internet transactions, simulations—potentially, records of all the digital sources of information in the enterprise. The data bank is large, complex, and often fast-moving, and so it becomes difficult to process using traditional database analysis and management tools.

Raytheon’s monitoring technology is often called “manufacturing execution software,” and several manufacturers are currently using MES to collect and analyze factory-floor data. The systems enable the real-time control of multiple elements of the production process.

Industry stands to reap many benefits from Big Data as more sophisticated and automated data analytics technologies are developed. These technologies will help extract value and hidden knowledge from large, diverse data streams.

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