If “intelligent factories” are to live up to their promise, the global manufacturing business will have to develop software and analytical systems that can make sense of the deluge of data currently being generated.
Such is the headline finding of a new white paper released by IHS Technology, examining the challenges faced by Industry 4.0 – a term coined by Germany’s government to describe “a vision of computerized manufacturing with processes all interconnected by the Internet of Things”, in the words of Mark Watson, an associate director of industrial automation for IHS.
Watson says the potential stakes are enormous, with the global industrial automation industry generating revenues of $170.2 billion in 2013.
According to IHS forecasts, that figure is expected to grow to $182.7 billion in 2014 and $209.4 billion in 2016.
“Some believe that Industry 4.0 is expected to spur fundamental changes on the order of the steam-powered first Industrial Revolution, the mass production of the second, and the electronics and proliferation of information technology that characterized the third,” said Watson.
IHS refers to a number of examples of early developments in the Industry 4.0 area that have involved adding more flexibility and individualization to manufacturing processes.
For example, Foxconn (Taipei, Taiwan), which produces iPhones for Apple (Cupertino, CA, USA), is adapting manufacturing lines and processes so that it can be more flexible in meeting Apple’s demands.
The changes involve making extensive use of computer numerical code control machines that perform automated management of machine tools, says IHS.
IHS also cites the example of a leading food and beverage machinery provider that is working to enable the individualization of mass production by personalizing labels on the bottles of shampoos.
However, to achieve actual improvements in manufacturing efficiency and flexibility, manufacturers will have to be capable of managing and analyzing huge amounts of data, says the marker-research company.
One solution may be so-called “distributed intelligence”, whereby pieces of factory equipment become intelligent and autonomous enough to determine on their own which pieces of information are valuable.
The equipment can then report that data to decision makers in the organization.
IHS reckons organizations will implement changes gradually, giving them an opportunity to develop expertise in managing and analyzing large amounts of data.