Reining in on industrial automation: cloud computing

May 09, 2017 // By Johannes Petrowisch
The domestic canary isn’t what most of us would consider a tool for industrial labour. But in 1988, hundreds of these birds were made redundant from their small, yet significant roles in Britain’s coal mining industry.

Earlier mines lacked air ventilation, which meant these ill-fated birds were favoured as the gas detectors of choice. Today, advancements in connectivity and the introduction of cloud computing are making monitoring industrial environments a lot more sophisticated.

 

Head in the clouds

In recent years, we’ve heard a lot about cloud computing, but its role in the manufacturing industry is not always clear. Manufacturers are not well known for investing heavily in the latest IT systems and technologies on a regular basis, so why are so many now deploying cloud computing software in their organisations?

As industrial automation becomes more intelligent and manufacturers embrace machine-to-machine (M2M) technology, cloud computing is set to become the obvious solution to store and manage the ever-growing expanse of production data. Aside from increased storage space, the cloud helps manufacturers to reduce costs, change business models, provide new services, increase agility, optimise performance and ultimately, drive profitability. 

 

Energy data management

For industry, there are few topics as widely discussed as the European Union’s Energy Efficiency Directive. However, performing a meaningful evaluation of a manufacturing facility’s energy efficiency is only possible when energy consumption figures are available in a complete manner. To make sense of the copious amounts of data produced on the shop floor, many manufacturers are deploying energy data management systems (EDMS).

Generally, EDMS is set up locally and embedded into the existing IT infrastructure, but there are a number of different scenarios available, including moving the EDMS to the cloud, a possibility which enables company-wide analysis of energy data.