The potential of predictive analytics for machine builders

March 29, 2016 // By Martyn Williams
The cost of production downtime varies significantly from one industry sector to another, but without a doubt, when it occurs, downtime is a troublesome and expensive inconvenience for all manufacturers.

More often than not, halts in production could be avoided, so imagine just how much manufacturers could save if machine data was available to anticipate breakdowns. The good news for industry is that the rise of the Internet of Things (IoT) is allowing machine builders to design and manufacture intelligent machines with predictive analytics capabilities.

 

Preparing for the smart era

Common causes of production stoppages on the factory floor include aging equipment, human error or incorrect machine usage. To minimise downtime caused by unplanned maintenance, manufacturers have always sought to predict issues with preventative maintenance initiatives. The advent of the Industrial Internet of Things (IIoT) enables companies to look for ways to exploit increasingly available production data and change the way they operate.

Spearheaded by internet-enabled technology, the manufacturing sector is bearing witness to the next industrial revolution. Connected machinery is causing a shift in the way the industry operates, making production lines more efficient, agile and more self-sufficient. To pave the way for the smart factory, machine builders need to equip their solution with the right tools for data collection, analytics and connectivity.

To simplify this transition, machine builders can future-proof their products to leverage the growing network of smart devices in industrial facilities and the increasing amount of data from the factory floor.

 

Using data to deliver

Smart data from IoT-enabled equipment can be employed to forecast the degradation of industrial machinery. Predictive analytics enable trend analysis, reviewing the operational data of equipment to uncover if and when a machine is likely to break down. In addition, pattern recognition can decode the relations between certain processes and product failures, enabling fast identification of the cause of equipment breakdown - priceless insight that industrial machine builders can offer their customers.

To collect, archive and analyse complex industrial machinery data, machine builders need HMI/SCADA software capable of high performance. When combined with a cloud computing platform capable of storing big data, such as Microsoft Azure, good HMI/SCADA software provides clear data visualisation for operations, supervisors and managers - giving plant managers and engineers the peace of mind that everything is running smoothly. In fact, predictive analysis for industrial machinery could constitute an entirely new revenue stream for forward-thinking, entrepreneurial machine builders.