Taking the guesswork out of maintenance

Medium-voltage drives are often exposed to extreme stresses that can cause wear and tear over their lifetime. Without regular maintenance, damage often goes undetected until an equipment failure. Kevin Wissner, R&D Department Manager at Siemens Large Drives Applications shared his thoughts on improving the data quality of medium voltage drivers to reduce downtime.

Few could have predicted Industry 4.0 – an industrial revolution not quite like its three predecessors. This is a gamechanger, across all industries, but it is in particular in the maintenance sector that one can find its true value. From steam power back in the 18th century when the world first industrialized to the introduction of new sources of power such as oil and gas, mechanization and mass production have taken manufacturing by storm. Over the past 50 years, computers have been integrated into operations and automation has become the norm. For Wissner, there is much to be excited about when it comes to Industry 4.0 and the developments that it brings. “This is more than just increasing automation but about the deployment of smarter features to deliver smarter machines for smarter factories. The discussion is now about data and how we can derive value out of it to improve efficiency and manage cost in our businesses.” When it comes to medium-voltage drives, Wissner says there is real value in investing in smarter machines and exploring what that can mean to an operation. Data, he says, is the driving force in this new environment.

The 5 V’s

Data explains Wissner, has 5 common characteristics. “The first is volume. The amount of data that you have is important. The second critical V is variety – you need different formats of data being produced from various sources. Then the value of the data is important. Some of the data collected will be of no use, so the ability to extract the useful data is what matters.” The other characteristic is velocity. In the fast-paced modern world, the speed of data accumulation and the speed at which it can be extracted and used is what are of critical importance. “Lastly, is the veracity. This is important because typically in any big data there will be some inaccuracy and this characteristic speaks to being able to identify the inconsistencies that exist in the data and getting rid of that.” With about 80% of businesses only in the early stages of industrial digital transformation there is still a huge amount to be learned and gained from this new industrial revolution, says Wissner. “To date, one of the reasons why we have not seen a faster transformation is due to the lack of data. Historically, industrial type businesses and processes have not been focused on data gathering and so the systems are simply not in place to capture the data that can be used to drive the improvements.” Big data analytics, artificial intelligence, and other innovative technologies have also been found to be more effective in the later stages of digital transformation.

Changing environment

According to Wissner, equipment design is the first step to improving data quality and visibility. “We are now introducing smarter medium voltage drives. A smart system has three major components.