Transmission & Distribution Technology
images in the construction of the 3D models, machine learning algorithms will provide even greater context, a predictive capability and deliver more informed business insight to the user, resulting in faster and more reliable decision making. Although machine learning gives the
impression that human involvement is minimal, this is not the case. It gives the user more intelligence, context and insight to make the decision-making process easier and improve productivity. For those adding machine learning to their asset management journey, the next logical step is to go model-centric by adding visualisation dashboards, cloud-based IIoT data, analytics and reality models to machine learning. With a machine learning strategy in place it will give users unprecedented insight into their operation and lead to benefi ts in effi ciency, safety and optimisation, as well as the speed in which decisions can be made. With the arrival of the IoT, data is
growing and becoming more accessible. With the ability to acquire more data, more advanced technologies are required to scrutinise and fi lter out the important
Data from physical assets can be sent to 3D modelling software
information and the value held within. But, it can only be exploited by identifying what works well and what does not. Machine learning features complex algorithms to sort through large amounts of data, identifying patterns and trends within it, to make predictions. T e use of machine learning in electrical utilities doesn’t have to stop at just transmission and distribution, but can be applied across the whole operation, where algorithms are used to continually improve overall performance across the whole facility and the equipment within it, and directly to
the individual customer. By combining these machine learning practices with the IIoT and visual operations, they will bring, as they mature, signifi cant benefi ts. T e IIoT, engineering models, and machine learning should no longer be considered just buzzwords. Instead, combined, they should be a priority for achieving operational excellence. ●
Richard Irwin is with Bentley Systems.
www.bentley.com
Intelligently combined
www.bosch-industrial.com
Three good reasons for combined energy systems from Bosch: Reduced energy costs for higher competitiveness Cost-saving own power generation and maximum waste heat recovery Eligible energy management (EN 50001)
www.engineerlive.com 15
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52
