or what the useful bearing life should be , is all residing within the ET ( or engineering design ) systems .
Traditionally , each of these systems operates independently and generates a lot of data that is seldom used or cross-referenced . To acquire a holistic overview of the motor , we integrate information from all of these systems and store the relevant pieces in a contextualized data model . This allows us to visualize and activate optimum equipment operation for the best overall process results .
A motor is just one example . In a large manufacturing plant , there can be hundreds of such assets performing several functions and running under different operating conditions with varied design parameters ; all with data stored in various systems .
Widespread OT / IT / ET integration and contextualization is , therefore , critical to obtain a complete view of the plant and carry out valuable analytical tasks that improve operations , asset integrity and performance management , safety , sustainability , and supply chain functions . What emerges are patterns that accurately predict future behavior , allowing improved process performance .
We have been using AI / ML to deliver a higher degree of prediction accuracy and optimization to operations , processes , and assets . Combining AI with deep industrial domain expertise empowers operators to run their industrial processes safer , more effectively , and more sustainably .
There are several barriers — perceived and otherwise — that hinder the implementation
Combining AI with deep industrial domain expertise empowers operators to run their industrial processes safer , more effectively , and more sustainably . of advanced analytics . The most common reason for hesitation is the perceived complexity . People mistakenly think it is much more difficult to achieve than it is . Another explanation we get is the incorrect belief that , to use big data , you must make massive capital expenditures , because it is an “ all or nothing ” undertaking . It is not as you can start with small steps . Other reasons might be lack of cooperation between OT , IT , and ET people , and just generally slow adoption of new digital tools in many industrial sectors .
The fact is that it is easy to join this digitalmaturity journey , no matter where you are , using data and signals that are already available in your process control , business , and engineering systems .
For further information , please visit www . new . abb . com
Issue 61 PECM 7