I have had a busy month. Good think I didn’t take four days to travel to Orlando. I’m wrapping up my last interview from there today. There are a few more pending if the media relations person can find a way to coordinate calendars.
This interview is with Kim Fenrich, ABB Global Product Marketing Manager, Process Automation, PC. He brought up the term “Digital Habitat”—something not found on the ABB website, but still an interesting concept.
The problem statement recognizes new people entering the industrial workforce. Many of these will not have much background in process operations. Meanwhile our digital technologies contain immense amounts of data that could be used to guide operators toward better decisions.
Fenrich brought a concept called Digital Habitat. This is the area alongside the core process control. This core contains monitoring and optimization. It houses process data. The data then gathers at the edge. In the ABB architecture, data at the edge becomes freely available to other applications, such as asset management and optimization.
Not all data is created equally. Some are “dirty” data that must be cleaned before using. Some is good data from trusted sources with solid metadata. These many applications ride atop the system to run analytics, support decision-making, optimize operations. Sometimes operators are new lacking operations experience and knowledge. Data science to the rescue to clean up and provide interfaces to support these new workers. Sometimes the data science supports engineers working in maintenance and reliability performing predictive analytics or enhancing asset management.
ABB had a suite of applications called the Augmented Operator. The system does pattern mining. Perhaps the operator sees something new. They can ask the system, “Have you seen this before? If so, what happened and how was it resolved?” This greatly helps the younger generation operator.
Should the situation be new to the system, then it can run simulations to predict outcomes and resolutions.
In short, the system:
- Freeing up operators time for more meaningful work such as using data and advanced analytics to optimise processes for energy efficiency and carbon emission savings.
- Enabling early warning of potential failure with AI-powered systems that can use real and historic data to offer troubleshooting solutions, much like a virtual assistant.
- Workflow simulation to check outcomes and for training and augmented reality (AR) headsets to access experts working offsite.
This is from the ABB web site. The next step to achieve this reality is to fuse together the Distributed Control Systems’, operations technology and real-time control system with the Edge and newer IT technology, such as machine learning and AI. As well as incorporating historical data and the mining of other data sources for pattern recognition and knowledge extraction. This will shift the automation system beyond only real time control to one that allows the operator to augment operations from day-to-day. It will be a journey, but humans working with technological systems to augment their cognitive capabilities can amplify their potential and provide huge value to both the workforce and the industry at large – as well as attract new generations to the sector.
