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Measure, manage, and operationalize your sustainability goals – including decarbonization, energy resources management, and reduced WAGES.
Achieve operations visibility and AI-based optimization, linking plant-floor actions to your enterprise sustainability initiatives.
A system of record to automate accurate GHG data collection, provide valuable insights, and identify ways to reduce carbon emissions
One modular solution to connect, see, control, and optimize DERs from a technical and an economic standpoint
Reduced operational costs and risks using Digital Twins, machine learning and predictive models
Increased network reliability
Advanced analytics to predict future asset and process performance for reduced variability and improved operations
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Optimize assets and processes – from plant-level operations to the enterprise – with self-service process analytics software.
Minimized potential impact of anomalies
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Performance Intelligence with APM Reliability is your partner in meeting your plant and fleet performance goals.
Predictive analytics software, helps prevent equipment downtime by detecting, diagnosing, forecasting & preventing emerging failures.
The AI-powered product automatically explores the space of operation of gas turbines, builds a machine learning model, and continuously finds the optimal flame temperatures and fuel splits to minimize emissions
BoilerOpt works within existing plant technology to improve boiler productivity and air-fuel ratios in a closed-loop system
Pre-built templates for equipment health monitoring, asset strategies, and process workflows
Operator rounds efficiency and operational impact
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Addressing fuel usage, carbon emissions, airspace efficiency, predictive maintenance, and more
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Reduced environmental footprint
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A globally recognized benchmark for procurement of OT secure products.
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Native cloud service for a data historian.
Safe and secure management and orchestration of the distribution grid
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Overcome foreseeable load variations
Minimized disruption of service even in extreme weather conditions
Effective management and orchestration to unlock the power of renewables and DERs
AI/ML energy market recommendations to improve profit for renewables and thermal generation assets
Increased output and energy production at times of highest demand
A common network view to ensure electrical integrity, network validity and infrastructure management
Accurately model your asset network, support traceability, help assure data completeness, & support integrity management
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Software designed to help grid operators orchestrate the grid
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Holistic performance management for today’s connected enterprise
Management of fast-moving processes as well as slower moving, labor-intensive jobs
Cost savings with improved manufacturing overall equipment effectiveness
Batch automation, regardless of the underlying equipment
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Unified manufacturing data from disparate systems to better meet changing consumer demands
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Best practices for your industrial processes to help build and maintain operational resilience
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Facilitate documentation between airlines and lessors
Reduced costs related to disruptions with real-time visibility
The cornerstone of your journey to operational excellence
Operational excellence including improved reliability, reduced costs and managed risk
GridOS, the first grid software portfolio designed for grid orchestration
Reduced operational costs and risks using predictive models
Enhanced overall situational awareness
Field-connected operations and management
One modular solution that enables grid operators to connect, see, control, and optimize DERs from a technical and an economic standpoint
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Reduced operational and new build costs and improved field inspection productivity
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Optimized operations to best meet changing consumer needs
Reduced variability and improved operations.
In-depth understanding of our software and its functionality
A clear a path to operational transformation
Maintain consistent quality and reduce cost per ton
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Streamlined end-to-end operations driving high-volume, high-quality production
GE Digital software is the backbone of modern plant operations
Improved reliability, increased availability, and reduced O&M costs
AI/ML to make your gas turbine's fuel and air controls smarter
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Inclusive outsourcing services that deliver best-in-class results
Achieve digital transformation
Expert service teams to maximize the benefits from your IIoT software
Reduced costs, lower risk, and faster response times
Analytics to predict future asset and process performance for reduced variability & improved operations
A common network view to ensure integrity, network validity and infrastructure management
Mission critical software to better operate, optimize and analyze your work to deliver results
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More efficient and secure electric grid, greater sustainability and waste reduction
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Using Digital Twin blueprints, GE's Industrial Managed Services team monitors 7,000+ global assets
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Experience in leading edge software development and business working with best-in-class leaders
Understand how Electrification software and services helps our customers solve today's toughest challenges
Output improvement
Earnings
Approximate annual additional production
Herning Vand
Water/Wastewater
Proficy CSense
Based in Denmark, Herning Vand strives to efficiently deliver clean water to its customers.
”Big Data” has become a buzzword and everyone agrees that it is worthwhile to explore the large volumes of data. Herning Vand has invested in an advanced calculator that can help to interpret their process data and already in the first project they came across particularly valuable knowledge.
A spreadsheet can be used to handle relatively large amounts of data, but it will not work when there are too many parameters in play simultaneously. Therefore, last spring we invested in Proficy CSense software solution, which is dedicated to finding and using mathematical correlations of large amounts of data.
Jan Ravn - Chief Operating Officer, Herning Vand
For years, Herning Vand has recorded and saved a large amount of process data that is collected online from Herning Vand’s 14 purification plants.
The data is logged with the clear intention to make Herning Vand wiser and therefore better equipped to optimize processes and the overall operations. However, for that to happen the large volumes of data must first be sorted, analyzed, processed, evaluated and thoroughly compared so that the important correlations and trends can be localized.
However, Proficy CSense shall, just like other simulation tools, be used shrewdly and Herning Vand, together with process consultants from COWI who were responsible for the initial consultancy, gained some valuable experience. COWI assists Novotek, a GE Digital partner, with process technical advice in connection with the use of Proficy CSense.
We have achieved some excellent results with our first project and we see a great future optimization potential with the tool.
“I see Proficy CSense as a closed box that is filled to the brim with advanced calculation routines. We just feed the box with the data we want it to compute and then we tell it what parameters we want to observe.
Proficy CSense finds the right mathematical description of the data stream and can then show two curves of the same data stream. One curve contains the actual data and illustrates the process as it was in reality. The other curve is generated by the mathematical model that Proficy CSense has set and therefore shows a simulated process.
When the program is fed with multiple data streams at once, it automatically locates the possible relationship that exist between the different data and that is exactly what we are after.”
— John Sorensen, Senior Project Manager for water and wastewater at COWI.
Modeling of variations in ammonium concentration. Proficy CSense has generated a model where the result is shown by the blue line. The red line is the measured values.
Simple comparison of trend curves to get a quick overview of the situation. The figure shows the ammonium concentration in four process lines.
When CSense has found the mathematical models and correlations, the user can then determine which parameters to focus on and what to look out for. Just like when you insert different values into an equation. Here it is just an automated solution to an almost unlimited number of equations.
We can find correlations that we did not know existed and our theories can be confirmed or dismissed. Once we have located the significant correlations, we can begin to optimize the process based on this new knowledge. If, for example, I want to have output A as high as possible, how should I then set inputs B, C and D?
The first project, which was the optimization of the gas production that is based on sludge from the purification plants, gave an output improvement of as much as 20%.
The gas is used for electricity production and according to Jan Ravn the increase corresponds to an annual additional production of approximately 400,000 kilowatt hours, which earns Herning Vand approximately DKK 500,000.
Herning Vand is now engaged specifically in a series of small defined projects that will ultimately achieve the goal of making Herning Vand energy neutral.
We knew roughly which buttons we had to press to achieve this gain and so CSense should not take all the glory. However, the tool makes it much easier for us to check the accuracy of our assumptions and it can also show us the way to the process-related correlations that we cannot find ourselves.
The advice from Jan Ravn and John Sorensen is that you have to be good at defining the amount of different data that CSense works with and you get the best and fastest results if you have relatively robust process knowledge.
The more data you put in means you get more answers out at the other end. However, there is of course an upper limit, and too many parameters in play can make it difficult to understand the results.
As Jan Ravn explained, "Our advice to new users is that you start simple and carefully consider both what it is you want to have answers to and also what parameters are likely to affect these answers. If you do not know exactly which parameters affect your focus area, you can gradually reduce the number using Proficy CSense as you test each one. When the data streams are recorded and analyzed they fit together mathematically, so when you adjust each parameter up and down with the mouse, you see how the other parameters are affected to either go up, down or remain unchanged. When you have isolated the relevant parameters there is the option to activate the tool to simulate towards an optimum process within a given framework."
The first project is only the tip of the iceberg in relation to what we expect to achieve with Proficy CSense. We have an ambition that the tool will be used regularly for small and large projects, and therefore assist us to pick all the low-hanging fruit that would otherwise be missed during a busy working day. The findings are instantaneous and the application potential is great.
Download Herning Vand's story.
Proficy CSense uses AI and machine learning to enable process engineers to combine data across industrial data sources and rapidly identify problems, discover root causes, and automate actions to continuously improve Quality, Utilization, Productivity, and Delivery of production operations.
Read how global leader Rockwool is using Proficy CSense to help automate control of a complex production process, including environmental facilities…
Learn how Lonmin, the third largest producer of Platinum Group Metals, drives improvements in its smelter area through operational transparency.
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