The use of a time series database is helping MAN Energy Solutions (MAN-ES), a German industrial equipment manufacturer, derive data visualization and real-time analytics to help its customers get closer to Net Zero.
That’s happening through its analysis of “billions” of time series data points across thousands of MAN-ES assets.
This data is then being pumped into customer management systems to get an accurate view of past, current, and future operational performance, and is helping avoid things like the needless use of fuel and other techniques to curb emissions.
In the words of its Chief Digital Officer, Gregory Puckett:
What we’re offering is constant advice on the safe operation of your asset, which can inform our customers in a very clear way on the condition of the engine, but also be able to go deep with the engineering knowledge to help them troubleshoot more complex problems.
The context of all this is that MAN-ES - an Augsburg, Bavaria based subsidiary of Volkswagen - is all about producing big engines and related equipment.
That includes everything from heat pumps to steam and gas turbines to the propulsion systems operators of container ships use to drive their fleets to pipeline and gas storage solutions for the oil and gas sector.
MAN-ES got to its current position due to its long legacy of innovation. Puckett says:
“When MAN was making steam engines, a guy by the name of Rudolf Diesel said, ‘Hey guys, I've just ended up with a really cool engine that runs on diesel, let's move to that.’ So, we're home of that core transport technology.
Though it has roots that stretch back two and a half centuries, says Puckett, the company is very much focused on the future.
Today, that centers on helping clients across all the industries it serves achieve more sustainable operations.
For example, it offers industrial-scale heat pumps for de-carbonizing heat supply, which can be used to supply industrial plants or even entire cities with climate-neutral heating and cooling.
It also offers solutions for separation and capture of excess CO2 during the production of cement, as well as other green tools for use by the chemical industry.
Right now, shipping is a key focus of decarbonization for MAN-ES.
That’s because this is a sector that is trying to put the work in to make itself less environmentally negative.
The EU has stated that global shipping “spews out” three percent of worldwide greenhouse gases, for example, and the UN is calling for all ocean-vessel emissions to be cut in half by 2050.
That means MAN-ES must help, says Puckett:
A typical cargo vessel will use 4.5 million gallons of fuel oil a year. If we can save 2% of that, that’d be a big helper of getting us further to everyone’s de-carbonization goals.
Using data analytics and IoT to optimize ‘big things’
In response, the company is developing engines for ships and power plants that can run on synthetic fuels, such as methanol, ammonia, and synthetic natural gas.
And in aid of meeting its aim of helping its customers in this sector achieve sustainable value creation in the transition towards a carbon neutral future, the company has built a new tool - an IoT (Internet of Things) platform called MAN CEON.
This securely connects MAN-ES machinery in the field - or on the sea lanes - to a German-based Amazon cloud.
This is the main way, explains Puckett, that accurate and extensive data analytics are generated to understand how a turbine or ship engine is performing. The data the software produces can also be used in other MAN-ES digital products and services for help in predictive maintenance and other operational metrics.
The idea is to help fine-tune performance, says Puckett:
MAN CEON allows us to leverage our engineering competency in daily interaction with the customer.
In a commercial shipping context, this could be to help the operator optimize fuel consumption and to ensure a vessel is always within emission limits while still providing the required level of engine power.
This is necessary as technology advancements in the field mean that old-style metal-bashing engineering doesn’t really work for new fuels like green methanol, he notes:
So, the chief engineer or the superintendent whose workload has doubled and gotten more complex now has a new virtual buddy who really knows the system.
MAN CEON is also constantly ‘on,’ collecting data, he adds.
That means customers can look at MAN CEON dashboards via a web application or mobile app, but sensor data is constantly being fed back to the company’s HQ where it is also constantly monitored.
All in all, the company claims MAN CEON can reduce fuel utilization by up to five percent for large vessels - which adds up to tens of millions of euros annually.
The ingredients for that understanding of 'what happened when'
Key to delivering those levels of increased efficiency via analytics is time series.
A time series database is one optimized for tracking and monitoring of time-stamped or time series data.
Typically, this is things like server metrics, application performance monitoring, network data, sensor data, events, and other types of analytics data.
The main features of a time series solution are that it includes support for accurate data lifecycle management, summarization, and the ability to conduct scans of records at scale.
Puckett says that when building MAN CEON, it soon became clear that these kinds of features would add a significant technical edge to the solution:
The reliability and maintainability of an engine relies on really understanding what happened when. And that ‘what happened when’ has to be very precise, because you're ingesting data at a very large frequency.
What a time series provides us with is really the ingredients for that understanding of what happened when - particularly if you want to get into early prediction of failure, where you really need to know the current state of an asset versus what it was five minutes ago - telling the underlying story behind what otherwise just be fairly dry metrics.
Here, Puckett says time series delivers much more precision than just putting data into a data lake, which would just deliver a summary of events.
To do this, Puckett and his team selected a time series data tool to do this called InfluxDB.
This is marketed by a company called InfluxData, which Puckett sees as “the gold standard” for time series data tools.
The tool became part of MAN CEON six years ago.
Puckett sees its support for handling large volumes of data and the reliability and accuracy that it delivers the main ongoing benefits of using the approach.
Next steps for use of time series in MAN CEON includes a move from using it as part of a hosting-in-the-cloud approach to moving it as a service out of the vendor’s own secure ISO cloud.
That will allow his team to go back to a full focus on that “moving big things to zero” mission.
Digitization can stand alone, but de-carbonization without digitization is impossible.
Those are the two key pillars of our strategy, de-carbonization and digitization. And therein lies the need for time series.