TwinThread: Speed and Visibility with Predictive Operations
If you are looking for greater production or cost efficiency, to effectively use your current data, or allow operators the power to find new opportunities, you may want to consider predictive analytics.
Predictive analytics could play a key role in making your data work more effectively, in a manner that suits engineers.
TwinThread has given insight into how the Predictive Operations Platform is timely, cost effective and uses innovative ideas for long term results.
‘Time is Money’
To get the most from Predictive Operations it’s important to understand what your provider aims to achieve and how quickly you will see results.
The provider will understand the importance of proving value fast.
“whatever predictive solution your organization pursues, it has to connect to your existing data sources easily and quickly,” according to TwinThread in their article ‘Powering Digital Manufacturing Transformation’.
“In the Litmus Test of assessing a prospective platform, whether it’s capable of drawing on your existing information has to be very high (if not first) on your list of prerequisites.”
Ultimately, the statement ‘Time is Money’ reigns true in most business practices.
When pursuing a goal, such as production or cost efficiency, it is necessary to deploy a system that can actively analyze production data, enabling your operations team to make further improvements to current processes.
TwinThread prides itself in achieving fast results within days by providing a solution that is simple for operators to learn and apply.
“If it’s slow out of the gate, because it’s difficult to connect, this is just pushing the time to insight further out,” adds TwinThread.
Any engineer or operator can use TwinThread’s platform to model their factory and scale learnings quickly.
Creating a Digital Twin
A useful component for continuous improvement, in production, is a digital twin.
“Bringing your data to life by pairing insights with illustrated representations of the assets your experts interact with day in and day out allows for faster and more comprehensive understanding and a more risk-based approach to scaling operational improvements.” TwinThread explains.
A virtual representation of production can give insight into its overall performance in real time, and creates an easier process of diagnosing potential issues or anomalies.
“By visualizing your information through these ‘digital twins’, operationalizing insights happens faster and more accurately.”
Uncovering insights within your data at a higher speed and with greater accuracy means optimizing the value your machine and human resources can deliver - resulting in maximum payback.
AES Corp seals 10-year carbon-free energy deal with Google
The AES Corporation has struck a 10-year supply contract with Google to provide near-carbon-free energy to power its Virginia-based data centers which will start later this year.
Claiming the first clean energy procurement deal in the world of its kind, AES will help ensure that the energy powering those data centers will be 90% carbon-free when measured on an hourly basis.
AES will become the sole supplier of the data centers' carbon-free energy needs on an annual basis, sourcing energy from a portfolio of wind, solar, hydro and battery storage resources to be developed or contracted by AES.
The agreement marks an important step in meeting Google's previously announced goal to run its business on 100% carbon-free energy on an hourly basis by 2030.
"Last year, Google set an ambitious sustainability goal of committing to 100% 24/7 carbon-free energy by 2030. Today, we are proud that through our collaboration with Google, we are making 24/7 carbon-free energy a reality for their data centers in Virginia," said Andrés Gluski, AES President and CEO. "This first-of-its-kind solution, which we co-created with Google, will set a new sustainability standard for companies and organizations seeking to eliminate carbon from their energy supply."
"Not only is this partnership with AES an important step towards achieving Google's 24/7 carbon-free energy goal, it also lays a blueprint for other companies looking to decarbonize their own operations," says Michael Terrell, Director of Energy at Google. "Our hope is that this model can be replicated to accelerate the clean energy transition, both for companies and, eventually, for power grids."
AES assembled the 500MW portfolio from a combination of AES' own renewable energy projects and those of third-party developers, which were selected, sized and contracted to meet Google's energy needs across a number of considerations, including cost efficiency, additionality and carbon-free energy profile.
The portfolio assembled by AES is expected to require approximately $600 million of investment and generate 1,200 jobs, both permanent and construction, in the host communities. These efforts will greatly simplify Google's energy procurement and management at a competitive price while decarbonizing Google's load and the broader PJM grid.
This supply agreement follows on the strategic alliance AES and Google formed in November 2019 to leverage Google Cloud technology to accelerate innovation in energy distribution and management and advance the adoption of clean energy. AES is pioneering greener, smarter energy innovations, with the goal of expanding the services available to large-scale corporate customers.
The Google.org Impact Challenge on Climate commits €10M to fund bold ideas that aim to use technology to accelerate Europe’s progress toward a greener, more resilient future. Selected organisations may receive up to €2M in funding and possible customised post-grant support from the Google for Startups Accelerator to help bring their ideas to life.
Last year it issued $5.75 billion in sustainability bonds to fund ongoing and new environmentally or socially responsible projects. To read its 2020 Environment report, click here.