TQS Integration, an international software consultancy company specializing in the provision of system architecture and application design, engineering, and system integration, today announced that they have been certified as a Google Partner with Google Cloud Partner Advantage.

Achieving Partner status means that TQS and Google can now share their combined knowledge and advanced technologies to provide the perfect end to end experience for their customers, from edge computing to automation, data historian to advanced data analytics and more.

“Obtaining Partner Status is a huge step into the future. It means recognition of our unique advanced technical expertise, and the ability to mutually share our learnings across a larger customer base with the Google team” says Rory Sheehan, Global Strategic Account Manager.

As a start, TQS and Google will focus their partnership on the Pharma / Lifesciences Industry where they have many mutual customers. Combined, their expertise and systems will allow customers to access manufacturing data, R&D data, operational data, and predictive data to streamline operations and quality.

“Our services will allow data sharing in a much wider capacity, both within the business and externally where required. With this partnership program and all our ongoing TQS developments, we are bringing customers, industries and partners into the future of manufacturing and that future is fuelled by data.” says Rory.

TQS has always been recognised for providing customers with an unrivalled service and advanced engineering, and this new Google partnership will continue to advance them into the future of Industry 4.0, IIoT and Edge Computing.

About TQS Integration

TQS Integration is a global data solution company specializing in the provision of system architecture and application design, engineering, system integration, project management, commissioning and 24x7 “follow the sun” support services to valued customers. TQS is at the forefront of data intelligence for over 20 years, working with extensive client base in the Life Science, Food & Beverage, Energy and Renewables industries. As the go-to partner for data collection, contextualization, visualization, analytics, and managed services, we are the main drivers in the world’s leading companies — helping them become leaders in Industry 4.0.

For information, please contact us.

Have you ever wondered if it were possible to predict process conditions in manufacturing? Know what is likely to happen before it actually happens in your business processes? Digital Twin might just be your answer.

There are several different definitions of Digital Twins or Clones and many use them interchangeably with terms such as Industry 4.0 or the Industrial Internet of Things (IIOT). Fundamentally, Digital Twins are digital representations of a physical asset, process or product, and they behave similarly to the object they represent. The concept of Digital Clones has been around for some time. Earlier models were based on engineering principles and approximations, however they required very deep domain expertise, were time consuming and were limited to a few use cases.

Today Digital Clones are virtual models that are built entirely by using massive historical datasets and Machine Learning (ML) to extract the underlying dynamics. The data driven approach makes Digital Clones accessible for a wide range of applications. Therefore, the potential for Digital Twins is enormous and includes process enhancements\optimization, equipment life cycle management, energy reductions, safety improvements just to name a few.

Building digital clones require:

1.      A large historical data set or data historian

2.      High data quality and sufficient data granularity

3.      Very fast data access

4.      A large GPU for the model development and real time predictions

5.      A supporting data structure to manage the development, deployment, and maintenance of ML models

The following shows the application of a Digital Twin to a batch process example. The model is built with 30 second interpolated data using a window of past data to predict future (5 min) data points:

So, what’s all the hype of Digital Clones? Well, not only are they able to predict process conditions, they also provide explanatory power on what drives the process - the underlying dynamics. The following dashboard shows a replay of this analysis including the estimate of the model weights:

Conclusion

In summary, the availability of enterprise level data historians and deep learning libraries allow Digital Clones to be implemented on the equipment and process level throughout manufacturing. The technology allows a wide range of applications and offer an insight into the process dynamics that were not previously available.

Please contact us for more information.

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