Digital Transformation through Industry 4.0.

"Their technical knowledge and ability to convey complex information clearly to our non-technical team has stood out"

MACHINE LEARNING & AI in manufacturing

Machine Learning (ML) and AI is the leading growth strategy for manufacturers in 2021. 

It can increase operational resilience & industrial sustainability as a core pillar and underpin several themes across Industry 4.0 and Smart Factory initiatives.

Manufacturers can improve efficiency, reliability, quality and sustainability standards as well as the robustness of their supply chain by investing in machine learning that provides the insights needed to take action and remain globally competitive.

Read on to find out more.

Anomaly Detection in Manufacturing

Predictive Maintenance

Manufacturers today want to know how machine learning can help maximise up time and make the most of their limited skilled human resource. Machine learning enables predictive maintenance by predicting failures before they occur, scheduling timely maintenance, and reducing unnecessary downtime.

The result is increased production and operational efficiency with the added benefit of:

  • Lower Maintenance Costs
  • Resilience
  • Sustainability
  • Automation

Anomaly Detection

Correct manufacturing flaws traced back to specific steps in the production process and reduce waste by detecting faulty components.

We employ supervised machine learning models to predict and understand spoilage based on material properties, production line state, and other factors. With data-driven predictions, manufacturers can make AI-based decisions that optimize best practices on the production floor. Even single-digit improvements in spoilage generate significant profits. Predictive AI will be quickly adopted into a production line norm.


Digital Twin in Manufacturing

Digital Twins (Industrial Control)

Digital twins can predict failures more easily, as they make it possible to virtually see inside any physical asset, helping identify the root cause of production problems, like assembly line faults, factory defects, or supplier errors.

By correlating smart factory data with digital twins, defects from manufacturing stages can easily be minimised, and by fully understanding the behaviour of production machinery, business owners can gain a better view of how product quality is being affected.

Leading Industry Insight

T-DAB.AI CFO & Chairman - Paul Calver

Manufacturers face constant challenges through mitigating disruption, adopting new technology and making better use of their data. Through Smart Factory and Industry 4.0 initiatives, manufacturers can quickly realise the value in their data and revolutionise their service offering, staying ahead of the competition in a highly competitive market. 

Paul Calver, Chairman

Get started with your Smart Factory & Industry 4.0 initiatives today

We know it’s imperative to deliver value to your organisation and it can be challenging to focus on the right project.

By working with T-DAB.AI, you can access an array of technical and domain knowledge, and before any project, we’ll work with you to:

  • Explore the possibilities for your business and educate your team
  • Target challenges that can be solved with data and analytics and calculate the value
  • Assess your data and provide recommendations to be delivered in-house


Book a call with our team to get started on your data analytics journey today!