Manufacturing & IoT

Manufacturers need to maintain highly demanding standards of operational precision, efficiency, safety and quality. They need AI that can navigate complex global supply chains and leverage vast IoT data to continuously improve performance. But current machine learning systems fail to separate signal from noise in manufacturing time-series data. 

causaLens uses Causal AI to find the real drivers of supply chain dynamics and the manufacturing value chain, enabling leading manufacturers to solve their biggest challenges.

Manufacturers are looking to AI to improve throughput, energy efficiency and profit

Operators often still rely on their experience, intuition and judgement. However a multitude of signals need to be monitored all at the same time, resulting in urgent activities getting prioritized even though they don’t necessarily add value. Manufacturers are turning to Machine Learning to help ease this burden, but current AI techniques often fall short:

  • AutoML is limited in its ability to effectively incorporate domain expertise, yet at the same time it cannot function independently of the direction of highly skilled operators.
  • Non-causal ML techniques are likely to include spurious correlations, so asset optimization does not reach its full potential.

Solutions

Efficient predictive maintenance can only be achieved with root cause analysis. Existing correlations-based predictive maintenance models often fail to distinguish between causal relationships and spurious correlations. At the same time they fail to adapt to changing conditions in the environment. causaLens autonomously discovers causal relationships in real-time enabling businesses to optimize the maintenance of their systems

Directly tune your production level to the most profitable one. causaLens autonomously predicts demand for products in real-time and takes into account the cost and profitability of the production lines in order to optimize the production level. It also allows you to seamlessly add and analyze macroeconomic data in your models to enhance your infrastructure investment planning.

Improve yields and customer satisfaction by detecting faulty products faster. causaLens helps you autonomously understand the areas that are at higher risk in real-time. It also empowers users to automatically assess the impact of potential interventions in the production line without the need to resort to costly trial & error.

Why causaLens

Which level is your organisation in?

0

No Machine Learning

  • Do you think it would take you years to become an AI-driven Enterprise?
  • Is the value of your enterprise’s data asset largely unrealised?
  • Are the predictions, insights and business decisions compromised due to human error?
  • Are resources wasted improvising solutions to problems that could be better solved with ML?
1

Manual Machine Learning

  • Is it hard to build and retain data science teams?
  • Does it take months or years to achieve real business impact?
  • Is the team mostly reactive, responding to requests from business functions for analytics?
  • Does your team spend their time implementing repetitive & expensive processes?
2

Automated Machine Learning

  • Do you find that generic Data Science Platforms overfit & underperform?
  • Do you have trouble translating predictive models & predictions to real value for the business?
  • Are generic platforms not flexible or transparent enough while failing to incorporate your domain expertise?

The State of AI in Supply Chains

Learn how Causal AI can be used to enhance Supply Chain modelling by listening to ‘The State of AI in Supply Chains’ panel at the Ai4 Supply Chain Conference.

Start optimizing your business today

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