_Predictive Quality Analytics

Moving to the next generation of quality and process control with AI

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_Business challenges

1
Unstable product quality
2
Bottlenecks in production
3
Customer dissatisfaction
4
Costly warranty returns
5
Loss of corporate reputation
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_What is Predictive Quality Analytics?

It is an innovative quality assurance solution for manufacturing that analyses the process parameters in real-time to identify and diagnose quality issues before they become visible on the finished product. Our AI solution is backed by predictive quality analytics, which analyzes incoming data and predicts problem areas, so you can minimize losses.
Predictive quality analysis is a powerful tool for companies that want to improve the quality of their products and services and prevent potential problems. Businesses can save time and money and increase customer satisfaction by using this technique.
Experience predictive quality analytics in manufacturing with our intelligent machine learning and AI-powered solution.

_The Benefits of predictive quality analytics

With an entirely new way to look at data, TT PSC offers a unified solution that automatically collects, cleanses, enriches, and analyzes all production data, from start to finish, and solves analytics issues in your company.

Improving product quality
Identifying trends and patterns in data, allowing companies to make changes across their processes or materials to improve overall product quality.
Reducing warranty costs
Identifying and resolving potential problems before they occur, which can reduce warranty claims and save money.
Improving customer satisfaction
Detecting and preventing defects to improve the overall customer experience and increase customer satisfaction.
Reducing waste
Recognize where waste occurs. This allows organizations to take steps to reduce waste and improve efficiency.

_Discover how predictive quality analytics will work for you

Download materials with an overview of the entire process and discover what prerequisites you must have in place before starting a project and becoming data-driven organization
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_Features

Analyze manufacturing process
in order to derive meaningful patterns and construct corresponding machine learning model
Identification of quality issues
by constant monitoring of the production process
Dynamic quality control limits
are applied in real-time to specified signals instead of classical SPC (Statistical Process Control)
Quality prediction
for a given production batch based on historical data
Recommendations
for process optimization in order to maximize quality

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_Predictive analytics is driving Industry 4.0

Now you can find predictive quality analytics functionality in our comprehensive Industrial Analytics solution. All you have to do is meet with us, and we'll do the rest.

_Success Stories

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