Predictive Quality Analytics
Quality 4.0: Leveraging on your data to achieve best in class output!
What we do
We understand the high-quality standards of the industrial sector and its need for continuous innovation and output optimization. By combining our client’s quality management expertise and production data with our predictive analytics know-how, we can identify root causes and early recognize or even prevent quality issues. This is an iterative process . We use various data analysis techniques and state of the art machine learning algorithms to develop robust models for our customers.
These models help to improve the quality of products and simultaneously result in decrease of scrap, warranty claims, rework cost as well as quality-related machine downtimes.
Together with an interdisciplinary team from both the client's side and craftworks, the concrete questions that should be answered were evaluated.
Using the gathered data from different production steps, we develop a machine learning algorithm that detects quality problems and its root causes. The results are being visualized in a way that makes it easy for the client’s operators to read and understand how the system and its recommendations work. After a successful proof of concept, the algorithm can be transformed and applied to other production machines step by step.
In a next phase, instead of acting upon recommendations from the system, the settings of parameters can be automated. The result: an even more efficient process and better quality assurance.
How you can work with us
A selection of our Industrial AI clients
With craftworks it was simple and uncomplicated. After an initial conversation, we could start a project within a short amount of time. While the data scientists at craftworks supported us in drawing valuable conclusions from our data, the close collaboration together with their domain experts made it possible to have fast results within a month.
Wien Energie, Head of Innovation and Strategic Projects