We at ATSEDA have a long-time expertise in manufacturing, since we actually worked in the industry before our data science careers and we know the challenges first hand and speak your language.
Typically company data comes from an ERP system, machine sensors, CRM and time tracking applications. Depending on the application, new sources of data might be needed and we can assist you with the data collection.
Machine Learning to predict complex processes
Sometimes the underlying processes of a production facility is too complex to fully understand all details. A model which takes sensory data into account can be used to better control and understand the plant.
Predictive Maintenance helps to decrease down-time and reduces waste. The truth is that for the best results you need quite a lot of historic data. If you don’t have enough data we can still give you pointers on what data to collect and how to do it. For a successful Predictive Maintenance project data needs to be coupled with knowledge about the corresponding machine, which you can discuss with Thomas Gölles who is a Data Scientist and a Mechanical Engineer.
Quality control with image recognition
Automating quality control using machine learning can increase defect detection rates by up to 90%. A custom developed and trained neural network can detect errors and defects accurately, and therefore reduces the need for manual inspections significantly.
Dashboard of the most important information
A TV screen or monitor with up to date information in the production hall instead of stained and outdated printouts.
Your colleagues are informed about current downtime, target-time vs. actual time and much more. In addition several interactive dashboards in the production control console provide information to the head of production.
Supplier performance analytics
Find out which supplier has the best value before negotiating contracts when you consider for example down-time, labor cost, etc.
Use our data audit service to uncover what you can do with your data.
These are only a few examples of what can be done with data and advanced analytics in manufacturing. If you want to know more, please contact us.