AI-Enabled Autonomous Optimization for Continuous Manufacturing

The Future of Manufacturing is Here

The ProcessMiner™ AI platform is autonomous manufacturing made simple. Our industry leading autonomous control solution delivers process improvement recommendations and parameter control changes in real-time to the production line. Our platform ensures reductions in scrap, defects and errors commonly encountered in complex manufacturing processes.

Manufacturing + ProcessMiner = Sustainability Goals

Manufacturing Operational Improvement

  • Address Skilled Labor Shortage
  • Improve Product Quality
  • Increase Yield
  • Increase Throughput

    Manufacturing Sustainability Improvement

    • Save Energy
    • Reduce Emissions
    • Reduce Chemicals Usage
    • Save Raw Materials
    • Decrease Water Usage

    Monetize Your Data

    Step #1: Collect Clean, Relevant and Actionable Data

    The first step in the optimization process is to access the historical data kept on the server and analyze it for data quality and consistency. This analysis will determine if the data collected is clean and consistently formatted for the purpose of optimizing the manufacturing process.

    Continuous Quality Improvement is Our #1 Goal

    ProcessMiner’s predictive system solves problems before they happen, by making recommendations and prescribing solutions in real-time. In doing so, ProcessMiner™ minimizes raw material usage and reduces other costs, while maintaining both speed and product quality.

    Modeling and learning

    Turn-Key, AutoPilot Solution

    Easily and quickly deployed turn-key solution for manufacturing processes allows manufacturers to do analysis without a staff of data scientists.

    Data Assessment

    Advanced Data Science

    We pair data science, technology and industry expertise to unleash the full potential of digital manufacturing: complete autonomous control for continuous quality improvement.

    Monitoring and Prediction

    Real-time Anomaly Detection

    Real-time artificial intelligence machine monitoring, predictions, prescriptions and recommendations, gives manufacturers access to metrics both off- and online.

    AI Optimization in manufacturing

    Closed-loop Control

    Predictive to root cause automatic vision control. Our AutoPilot platform achieves unprecedented autonomous, closed-loop control of machines for continuous manufacturing.

    Partner and Affiliate Organizations

    Autonomous Manufacturing Made Simple


    Monitoring historical data ensures you’re collecting clean, relevant, trustworthy and actionable data to relay back to the server.


    Machine-learning system begins predicting performance measures and identifying improvement opportunities.

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    Easy to read suggestions for minimizing variability though improvement, preventative and corrective actions.

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    Closed Loop

    Through our predictive machine learning and artificial intelligence systems, real-time recommendations are automatically sent for autonomous manufacturing.


    Continual improvement that optimizes process performance and variability. The longer it’s used, the more ProcessMiner improves.


    With good, clean data in hand, applies advanced data science and machine learning techniques to your manufacturing process to find insights and impact ROI.

    What We Do

    Continuous Quality Improvement

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    AI-enabled autonomous optimization for continuous manufacturing

    Reduce energy consumption, raw materials and chemicals usage

    Build a real-time AI platform that is self adaptive & evolving

    Meet and exceed quality specs through reducing variability

    Research & design to solve manufacturing problems and improve quality

    Case Studies

    ProcessMiner™ Director of Science, Chitta Ranjan, shares his extensive research on data in the manufacturing industry.

    LSTM Autoencoder for Extreme Rare Event Classification in Keras

    LSTM Autoencoder for Extreme Rare Event Classification in Keras

    Here we will learn the details of data preparation for LSTM models, and build an LSTM Autoencoder for rare-event classification. This post is a continuation of my previous post-Extreme Rare Event Classification using Autoencoders. In the previous post, we talked about the challenges in an extremely rare event data with less than 1% positively labeled data.

    A lot of what Solenis provides is helping our customers meet a specific quality objective. We were aggregating data and visualizing it for our customers to show value for the programs we had, but we weren’t actually doing stuff with that data. A big piece of the analytics space we were struggling with was there was no focus. We met with many vendors, big and small, different sizes and countless specialties. That’s when we came across ProcessMiner. ProcessMiner was very focused on quality. We went with ProcessMiner.

    Tony Lewis

    Global Product Manager, Solenis

    Contact Our Data Science Team

    Fill out the form below and we’ll get back to you, or contact us by phone to speak to a miner today.

    Have a project in mind?

    For more information, download our brochure. We’ll reach out to you!

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    U.S. Headquarters

    715 Peachtree Street NE
    Suite 100
    Atlanta, GA 30308
    +1 (678) 463-5799



    Oy ProcessMiner Ab
    Otakaari 5
    02150 Espoo
    +358 400 450 748