The Dataiku Solution for Batch Performance Optimization comes with ready-to-use insights to easily follow your production, identify the root causes of your process upsets with machine learning (ML), and understand failure prediction for the next batch.
Instantly ingest production process data from sensors or other IoT sources as well as transactional batch data through an intuitive Dataiku app without writing code or performing manual modification. Deploy the resulting insights and give access to Production Engineers and other technicians to accelerate monitoring and decision making.
With this Dataiku Solution, turn IoT data into insights and decision making drivers.
Predict risk of success or failure for recipes or products with a transparent ML model. Understand root cause, visualize insights on historical batch process performance, key failure patterns, and their impact on future success, then enable operators and maintenance to intervene before failure happens.
Perform AI-powered root cause analysis by studying sensor data per batch and recipe or product. The Batch Analysis Dashboard improves production performance by training and deploying current AI models and leveraging all relevant data for your equipment and its use.
With Dataiku’s comprehensive flow, get simple aggregations by recipe and equipment through advanced analytics, then process variability across batches. Leverage powerful root cause analysis on charts and graphics, then adapt the flow to your manufacturing process.
The Dataiku Solution for Batch Performance Optimization helps answer a broad range of questions like:
Enhance the capacity to dissect vast volumes of production process data and easily develop actionable insights for technicians, operators, and reliability and process engineers to understand root cause of failures and predict batch outcomes. Accelerate the move from reaction to anticipation in batch manufacturing.
A composite organization in the commissioned study conducted by Forrester Consulting on behalf of Dataiku saw the following benefits:
reduction in time spent on data analysis, extraction, and preparation.
reduction in time spent on model lifecycle activities (training, deployment, and monitoring).
return on investment
net present value over three years.