Optimize manufacturing processes to improve products and enhance brands

Manufacturing businesses rely on continuous improvement and innovation to thrive. But today, innovation is not just about manufacturing new products – it’s also about using data to improve every aspect of operations. With data science, manufacturers can find new ways to improve quality assurance programs, reduce equipment downtime, manage supply chain risk, and forecast demand. Manufacturers embracing data science to the fullest can dramatically improve core operational functions and see their products and brands stand out in the marketplace.

Ensure high product quality

Detect production issues early on and evaluate the impact on your business. Provide input to product design and operations to fix the issues before they become a problem.

Learn more about quality assurance

Anticipate maintenance needs

Identify potential problem equipment that will impact your business and needs fixing. Reduce maintenance costs through preemptive maintenance scheduling.

Learn more about predictive maintenance

Manage production risks

Identify potential risks to production from vendor problems to weather to macroeconomic issues. Score supplier quality and accuracy and detect issues that need your immediate attention.

Learn more about risk management

Forecast demand for better planning

Gain insight into demand for products to allocate production resources in the most cost- and profit-efficient way. Ramp resources up and down and retool at optimal times.

Learn more about demand forecasting

Maximize productivity

Use data from your production processes to optimize productivity while keeping product quality high and deterioration under control.

Manufacturing Use Cases

“This manufacturer sees lots of opportunity for data science to improve product quality and production yield, many involve predicting with great precision exactly how a step in the production process should be executed, to maximize the desired results.”

“The data science team uses the insights gained from RapidMiner to adjust practically every aspect of its operations to reduce customer support costs and improve its customer experience.”

Lightning Fast Data Science

Built for analytics teams, RapidMiner unifies the entire data science lifecycle from data prep to machine learning to predictive model deployment. Organizations can build machine learning models and put them into production faster than ever, using RapidMiner’s lightning fast visual workflow designer and automated modeling capabilities. 400,000 analytics professionals use RapidMiner products to drive revenue, reduce costs, and avoid risks.