Whether you want to add context to your production data, improve product quality or gain insights into your energy consumption, self-service industrial analytics help you imagine what the future may hold.
Self-service industrial analytics solutions are used by process engineers daily to uncover thousands of opportunities for optimization, often increasing overall profitability. This is where TrendMiner comes in; offering engineers the tools to analyze all the data themselves and find new ways to improve operational performance.
Here are some real-life examples of companies using TrendMiner:
- Solve previously unsolvable issues
Sitech is an organization that provides services and solutions to chemical organizations, including maintenance, technological improvements, and Advanced Process Control. They use TrendMiner to contextualize asset performance with process data.
For example: After washing out a chemical, carbon dioxide peaks caused high downstream process temperatures – but they did not know why. Using TrendMiner, Sitech easily identified a previously hidden influencing process variables, identified as the root cause, through comparative analysis of peak and normal operation periods. Additionally layer comparison helped identify those influenced variables, allowing for stabilization, increased production, and a 5% revenue increase resulting in $2.4 million annually. Effectively Sitech solved the chemical wash-out problem in only 2 hours, saving over €1.8 million per year.
- Enhance reliability, quality, and profitability
Ashland is a $5 billion specialty chemical provider. To support the transition of their Belgian plant manufacturing pharmaceutical-grade ingredients in a GMP (good manufacturing process) production environment, Ashland used TrendMiner to assure reliability, quality and GMP compliance.
For example: Ashland wanted to control all mill influencing factors, such as air flow, temperature, humidity, process upstream, and other parameters. They accomplished this by conducting comparative analysis of on- and off-spec production, utilizing TrendMiner to identify those influence factors. This allowed them to control the product density, directly impacting product quality, monitoring those factors, and increasing on-target GMP production from 70% to more than 95%.
- Reduce energy consumption
Covestro is a leading chemical company producing polyurethanes, polycarbonates, and specialty chemicals. To improve control and gain insights into energy consumption at its Antwerp plant, Covestro uses TrendMiner industrial analytics in combination with process data captured in OSIsoft PI.
For example: Covestro previously used Excel to monitor energy consumption year on year. It could verify positive progress but managing big process data in spreadsheets made this a cumbersome exercise. With TrendMiner, Covestro was able to visualize annual energy usage in layers and compare time periods.
By combining process data captured in OSIsoft PI with the pattern recognition of TrendMiner, Covestro is now able to quickly and easily monitor and track their energy consumption.
- Inform decision-making
Arlanxeo is a world-leading chemical company manufacturing synthetic high-performance rubber. Arlanxeo uses TrendMiner industrial analytics to leverage digitalization at the operational level, leading to gained process insights and informed decision making.
For example: Arlanxeo needed to investigate the impact of a different supplier’s new raw material on reactor run time and quality indicators. It had been previously considered unlikely feasible within the production process.
With TrendMiner, Arlanxeo was able to identify the parameters that would need adjusting in order to use the alternate material. Deeper insight into the process enabled Arlanxeo to make an informed decision about the material they were analyzing. It also gave them more freedom in selecting future suppliers and responding to changes in raw material prices.
- Improve overall equipment effectiveness
Total Refining & Chemicals (R&C) transforms crude oil and natural gas into finished products, or intermediates used to manufacture chemicals. Total R&C uses TrendMiner to improve the effectiveness of its equipment and contribute to data-driven decision making.
For example: In order to optimize plant production, Total needed to define normal operating windows. With TrendMiner, Total used historical data to define operating windows and fingerprint the pattern. This pattern could then be used for easy comparison of batch production for different grades and triggering pre-maintenance notifications. The potential to increase productivity and plant availability based on easy data exploration and analytics is so great that Total decided in 2017 to roll TrendMiner out globally across their R&C segment.
TrendMiner offers engineers the tools they need to analyze all the data themselves and find new ways to improve operational performance
Find out more by clicking below.