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How 15 Companies Successfully Leverage Operational Data

These manufacturers dramatically cut costs and improved production with TrendMiner

In the era of Industry 4.0, manufacturers are constantly searching for solutions that can unlock the full potential of their operational data. Some have found great success by applying advanced industrial analytics. Not only does it provide operational experts with the information they need to make daily decisions, but it also fosters collaboration between local experts and central data scientists.

In a new E-book, leaders from global companies share how they used TrendMiner to drive improvements, optimize production, and achieve operational excellence. How Leading Manufacturers Benefit from Advanced Industrial Analytics looks at how industrial organizations use our software in the field. They also talk about its benefits—from saving money on energy consumption to improved development of machine learning models.

Democratizing Data for Informed

Decision-Making

In today’s data-driven world, access to information is essential. However, many companies grapple with fragmented software environments that lead to siloed information. That means data remains locked away and is not available to everyone who needs it. A common thread among the success stories, be it ARLANXEO’s journey to decrease costs or Arkema’s digital transformation initiative, is TrendMiner’s ability to democratize data. With TrendMiner, operational experts get a more holistic view of operations and a solution that fosters a culture of informed decision-making.

Boosting Operational Efficiency and Savings

At the end of the day, the value of any solution depends on how much it contributes to the bottom line. CP Kelco, a specialty hydrocolloids producer, realized dramatic savings with advanced industrial analytics. By harnessing the power of TrendMiner, the company is on track to save a staggering $1 million annually. Similarly, Bayer Crop Science, faced with unique production challenges that affected the addition of starting material in a reactor, turned to TrendMiner for insights. Engineers saw a 10% increase in production capacity.

Ready to Achieve Operational Excellence?

The stories of these 15 companies exemplify the tangible benefits from applying advanced industrial analytics software to operational data. They demonstrate TrendMiner’s commitment to provide deep insights, streamline operations, and foster a culture of data-driven decision-making. With TrendMiner, the future of industrial analytics looks brighter than ever.

Download the new e-book for free

Predicting Future Maintenance Needs

The ability to anticipate problems before they escalate is invaluable. TrendMiner offers predictive maintenance capabilities that help engineers create maintenance schedules. Enerjisa Üretim, with a diverse portfolio of power plants, was facing anomalies that traditional methods couldn’t resolve. Within a week of deploying TrendMiner, engineers not only identified root causes for a dozen anomalies but also set up a predictive maintenance schedule. Such proactive measures minimize downtime, ensure smooth operations, and optimize output.

Safety and Environmental Concerns

No discussion about industrial operations is complete without addressing personal safety and the environment. TrendMiner helped companies bolster their safety measures and mitigate environmental risks. For instance, CURRENTA, operating in a highly regulated market environment, leveraged TrendMiner to detect creeping leaks in their system. Similarly, Kuraray expanded its use of TrendMiner to ensure plant safety and address environmental concerns proactively.

Anomalies: Challenges Turned Opportunities

A powerful feature of MLHub is the ability to detect challenging anomalies. LANXESS, a global chemical company, had persistent flooding issues in its field compressors. In this case, digital sensors all appeared to be normal. However, through collaboration with central data scientists, operational experts created an anomaly detection model that provided early warnings of flooding, even when conventional readings appeared normal. This proactive approach didn’t just resolve the immediate problem; it led to savings of more than €1 million.

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Companies have many decisions to make about how they will explore and use operational data.