Huntsman’s Journey Towards Analytics Maturity & Operational Excellence
Learn how Huntsman used TrendMiner self-service analytics in its digitalization evolution and production optimization to establish 24-hour engineering support.
About Huntsman
Huntsman Corporation is a publicly-traded global manufacturer and marketer of differentiated and specialty chemicals with 2021 revenues of approximately $8 billion. Their chemical products number in the thousands and are sold worldwide to manufacturers serving a broad and diverse range of consumer and industrial end markets.
Solution & Implementation
This problem was solved by adopting TrendMiner self-service analytics which allowed process experts to do the data analytics themselves, thus moving their data skills closer to that of the data scientists. The process experts now had a tool that they could use to analyze the data giving them data-driven insights to make data-driven decisions.
The next step was to capture a way of working so that the personnel would successfully adopt and use self-service analytics. With any new work approach, personnel need to have the ‘mindset’ to
use the new tool and to want to make it a success. It was decided to solve this challenge by showing quick and important wins. Personnel were willing to adopt self-service analytics once they saw how using it could substantially ease their work and improve operations.
Also, with any new work approach to be successful,
‘methods’ and ‘management’ have to be in place. Huntsman created a standardized plan for implementing adoption which included proper management support. With these three aspects in place, Huntsman overcame these challenges allowing the organization’s workflows to go from an experience-driven to a data-driven work.
Use Cases
Use Case 1
Setting Soft Sensors For Product Quality Monitoring
For years, a Huntsman continuous isocyanate plant had been collecting daily process and offline-created lab analysis data, both of which were stored in the historian database.
Solution
Early in 2016, the company’s teams used TrendMiner to build soft sensors on operating conditions to predict product quality for certain Isocyanates. The process experts in turn used these to make micro-adjustments to process setpoints to pro-actively minimize impurity levels.
As an example, one of the monitors predicted hydrolyzable chloride levels in the final product, and by tweaking vacuum pressure conditions, the impact on product quality was mitigated. In addition, monitors were set up to send out early warnings to tell the operators not to load trucks, preventing off-spec material from going to a customer.
Results
TrendMiner made it possible to have 24/7 quality control compared to a quality control situation with lab analyses that were only available for regular weekday work hours. With trucks being sent out 7 days per week, the soft sensors eliminated 75% of the expensive off-spec transportation cases which occurred on the weekends. In addition, a significant positive impact on lead time was achieved as unnecessary wait hours for the in-spec products were eliminated, with the average lead time being reduced by several hours. Finally, the extra insights on product quality also reduced the demand on lab resources as the number of uncertain situations for this specific product was reduced by as much as 10%.
Use Case 2
Use Case 3
A complete Six-Sigma DMAIC analysis was performed using the various capabilities of TrendMiner. The analysis included using value-based searches, layer comparisons, statistical comparison tables, scatterplots, filtering, and the recommendation engine.
With the use of TrendMiner self-service industrial analytics, Huntsman process experts:
Became “analytics enabled” so they could fully leverage sensor-generated time-series data.
Eliminated data silos.
Became much more effective in coming up with solutions for operational problems.
Compared past patterns looking for good and bad production behavior.
Reduced off-spec batches.
Performed fast root cause analyzes on much larger data sets.
Improved product quality.
Optimized each phase of the classic DMAIC cycle in the Six-Sigma methodology.
Download The Full Huntsman Success Story
Download this free PDF and learn how Huntsman used TrendMiner self-service analytics in its digitalization evolution and production optimization to establish 24-hour engineering support.
Huntsman Global Advanced Analytics Democratization
Huntsman started their digitalization journey some years ago and one of the quickest wins was to leverage time-series data. As operational data is still kept in separate silos, this adds an extra challenge to improve operational excellence by use of advanced analytics.
Discover how self-service analytics helps to make process and asset experts at Huntsman contribute to corporate operational goals such as improving plant safety, improving product quality, and increasing capacity without CAPAX.
“TrendMiner provides us with 24-hour engineering support, so we are able to optimize processes and asset reliability and run our plants more stably … a more reliable and stabler site is a safer site.”
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