Webinar on Demand
Self-service analytics in practice
Real-life examples of making data actionable
Duration: 60 minutes (52 minutes presentation + 8 minutes Q&A)
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Video Chapters Overview
00:00 Introduction and Agenda
The webinar is focused on practical applications of self-service analytics in optimizing manufacturing processes. Fredrik Mote, a Customer Success Manager at TrendMiner will demonstrate how self-service analytics can transform process data into actionable insights, driving improvements in plant performance across various real-life use cases.
02:15 Role of TrendMiner in Process & Asset Analytics
Dive into the core functionalities of TrendMiner and how it serves as a critical tool in process and asset analytics, helping manufacturers gain a competitive edge through data-driven insights.
02:15 Use Case 1
Avoid Bottlenecks to Increase Production Efficiency: Explore a practical scenario where TrendMiner identifies and resolves bottlenecks in a manufacturing process, significantly improving production efficiency and throughput.
04:34 Use Case 2
Control Fouling to Improve Asset Availability: Learn how TrendMiner’s predictive analytics capabilities enable proactive maintenance strategies to control fouling in critical assets, thus enhancing their availability and reducing downtime.
15:55 Use Case 3
Distillation Column Trip: Examine a case where TrendMiner helps in diagnosing and preventing unexpected trips in a distillation column, ensuring continuous operation and preventing costly shutdowns.
25:42 Use Case 4
Compare Current Batch to Golden Batch Fingerprint: Understand how TrendMiner’s analytics compare current batch processes to a ‘golden batch’ fingerprint, ensuring quality and consistency in production outcomes.
37:06 How to Gain the Benefits at Your Site
Gain insights into implementing TrendMiner at your facility, highlighting the steps to integrate this powerful analytics tool into your existing processes for immediate ROI.
52:05 Q&A
Conclude with a Q&A session, addressing common queries about TrendMiner’s application in process manufacturing and how it can be tailored to meet specific industry challenges.
This webinar showcases TrendMiner’s capabilities in leveraging self-service analytics for process optimization in the manufacturing industry. Through four detailed use cases, Fredrik Mo illustrates how TrendMiner aids in identifying bottlenecks, addressing equipment fouling, preventing distillation column trips, and comparing batch processes to ideal benchmarks. The platform’s intuitive interface allows for real-time monitoring, predictive insights, and actionable intelligence, leading to significant efficiency gains, cost reductions, and enhanced safety without the need for extensive data science expertise.
About the Speakers
“Making data actionable is what makes data valuable.”
“This is where TrendMiner can help. Our software avoids the time-consuming approach of building data models and delivering a black box solution. Instead, with self-service analytics we bridge the gap to the subject matter experts, giving them fast answers to their questions and actionable insights into their process data.”
