Industrial tools and solutions’ Post

Achieving the right balance between an algorithm's false positive and false negative outcomes is crucial. Too many false positives result in wasted time, money, and resources, but a reduction in risk of data slipping through. Conversely, too few false positives may result in missing critical vibration anomalies leading to failure but may be more efficient. Defining thresholds and algorithm success parameters accurately is paramount for this balance. For further insights and details on this topic, please click through to our blog. https://bit.ly/44k6QVd

This tool is for anyone who wants a deeper understanding of pipeline integrity. Do not miss the chance to try it out. 🌟. #PipelineIntegrity #DataDrivenAssetIntegrity

WORD OF THE WEEK: Scheduled Maintenance Read the full definition and more at https://lnkd.in/gGBwcHsF

New Visualization Technique for ILI Data 📈 ✨ Introducing a new defect overlay mapping method I recently developed for highlighting pipeline susceptibility. More intuitive than a standard density plot. 📏 Overlays all defects found in ILI scans as arcs along the pipe's circumference ▶ Arc thickness corresponds to defect depth ▶ Stacking visualizes defect density around pipe's circumference This technique enables: 🔎 Clear identification of defect prone areas 📊 Better understanding of corrosion mechanisms 💡 More informed integrity management decisions Have you ever wanted to derive more insights from inline inspection data? 🤔 I believe approaches like this can unlock far more value. I'd welcome perspectives from: 👨💻 Data analytics professionals 🧑🔧 Pipeline integrity engineers 🛢️ Inline inspection specialists As well as any other industry professionals interested in advancing inline inspection data analytics. Please share your thoughts! Collaborating with industry leaders will help refine this visualization further. The goal is empowering pipeline owners through data analytics.

Predictive maintenance in 3 words

Are you performing #InspectionRounds? Capture the data in #RoundsLogging with #TANGOReliability. www.roundslogging.com Easily communicate condition changes.

Thank you UpKeep for this insightful article. Its high time maintenance and reliability professionals leveraged Data Analytics to optimize maintenance programs. It is cardinal to obtain management buy-in for data analytics to really work considering that most industries especially for the mining and metals industry where we have a good number of managers who have seen the evolution of maintenance over time [Reactive to Proactive and now maintenance 4.0 IOT] and are so adamant about doing things a certain way.......... Below is an extract of the conclusion of the article: CONCLUSION Incorporating data-driven strategies into maintenance operations can lead to significant improvements in efficiency, cost savings, and equipment reliability. By leveraging data analytics, predictive maintenance, and condition monitoring, organizations can transition from reactive to proactive maintenance approaches. This shift not only reduces downtime and unexpected costs but also enhances overall operational performance. As technology continues to advance, embracing data-driven maintenance will become increasingly vital for organizations aiming to remain competitive in their respective industries. #assetmanagement #miningandmetalsindustry

This book supports all activity around fluid analysis so managers can lay a more solid foundation for maintenance. It serves as a major contribution to both the science and art of fluid analysis, and is destined to become the cornerstone of every successful condition-based maintenance program. The examples and recommendations will have direct application to implement a true predictive maintenance program. More than 100 examples come from real-life cases, and reflect what many fleet managers encounter in their daily challenges. Go to: https://lnkd.in/gWE79MAP

This book supports all activity around fluid analysis so managers can lay a more solid foundation for maintenance. It serves as a major contribution to both the science and art of fluid analysis, and is destined to become the cornerstone of every successful condition-based maintenance program. The examples and recommendations will have direct application to implement a true predictive maintenance program. More than 100 examples come from real-life cases, and reflect what many fleet managers encounter in their daily challenges. Go to: https://lnkd.in/gWE79MAP

This book supports all activity around fluid analysis so managers can lay a more solid foundation for maintenance. It serves as a major contribution to both the science and art of fluid analysis, and is destined to become the cornerstone of every successful condition-based maintenance program. The examples and recommendations will have direct application to implement a true predictive maintenance program. More than 100 examples come from real-life cases, and reflect what many fleet managers encounter in their daily challenges. Go to: https://lnkd.in/gWE79MAP