Machine Fault Indication: Reduce Downtime and Improve Operational Efficiency

Welcome to TWTG's Newsletter on LinkedIn!?

We're excited to present to you the LinkedIn edition of our bi-monthly newsletter, now in its third edition!?

Previously available exclusively via email, we're expanding our reach to LinkedIn to bring you even more insights, updates, and industry news directly to your feed. This newsletter is your go-to source for staying informed about the latest developments in IoT, use cases for your industry, and innovative solutions at TWTG.

Each edition is carefully curated to provide you with valuable content. Be sure to follow us on LinkedIn and keep an eye out for our bi-monthly updates. We look forward to sharing insights and inspiring discussions with you!

NEON’s Machine Fault Indication

In a modern industrial plant, the reliability and performance of every piece of machinery are crucial in avoiding unscheduled, costly downtime. Modern Technologies such as Active Machine Fault Indication (ActiveMFI) are leading the way in keeping facilities operational. Traditional systems require data from thousands of sensors to be processed centrally, with engineers manually analyzing frequency data to detect anomalies. ActiveMFI revolutionizes this process by enabling each NEON sensor to perform its own analytics using machine learning, determining its breach limits and historical data independently. This allows the device to predict faults and issue alerts autonomously, significantly reducing the need for centralized data processing while still supporting comprehensive analysis.

Key features of ActiveMFI include advanced vibration analysis, bearing fault detection, rotor unbalance, bent shaft detection, and identification of misalignment, mechanical looseness, and resonance conditions. These capabilities allow the NEON sensors to detect a wide range of machine-learned faults, providing detailed insights into machine health through harmonic frequency and amplitude measurements, and advanced algorithms for statistical analysis. This comprehensive data analysis enables ActiveMFI to diagnose faults and recommend corrective actions automatically, simplifying maintenance decisions and reducing the need for extensive technical knowledge.

ActiveMFI is especially transformative for remote facilities, where it can bring state-of-the-art monitoring capabilities without requiring complex installations. Sensors equipped with ActiveMFI can immediately alert local engineers to operational changes, allowing for swift action and minimizing downtime and maintenance costs. This technology is available as firmware for new NEON Vibration Sensors and as an upgrade for existing devices, ensuring that even current installations can benefit from this innovative solution. This ability to provide precise, real-time fault detection and analysis makes ActiveMFI a crucial and revolutionary tool in the field of industrial maintenance.

Read the full use case here: NEON's Machine Fault Indication

Quantifiable I-IoT Benefits?

As energy companies gather increasing amounts of data from numerous measuring points and devices, Calculating the incremental gains of digitization becomes crucial for building business cases to justify investments in new technologies. Understanding the historical data of processes being digitized—such as failure rates, inspection frequencies, and equipment lifespans—helps estimate cost savings and efficiency improvements from implementing digital alternatives like real-time alerts or predictive maintenance. For instance, I-IoT can enhance system efficiency by up to 40% and reduce downtime by 25%, according to the Journal of Sensor and Actuator Networks.

Specific examples include vibration sensors that can decrease machinery failures by up to 30% and extend equipment lifespans by up to 40%, and temperature transmitters that can increase process efficiency by 35% and reduce safety-related incidents, according to the International Society of Automation. These improvements can be calculated by analyzing historical data, such as failure rates and inspection frequencies, to estimate cost savings and efficiency gains.

A practical use case involves steam trap monitoring using NEON Temperature Transmitters. These devices can detect blockages and leaks by measuring temperature differences upstream and downstream of a steam trap. For a facility with 100 steam traps and $5,000 per trap, a conservative estimate of a 15% failure rate could result in annual losses of $75,000 due to steam loss and maintenance costs. The cost of the monitoring solution is comparable to the annual loss, offering a return on investment within a year. Effective steam trap monitoring could save up to 20% of a facility’s annual energy bill, demonstrating the feasibility of assigning value to specific use cases and highlighting significant energy savings.

Read more about: Quantifiable Benefits of Using I-IoT

Industry Talk

In our newsletter, we like to highlight interesting and important pieces from other industry experts. We make a selection of the current industry news to provide you, our subscribers, with fresh insights.

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