30 day corrosion rates
Operating below minimum thickness
30 day corrosion rate
3
7
TML ID
corrosion rate (mpy)
08-CAC-1693-10> 1.8
0.2933
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View all
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
0.2933
60 day corrosion rate
90 day corrosion rate
1
18
08-CAC-1693-10> 1.8
0.2933
View all
View all
View all
60 day corrosion rate
90 day corrosion rate
Lowest remaining life
TML ID
corrosion rate (mpy)
TML ID
Year
TML ID
corrosion rate (mpy)
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
500
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
500
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
500
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
500
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
0.2933
08-CAC-1693-10> 1.8
500
08-CAC-1693-10> 1.8
0.2933
View all
View all
View all
Figure 7 Simplified status dashboard highlighting critical assets
from mCluez enabled informed decision-making, allowing for timely adjustments and a reassessment of equipment longevity. Raising the temperature effectively mitigated the heightened corrosion rate, stabilising the asset’s condition and improving overall safety. The implementation of mCluez with AIoT technology transformed corrosion management for the facility. By providing accurate, real-time data and facilitating quick responses to environmental changes, AIoT technology sig- nificantly enhanced monitoring accuracy and operational decision-making. This case study highlights the transform- ative impact of integrating advanced technologies to opti- mise asset management and ensure long-term reliability. Using AIoT Corrosion poses significant safety risks in the refining and petrochemical industry. Traditional manual ultrasonic thickness monitoring is fraught with errors and inefficien - cies, and even permanently installed sensors struggle with accuracy due to surface irregularities and material velocity limitations. The proven approach of AIoT technology has funda- mentally transformed corrosion monitoring. By combin- ing artificial intelligence with IoT sensors, AIoT enhances measurement precision, dynamically adjusts parameters, and delivers real-time analysis. AI algorithms significantly improve data quality by addressing variations in temper- ature and stress, ensuring more reliable results. Modern AIoT-powered dashboards offer a clear, real-time view
of asset health, enabling rapid focus on critical areas and informed decision-making. These innovations dramatically improve accuracy and efficiency, revolutionising corrosion management practices across industries.
mCluez is a trademark of mPACT2WO, a Molex Business.
References 1 www.ampp.org/technical-research/what-is-corrosion/corrosion- reference-library/oil-gas 2 Schieke S, Geisenhoff M, Ultrasonic Corrosion Monitoring – It’s time for a Paradigm Shift , presented at the API Inspection Summit 2022. 3 Schieke S, Geisenhoff M, Ultrasonic Corrosion Monitoring – Real World Examples , API Inspection Summit, 2024. 4 Schieke S, Geisenhoff M, Ultrasonic Corrosion Monitoring – It’s time for a Paradigm Shift, Inspectioneering Blog, 2021. Venkat Eswara is Senior Director in Product Management at mPACT2WO, a Molex Business. He leads a pioneering Solution as a Service portfolio for process industries, integrating AIoT, operation- al-aware analytics, and automation. His role encompasses portfolio strategy, roadmaps, go-to-market strategies, P&L management, and strategic partnerships, He holds a Masters in management from Northwestern University. Sascha Schieke is Director of Corrosion Monitoring Solutions at mPACT2WO, a Molex Business, where he oversees research and development, hardware/firmware engineering, application engineer - ing, manufacturing, and field services. He holds a Masters in geophys - ics and a PhD in engineering and currently owns 10+ patents and patent applications as lead and co-inventor.
105
PTQ Q4 2024
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