January 14, 2020

Customer success video: ArcelorMittal Ghent

ArcelorMittal’s rotating assets often operate under harsh conditions. A conveyor at the Ghent hot strip mill facility moves plates of sizzling hot steel along the production process. Under these circumstances, traditional, vibration-based predictive maintenance technologies fail due to high temperatures.

Hear from Carlos Alba (chief digital officer at ArcelorMittal) and Peter D'haese (chief digital officer at ArcelorMittal Flat Europe) on how SAM4 predictive maintenance enables the detection of developing asset faults from inside the motor control cabinet.

12 issues detected

"The first three incidents predicted by Semiotic Labs' SAM4 were not accepted by the maintenance team because they doubted the accuracy of the solution," says D'haese in the video. "Afterwards, those motors also came to failure. And once this conviction was there, every prediction of every failure was accepted by the maintenance team and they replaced the motors quite in advance. So in total, I think we detected 12 issues of which each was confirmed later by a failure in the motor."

To learn more about SAM4 predictive maintenance and how it could help your plant to reduce unplanned downtime, click here to book a demo.

May 10, 2019

Success story: Honeywell

SAM4 detects loose belt on a critical HVAC system

Honeywell installed SAM4 on a critical HVAC system at its facility in Delft, the Netherlands to detect upcoming failures at an early stage so that maintenance can be performed before breakdowns occur. Because the HVAC system was housed in a remote location, installing vibration sensors was impossible. Honeywell decided to use SAM4, Semiotic Labs’ online condition monitoring solution that analyzes electrical waveforms to detect machine failures. SAM4 installs its sensors inside the motor control cabinet and not on the asset in the field, enabling condition monitoring for assets operating in hard-to-reach places.

Implementation

SAM4's sensors and communication devices were installed inside the HVAC system's motor control cabinet. The SAM4 gateway then connected to the SAM4 platform over 4G. After 60 minutes, the system was up and running and started collecting data. After a training period of 3 weeks, SAM4 began providing insights into the HVAC system's condition, performance and energy consumption.

Results

After a few months of monitoring, SAM4 detected a loose belt and sent an alarm, triggering an inspection. SAM4's findings were substantiated, and Honeywell replaced the belt, preventing unplanned downtime.

Zooming in on the data

1. SAM4 generated an alarm for an increase in energy at the rotational frequency, which is often associated with a loose belt.
2. Upon inspection, a loose and dry belt was detected. In the absence of replacement parts, the belt was tightened, resulting in a reduction of scores for that specific failure mode.
3. After replacing the aging belt with a new one, scores leveled out at the pre-issue level.

April 12, 2019

Success story: Crown van Gelder

1,000-kilowatt motor, zero unplanned downtime

It takes a lot of work to turn wood into paper: from hydrapulping, where agitators mix waste paper and water to create recycled pulp, through bleaching, pressing, drying, and rolling, to cutting the result into sheets and stacking them for transport.

Paper manufacturer Crown van Gelder installed Semiotic Labs' AI-based SAM4 to monitor critical production assets. On 6 December 2018, that investment paid off—big time. Read more in our Crown van Gelder case study.

March 25, 2019

Newsletter March 2019

Dear reader,

One year ago, the first SAM4 units were installed in production environments. The implementation of 4th generation Smart Asset Monitor marked the launch of the 1st commercial version. SAM4 has monitored over 1.000.000 running hours of motors and detected 84% of failures in 2018 and 100% in 2019 (so far).

More about SAM4:
ArcelorMittal Use Case - SAM4 detects 100% of failures up to 4 months in advance.
Vopak monitors critical pumps (video)
Pump cavitation demo (video)

To see SAM4 in action, please join us on April 11th in Ahoy during Maintenance Next, where we will demo the integration with Salesforce’ Field Service Lightning. In short: SAM4 detects failures, FSL automatically generates work orders, permits, and scheduling services.

Over the next couple of months, several improvements to the dashboard will be implemented. We’ll focus on offering a more complete and concrete picture of the condition and performance of connected assets. In addition, we are working on a project that aims to provide in-depth energy savings potential based on the same data we use to monitor the condition of assets.

We’ll keep you posted!

Best regards,

The Semiotic Labs-team

March 19, 2019

Klant case: ArcelorMittal

Het doel

ArcelorMittal heeft al een aantal jaren een digitale focus, wat vooral de klanten ten goede komt. ArcelorMittal investeert geld en aandacht om voorop te blijven lopen in de digitalisering van de staalindustrie.

Investeringen in Smart Condition Monitoring oplossingen zijn gericht op het verbeteren van de Overall Equipment Effectiveness, het prioriteren van onderhoudstaken en het verbeteren van de duurzaamheid van productieprocessen.

De uitdaging

De roterende assets van ArcelorMittal werken vaak onder zware omstandigheden. Een transportband in de Gentse Hot Strip Mill-fabriek verplaatst platen van gloeiend heet staal langs het productieproces.

Onder deze omstandigheden falen traditionele, op trillingen gebaseerde sensortechnologieën door de hoge temperaturen.

Andy Roegis - ArcelorMittal

"Ons doel is om de betrouwbaarheid op een kosteneffectieve manier te verbeteren. In de staalindustrie werken assets vaak onder omstandigheden die niet geschikt zijn voor gevoelige sensortechnologieën. We waren op zoek naar een oplossing die een aanvulling kan vormen op trillingen-gebaseerde conditiebewakingssystemen om assets te monitoren die anders niet bereikbaar zijn. SAM4 installeert in de schakelkast, waardoor we in staat zijn om assets te monitoren die onder zware omstandigheden werken".

Oplossing

SAM4 is een plug & play conditie-monitoring oplossing die in de schakelkast wordt geïnstalleerd - en niet op de asset in het veld. Het bestaat uit sensoren, analyses en een online dashboard of API. SAM4 bewaakt de assets 24 uur per dag, 7 dagen per week.  De machine learning algoritmes zetten deze om in informatie over de gezondheidstoestand van de apparatuur. Het online dashboard biedt bruikbare informatie over de gezondheid, de prestaties en het energieverbruik van de aangesloten activa, zodat ArcelorMittal het onderhoud op het optimale tijdstip kan plannen.

Het proces

SAM4 werd geïnstalleerd op de motoren van ArcelorMittal's Hot Strip Mill. Na een leerperiode van 4 weken is SAM4 begonnen met de opvolging van mechanische en elektrische storingen.

SAM4 stuurt een alarm zodra er problemen worden gedetecteerd, zodat de onderhoudsteams van ArcelorMittal inspecties, reparaties of vervangingen kunnen uitvoeren voordat de stilstand optreedt.

Resultaten

SAM4 ontdekte 7 storingen in 12 maanden, soms tot 4 maanden van tevoren. Met vrijwel geen false-positives en geen gemist falen, was de Proof of Concept succesvol. Op basis van deze resultaten breidt ArcelorMittal zijn installed base uit.

Andy Roegis - ArcelorMittal

"De transportband op onze Hot Strip Mill is een cruciaal onderdeel van het productieproces. Omdat het onder zware omstandigheden werkt, is het vrijwel onmogelijk om handmatige bewakingstechnieken - of op trillingen gebaseerde systemen - toe te passen. SAM4 detecteert opkomende storingen door het analyseren van elektrische golfvormen vanuit de schakelkast. De informatie over gezondheid, prestaties en energieverbruik stelt ons in staat om data gestuurde beslissingen te nemen over de toewijzing van middelen. Bovenal biedt het inzicht dat nodig is om ongeplande stilstand te voorkomen".

download PDF: ArcelorMittal case
Product - Pricing - Demo

March 15, 2019

Success story: ArcelorMittal

Performance made of steel: SAM4 detects 100% of failures up to 4 months in advance

ArcelorMittal’s rotating assets often operate in harsh environments. A conveyor at the company’s hot strip mill in Ghent, Belgium moves plates of sizzling hot steel along the production process. In conditions like these, traditional proximity-based technologies like vibration and acoustic analysis fail: the sensors can’t handle the high temperatures. But SAM4's sensors that install in the motor control cabinet can—and they gave ArcelorMittal's plant precisely the insights they were looking for. Read more in our ArcelorMittal case study.