May 10, 2019 | Client cases

Success Story: Honeywell

Condition-based maintenance, Installation, Internet of Things, SAM4

SAM4 detects belt looseness on a critical HVAC system

Honeywell in Delft installed SAM4 on a critical HVAC-system to detect upcoming failures at an early stage so that maintenance is performed before breakdowns occur. Because the HVAC-system was installed in a remote location, installing vibration sensors was impossible. Honeywell decided to implement SAM4, Semiotic Labs’ online condition monitoring solution that analyses electrical waveforms to detect failures. SAM4 installs 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 installs sensors and communication devices inside the motor control cabinet. The system is connected to the SAM4-platform via 4G. After 60 minutes, the system was up-and-running and started collecting data. After a training period of 3 weeks, SAM4 provided insights into the condition, performance, and energy consumption.
Results SAM4 detected a loose belt and sent an alarm - triggering an inspection. The findings of SAM4 were substantiated: Honeywell replaced the belt, thus preventing unplanned downtime.  

The data After a couple of months of monitoring, the system:
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 lieu of replacement parts, it was tightened, resulting in a reduction of scores for that specific failure mode.
3. After replacing the ageing belt with a new one, scores levelled out at the pre-issue level

April 12, 2019 | Client casesUncategorized

1.000 kilowatt motor, zero unplanned downtime

SAM4

Facta and Semiotic Labs collaborate to eliminate unplanned downtime
for Crown Van Gelder

Collaboration Monitoring & Service

Facta Aandrijftechniek and Semiotic Labs work together to ensure a higher availability of production resources. SAM4, the smart sensor of Semiotic Labs, monitors critical assets from the control cabinet and signals approaching failures up to 4 months before production resources fail. Facta Aandrijftechniek monitors the alarms and carries out inspections, repairs or replacements.

Full-Service

Cees Slegt, Facta: "We relieve our customers of their worries by taking over the maintenance of engines and assets. This enables us to achieve higher availability of production resources at lower costs. We do this by doing risk analysis and drawing up a maintenance plan based on these. In combination with condition monitoring from Semiotic Labs, we can optimize maintenance intervals and prevent unplanned downtime."

In practice

Semiotic Labs' SAM4, monitors critical assets for Crown Van Gelder. On 6th December 2018, SAM4 reported electrical damage to a 1,000-kilowatt motor. Because the replacement of the motor involves considerable downtime, it was decided to closely monitor the development of the condition to determine whether it is possible to keep the motor operational until the next maintenance stop.

Result

The scheduled maintenance stop was met, and the engine was replaced during the regular maintenance stop. Because the engine was not on the list for inspection, unplanned downtime was avoided.

Andre Prent - manager maintenance (PM2) Crown Van Gelder

"Our customers count on us to deliver consistent quality, on time. That's why we at Crown Van Gelder continuously invest in upgrading our facilities to continue to improve service, performance and, competitiveness. Our investment in the innovative way of monitoring by Facta and Semiotic Labs is one example. This is now paying off because the alarm and service have prevented a major standstill and have not compromised the security of supply".

March 25, 2019 | Client casesVideo

Newsletter March 2019

Maintenance, Pump, SAM4

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 25, 2019 | Client cases

Vopak monitors pumps using SAM4 (video)

Pump, SAM4

March 21, 2019 | Client cases

TRENDnet Application Spotlight

SAM4

DOWNLOAD

March 19, 2019 | Client cases

Klant case: ArcelorMittal

Installation, Reliability

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 | Client cases

SAM4 detects 100% of failures up to 4 months in advance

Condition-based maintenance

Case Study ArcelorMittal

The goal

ArcelorMittal has had a digital focus for a number of years, benefiting customers in particular. ArcelorMittal is making major investments, not only in terms of resources but also in time and in management attention, to remain at the forefront of digitalisation in the steel industry.
Investments in Smart Condition Monitoring solutions are aimed at improving Overall Equipment Effectiveness, prioritising maintenance tasks and improving the sustainability of production processes.

The challenge

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

Andy Roegis - ArcelorMittal

“Our goal is to improve reliability in a cost-effective manner. In the steel industry, assets frequently operate in conditions that are not hospitable to sensitive sensor technologies. We were looking for a solution that could complement vibration-based condition monitoring systems to monitor assets that can otherwise not reachable. SAM4 installs inside the Motor Control Cabinet, enabling us to monitor assets operating under harsh conditions”.

Solution

SAM4 is a plug & play condition monitoring solution that installs inside the Motor Control Cabinet - and not on the asset in the field. It consists of sensors, analytics, and an online dashboard or API. SAM4 monitors data 24/7 and turns data into information about the health-status of equipment. The online dashboard offers actionable information about the health, performance and energy consumption of connected assets - allowing ArcelorMittal to schedule maintenance at the optimal time.

The Process

SAM4 was installed on motors at ArcelorMittal’s Hot Strip Mill. After a learning period of 4 weeks, SAM4 started to monitor for mechanical and electrical failures.
SAM4 sends an alarm as soon as issues are detected, so that ArcelorMittal’s maintenance teams can perform inspections, repairs or replacements before downtime happens.

Results

SAM4 detected 7 failures in 12 months, sometimes up to 4 months in advance. With virtually no false positives and no missed failures, the Proof of Concept was successful. ArcelorMittal expands its installed base based on these results.

Andy Roegis - ArcelorMittal

“The conveyor on our Hot Strip Mill is a critical part of the production process. Because it operates in harsh conditions, it is virtually impossible to apply manual monitoring techniques - or vibration-based systems. SAM4 detects upcoming failures by analysing electrical waveforms from inside the Motor Control Cabinet. The information about health, performance and energy consumption allows us to make data-driven decisions about resource allocation. Above all, it provides insights needed to prevent unplanned downtime”.

download PDF: ArcelorMittal case
ProductPricing - Demo