June 19, 2019 | Blog

SAM4 has a fresh new look

Condition-based maintenance, SAM4

After gathering your feedback, we have made some changes to the SAM4 dashboard that we think you’ll love.

Instantly actionable failure analysis

The new traffic light warning system gives you an instant heads up when something is going wrong. SAM4 will also give you an idea of what is causing the problem, and recommend next steps, meaning you can fix or replace your motor faster.

Real-time performance & trends over time

See the data you need as soon as you need it. Our real-time performance module will show you the metrics you need to see, while they are being recorded.

For the bigger picture, our Trends over Time module will also show you Running Time, Energy Consumption and Starts on any motor over time.

Understand what makes your motor tick

Want to see how Power Factor and Current are linked for a specific motor? We’ve got just the ticket. Our new dashboard helps you to understand the relationship between various motor metrics by comparing them all on one plot.

Curious to see if motor performance is decreasing over time? Our Performance Timeline will show you key metrics over a time period of your choosing.

Like the look of our dashboard?

If you are looking for a Condition Monitoring system that allows you to get the most out of your data, book a SAM4 demo with one of our consultants.

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 17, 2019 | Blog

Installing Sensors in the control cabinet: When does this add value?

SAM4, Sensor

 

 

A growing number of companies are moving toward condition-based maintenance (CBM) on assets such as motors and pumps.  This concept is based on the idea of matching maintenance to the state of the equipment, rather than time based preventive maintenance tasks.  When the maintenance manager has insight into the real-time condition of a machine, he can adjust his maintenance strategy optimally.

Sensors collect data, which is used to determine the condition of the assets. For example, velocity sensors or accelerometers measure vibration. For each application there are several commercially available sensor options - some more robust or accurate than others. One common drawback with sensors, however: they must be mounted on a machine to make measurements.

Alternatively, a new method to determine machine condition is by measuring a high frequency on the cables of motors or pumps. A deviation in the power supply can indicate a mechanical or electronic problem to the asset itself. For example, vibrations disrupt the electromagnetic field in an electric motor, which can be read in the data that generates the current. Every failure mode has a specific signature or fingerprint that can be measured in the current or voltage.

This alternate method of measurement still drives toward the goal of condition monitoring. A large difference with other “traditional” methods is where the measurement takes place. The current measurement does not have to be determined at the asset; it can take place in the control cabinet. Installing sensor modules in a control cabinet (rather than in the field) can provide many advantages.

Field Sensors Are Subject to External Factors

Sensors in the field are subject to local conditions. In the food sector, for example, strict hygiene and quality requirements apply. Rooms, surfaces and materials are cleaned often. The equipment and the sensors must be resistant to water or high humidity.

In other sectors, external factors such as extremely high or low temperatures, pressures, or contaminants may be present. This can lead to problems when sensors are not sufficiently robust.  A defective sensor does not provide reliable data. Sensor modules mounted in a control cabinet are in a stable, conditioned, dry room - ideal conditions for sensors to do their job.

Field Sensors Need Energy Sources

To collect and send information, sensors must be provided with an energy source. In the past, this was done via cables. However, laying cables is a time-consuming and expensive affair. In recent years, wireless sensors have gained a lot of ground. These sensors usually run on batteries. Depending on the type of sensor and the application, a battery will run out quickly or less quickly. Sending data once a day or every fifty milliseconds is a big difference. When batteries are drained, a mechanic will have to replace them – no battery, no data.

One solution for this problem is energy harvesting, a process in which energy (for example heat) is extracted from the immediate environment to supply the sensor with energy. However, this is currently not yet possible with all sensors or in all situations. With sensor modules placed in a control cabinet, the energy problem disappears. In a control cabinet, a sensor module can easily be connected to the mains.

Field Sensors Have Higher Installation Costs

A third advantage of sensor modules in a control cabinet is in installation. Motors or assets whose condition needs to be measured are often spread over a facility. In a baggage handling system, enormous distances exist between motors of a conveyor belt. Installation of sensors on each individual motor would take a lot of installation time.

Moreover, installing sensors at the right place in the asset is not always easy. Certain sensors must be located very closely to their source, while other sensors must be installed in places that are difficult to reach. Getting to motors integrated in larger machines, or submerged pumps can often prove problematic.

At some locations, there may be a flammable ATEX environment. Sensors here must meet certain ATEX or Classified flammability certifications. The installation of the sensors themselves in this environment also requires extra measures. Installing sensors in the field is therefore often difficult, cumbersome or expensive.

In the case of sensor modules in switch cabinets, the above issues do not play a role. The power supply of several assets comes together in one central location: the switch cabinet. If possible, this is always placed outside a potentially explosive area.  It must always be accessible or easily accessible. As a result, installation costs can be reduced.

Furthermore, preparations such as pulling cables can be done ahead of schedule, which means that installations only need be out of operation for a short period of time.

In practice

Some have already installed sensor modules in their control cabinets.  Two examples are Vopak Vlaardingen, a storage company; and Kaak Group, a manufacturer of machines for the bakery industry.

Vopak Vlaardingen

Marcel Kool, Maintenance Engineer at Vopak:

“Vopak Vlaardingen temporarily stores products from sea-going vessels in storage tanks. The product is then further distributed in trucks or lighter barges. About two hundred pumps take care of the loading at this location. For us it is important to monitor our equipment better so that we can increase service to our customers. We want to increase the predictability of maintenance.”

Vopak Vlaardingen chose not to install sensors on the pumps themselves, but centrally in a control cabinet.  Kool: “The pumps are not positioned far from each other, but they are insulated so you can't reach them directly if you want to install a sensor. ATEX was not an issue at our location, but it would be an extra factor to take into account at other locations.”

Installation & Baseline Determination

Vopak started a pilot program on ten pumps.  “The installation of the sensor modules in the control cabinet went quite smoothly. No special procedures were required, which resulted in a great deal of installation advantage. The installation of the modules was followed by a period in which the machine learning programmes were worked into and a baseline measurement was performed, a sort of starting position of the pump.

“Almost immediately after this phase, we received two indications based on the data. The dashboard indicated that the pump was almost failing. Mechanics examined these two pumps in the field and what the system indicated appeared to correspond with the findings in the field. This has increased the confidence in the system, which certainly offers perspective for the future.”

Justification for system extension to all 200 pumps may not make sense. “The pumps we selected for the pilot run regularly. We only use a small number of pumps on site sporadically. These pumps would take a little longer to learn, simply because they are used so little. If you let go of a business model on these pumps, the outcome may be that it is not sufficiently profitable to monitor them, whatever sensor technology you choose. For the majority of the pumps, condition monitoring is an option to consider.”

Kaak Group

Kaak Group has also chosen to install sensor modules in their control cabinet. Marcel Trapman is team leader at iBakeware, which builds software for monitoring and analysing the bakery line and the baking process:

“Our bakery lines that are with customers consist of a combination of a number of machines. There are critical, large motors in these lines that are built to customer specifications. If such an engine breaks down at a certain moment, this means that the line must be stopped, and a delivery may not be possible.  To avoid a long standstill, a spare motor must be stocked. This can be prevented by monitoring motors using sensors. If a discrepancy is found, an inspection can be carried out in time, spare parts can be ordered and maintenance can be scheduled.”

The bakery lines currently contain many different types of sensors and can be equipped with optional sensors at the customer's request. An example of such an optional sensor is that of Semiotic Labs.

“At a later stage we want to be able to give the customer the choice whether he wants to monitor the motors using data and sensors. For us, therefore, the possibility of retrofitting sensors in a fairly simple manner is of great importance. With the sensor module in the control cabinet, we do not need to reach the motor at all. We therefore see it as an added value for the customer to be able to retrofit it fairly easily. That's why we chose this type of system.”

Would you like to know whether sensors in the control cabinet also have added value for you? Check out our solution, follow us on LinkedIn or schedule an appointment with us.

 

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