The DNA of Machine Reliability™

Real-time Industrial IoT Sensors, Big Data Analytics and Physical Oil Analysis Provide Unparalleled Actionable Intelligence

Real-time condition-based machine lubricant monitoring can generate huge savings by helping mechanics instantly identify predictive maintenance requirements before catastrophic failures otherwise lead to plant shutdowns or costly repairs.

But to be effective and achieve maximum uptime, mechanics must tightly control the entire monitoring process — which can be comprised of both physical sampling and embedded sensors that perform real-time condition monitoring, for data integrity and reliability as well as comparative data analytic consistency.

In the case of physical oil sample testing, analytic data delivery speed goes hand-in-hand with a chain of custody that ensures samples are reliably taken, tracked, and analyzed with results uploaded to cloud servers — typically within 36 hours or less — reporting actionable intelligence.

LogiLube SmartLab™ Solution Offers Two Sampling Options

The LogiLube SmartLab™ oil sample analysis solution, a best-in class technology, offers two options for oil sampling: manual and autonomous.

MANUAL sample collection.

Mechanics can draw samples manually from machinery lubrication lines at any time and swiftly analyze them in the LogiLube SmartLab™ to identify potential degradation of critical oil properties such as viscosity, temperature sensitivity, or the presence and volume of water, and other impurities.

Manual sample collection is a simple but carefully prescribed process. Human induced errors such as inaccurate or incomplete data entry and untimely handling of the physical samples can render the sample invalid. Clearly, however, the implications for continuity of operations and accuracy of the related machine/oil sample data can be profound. The data analytics identify remaining-useful-life (RUL) and generate performance-related color codes based on a standard green-yellow-red system of alerts.

AUTONOMOUS sample collection.

For process-critical machines or, indeed, more sophisticated monitoring across entire systems, autonomous sampling via machine-time-based scheduling can become a more powerful part of the maintenance process.

With autonomous sampling, SmartOil™ equipment physically attached to the machine collects physical oil samples every 168 hours (weekly) of machine operation. The sampling bottle is contained within the SmartOil™ unit, a leading-edge Industrial Internet of Things (IoT) device, and dispatches a mechanic to retrieve the sample bottle for prompt shipment to LogiLube's state-of-the-art strategic partner oil analysis lab.

The SmartOil™ real-time condition monitoring system continuously monitors the quality of the oil flowing past embedded sensors. Sub-second sensor data is "edge processed", applying dozens of proprietary algorithms to determine the health of the system while simultaneously looking for "dangerous conditions" that could lead to an unplanned shutdown event. Scheduled physical sampling enables mechanics and supervisors to gather analytic data, perform historic trend analyses and corroborate the real-time data in order to generate highly intuitive predictive analytics.

SmartLab™ oil sample testing employs a chain-of-custody that ensures samples are reliably taken, tracked, and analyzed with results uploaded to cloud servers — typically within 24 hours or less — reporting actionable intelligence.

Manual intervention is still possible via a Sample-By-Exception™ process when the internal SmartOil™ embedded sensors and proprietary edge-processed algorithms detect a variation of oil condition outside prescribed thresholds.

Autonomous oil sample collection naturally offers a number of distinct advantages over the manual process. For example, it eliminates human error risk, delivers certainty that a sample has been taken, and gives managers and supervisors the consistency reassurance in the process. Machine-to-lab accountability can be assured in order to provide the best chances for protection of valuable mission-critical assets.

Whether manual or autonomous, each step of the chain-of-custody must be meticulously controlled to achieve comparison consistency over time and reduce human error risk. LogiLube’s SmartLab™ chain-of-custody process provides a best-in-class process that ensures scientifically accurate and fully traceable physical oil sample analysis.

10-step end-to-end SmartLab™ process

The physical oil sample collected for lab analysis passes through a 10-step process within that less-than-36-hour window.

Step 1

In the manual process, the mechanic or field agent receives a notification or request for the sample to be drawn and collects the sample. In the autonomous process, an alert is generated indicating when the bottle is full and ready for retrieval.

Step 2

The mechanic draws oil and fills the sample bottle in the manual process while, in the autonomous process, the bottle is automatically filled; the mechanic replaces the bottle with a new, empty one.

Step 3

A unique QR code on the asset identifies the machine. In the autonomous process, the QR code is affixed to the machine-mounted SmartOil™ unit. In both processes, the field worker uses a handheld mobile device running a SmartLab™ app to scan the QR code along with a barcode on the removed bottle, ensuring the sample and its location are irrevocably linked and stored on a cloud-based server.

Step 4

This action generates a time-stamped tracking report (SmartLab™ Notification), which the mechanic (and/or supervisor) can read on a web-enabled computer or smart device, indicating the bottle has been retrieved.

Step 5

The mechanic then ships the sample by overnight delivery service to the LogiLube SmartLab™ analysis laboratory.

Step 6

SmartLab™ analysts scan the bottle barcode and generate a tracking report showing that it has been received. They can transmit the report via email, text, or other messaging technologies confirming the physical sample has safely arrived at the lab and is in-process.

Step 7

Sophisticated lab equipment is used to automatically analyze the sample according to ASTM and ISO parameters for abnormalities in terms of viscosity, base number, acid number, water/glycol content, elemental and additive contamination, particle counts, and other impurities.

Step 8

The analysis results undergo a human tribology analyst review in addition to Big Data analytics with the application of expert-system based artificial intelligence and machine learning algorithms. Data-driven ‘actionable information’ is auto-generated and shared via alert/notifications (SMS, email) and lab analysis report (PDF).

Step 9

The analysts provide additional insight and comments and upload the timestamped information to remote, cloud-based data servers where it is converted to actionable information, which is accessible to any authorized user via web-enabled PC or smart device. They also issue a cloud data availability notification alert.

Step 10

The client receives the actionable intelligence and implements the relevant data-driven decisions for proactive maintenance to rectify identified issues.

Establishing a precisely defined and time-controlled chain-of-custody ensures that the physical oil sampling process fulfills the critical predictive maintenance role, avoiding catastrophic failure consequences and thereby enhancing both client reputation and financial performance.

Tell us how we can help you protect your assets with our industry-leading SmartLab™ solution. Contact LogiLube today.


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