Case study: Mueller moves from preventive to predictive maintenance

Figure 1: The system is easy to use, and the device itself is compact, mobile and requires very little training.

Mueller Industries is a global manufacturer and distributor of copper, brass, aluminum and plastic products. Headquartered in Memphis, Tennessee, the company provides wholesalers, retail distributors and original equipment manufacturers (OEM) around the world with offerings of flow-control and industrial products. Since its founding in 1917 as Mueller Metals, it has grown into a multi-billion-dollar publicly traded company. Mueller Industries has traditionally employed a preventive-maintenance approach in managing its equipment.

Recognizing the recent advances in and affordability of predictive maintenance (PdM), the company decided to implement a PdM program in one of its facilities on a trial basis. Anticipating positive results, we hope to gradually pursue wider implementation.

We based our initial decision to go with Augury on the quality of its products, most specifically its sensor technology. Augury combines Internet Age technologies and the gold-standard practices of predictive maintenance to extend the operational life of machine components, eliminate catastrophic equipment failures and reduce the costs of parts and labor. Augury’s diagnostic technology is built around a simple principle that every mechanical system can be characterized by the sound that it makes.

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Figure 2: The software is housed in a smartphone app, so no monitoring or transmitting equipment is necessary for analysis.

Using vibration and ultrasonic sensors to measure these sounds, the Augury platform can detect the slightest changes in machine performance and warn of developing malfunctions.

The Auguscope is a portable device that was developed by Augury to analyze machines “on the go.” The device, which caters primarily to field and on-site service technicians, directly plugs into a user’s smartphone. Used in tandem with an iPhone or Android device, the Auguscope’s special contact microphone allows technicians to convert analog vibration and ultrasound signals into digital signals. These readings are then uploaded to the cloud where Augury’s machine learning algorithms analyze the data against a library of signals to provide an immediate initial reading back to the technician.

The Auguscope incorporates more than three years of electronics and analog circuit development, resulting in analog signal sampling at rates of 120 kilo samples per second (ksps). Sampling at such a rate, as opposed to a lesser rate, allows Augury to determine with greater accuracy and specificity the exact type of malfunction present in rotating pieces of equipment.

It can record results from both vibration and ultrasonic sensors and be used for mechanical diagnostics, as well as leak detection, pump cavitation and steam traps. The result is a compact yet rugged, portable device.

The first benefit the facility experienced after implementing the Auguscope was the discovery of a hidden problem. Critical machines had bearings degenerating in the high-speed motion operations. The Auguscope was able to detect the problems, and the plant was able to plan the repair with minimal downtime.

The system is easy to use, and the device itself is compact, mobile and requires very little training. The software is housed in a smartphone app, so no monitoring or transmitting equipment is necessary for analysis. Augury also provides a high level of support, providing in-house training and webinars to ensure streamlined implementation.

Mueller utilizes overall equipment effectiveness (OEE) to measure productivity. In the most basic sense, the OEE metric provides a composite performance score for a piece of equipment. A plant OEE score proves high-level understanding of how well all equipment is performing. One of the key components to this score is machine downtime—the lower the downtime, the higher the OEE.

Figure 3: The facility has a good amount of automation, making it an ideal test site.

Because the Auguscope has the capability to predict failures before they happen, the facility can plan resources and materials in order to minimize that downtime while lowering repair part expedition cost. Subsequently, it also ensures the plant is better able to meet customer demands, stocking goals and total manufacturing cost targets. In a nutshell, if we can plan repairs to machines we can mitigate adverse impact to the business.

This particular facility has a good amount of automation, making it an ideal test site for the Auguscope. When the trial phase is completed in Q3 2017, a summary of results that pinpoint data pertaining to the system’s effectiveness will be presented to Mueller’s executive team. As the data collected will provide quantifiable impact of equipment and program on the business, Mueller will consider use of Augury in all facilities as a best practice.

Augury’s intent is to bring predictive-maintenance technology to new markets. Built on the idea that each machine has a unique acoustic fingerprint, Augury has developed technology that listens to the machine, analyzes the data and catches any malfunctions before they arise. The Augury solution can be applied in industrial factories. Augury is building the mechanical diagnostics platform for the Industrial Internet of Things.