International Maintenance Conference: The Speed of Reliability

International Maintenance Conference 2025: The Speed of Reliability

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asset condition management

The Use of Drone Technology for Remote Oil Sampling

The Use of Drone Technology for Remote Oil Sampling

TRC-2018 Learning Zone 51:38
by Michael Holloway, ALS Global

Oil analysis sampling can be difficult if not impossible in certain environments due to location.The use of unmanned aerial vehicles have increased exponentially due to advances in materials, aeronautics, and systems for commercial applications.Drones can accomplish tasks that would be difficult if not impossible for people.The combination of oil sampling and unmanned aerial vehicles is a perfect match in certain situations.Only recently has the concept become viable due to a combination of an aerial sampling boom with magnetic sample ports, evacuated vacuumed sample bottles with a servo activated sample valve, and a ducted fan unmanned aerial vehicle technology.This system provides ease of sampling in remote and difficult to reach access points to various assets such as wind turbines where normally it would be expensive if not prohibitive for typical sampling protocols to occur. This paper explores the development and application of such a system.The presentation will also have a video example of a case study of this application.

C&W Services Turns to Wireless Predictive Maintenance to Maximize Asset Reliability

C&W Services Turns to Wireless Predictive Maintenance to Maximize Asset Reliability

TRC-2018 Learning Zone 46:50
by David Auton, C&W Services and Abhinav Khushraj, Petasense

After a successful pilot, C&W Services implemented a machine-learning based predictive maintenance system in order to address the limitations of a manual walk around program at one of its leading pharmaceutical client facility. Over the past year, by leveraging wireless sensors, secure cloud infrastructure and predictive analytics, C&W Services has been able to automate data collection, improve asset reliability, reduce equipment downtime, dramatically cut down on maintenance spending and achieve better resource allocation. Soon after deployment, the IIoT solution enabled the reliability engineers at C&W Services to detect a defect in an AHU, thereby preventing a catastrophic failure. The asset in question displayed an increase in the amplitude of fan shaft harmonics. Upon investigation, it was verified that the belts were running loose and the shafts were out of alignment. In another instance, the pillow block bearings were extremely noisy on the fan. There was a step increase in the acceleration spectrum, relatively small but noticeable that was returned to its normal vibration signature upon lubrication. With the continuous monitoring of critical rotating machinery, C&W Services has been able to achieve a competitive edge through a strong ROI along with other tangible benefits. Today it is inspiring others in the industrial world to make a transition towards IIoT.

Creating a Business Case for Continuous Monitoring Using Reliability Science

Creating a Business Case for Continuous Monitoring Using Reliability Science

TRC-2018 Learning Zone 20:46
by John Langskov, Palo Verde, Arizona Public Service

On-line monitoring can provide significant cost savings through improved reliability (such as production line shutdown avoidance), but additional savings can also be obtained through reduced PM tasks. The question is: do the savings in PM reduction balance the cost of adding continuous monitoring to sensors to your equipment? Palo Verde uses a parameter-based approach, that focuses on degradation mechanisms affecting a specific component type, and a sensors ability to monitor them continuously for degradation, periodic PM tasks can be eliminated, or extended based on changes in failure probability.

Basic Vibration Analysis, Case Histories

Basic Vibration Analysis, Case Histories

TRC-2018 Learning Zone 41:41
by Robert Jones, Vibrometrics

Reliability-centered maintenance depends on accurate information about the condition of the machinery. Vibration analysis is one method of obtaining that information. Our primary concern is the condition of the bearings. If the bearings are in good condition, even if the machine is out of balance, misaligned, or loose it still operates until these conditions can be corrected. But if the bearings are faulty, disaster can be just around the corner. By the use of vibration spectrums and time domain spectrums collected by the author, under operating plant conditions, it will be demonstrated how the necessary data can be analyzed to determine the condition of the machine bearings. With operational speeds that will vary from 8 RPM to 3600 RPM, other machine fault conditions and solutions will be presented. Someone once said that if we had perfect information we could all make perfect decisions. Vibration analysis may not provide perfect information but the information provided will enable the user to make better decisions during the operation of plant equipment.

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Condition Monitoring and AI are Driving Change in the Energy Industry

Condition Monitoring and AI are Driving Change in the Energy Industry

TRC-2018 Learning Zone 40:27
by Stuart Gillen, SparkCognition

Many organizations today are facing challenges in increasing reliability and uptime. Current industry solutions do not offer advanced notice for performing proactive, predictive maintenance. The use of intelligent edge devices to acquire asset sensory data, along with machine learning algorithms to predict when an asset will fail, is becoming more attractive to maintenance managers as they seek new methods to get maintenance costs under control. The use of this technology can augment or even supplement human subject matter experts while providing significant advanced notice of asset health issues by analyzing and learning from past asset health data. In this presentation, we will discuss practical ways in which utilities can get started today and see how others are implementing this technology.

How Weyerhaeuser Is Building a Foundation for Precision Lubrication

How Weyerhaeuser Is Building a Foundation for Precision Lubrication

TRC-2018 Learning Zone 35:43
by Mark Barnes, Des-Case and Keith Staton, Weyerhaeuser

Weyerhaeuser knows a thing or two about building houses. From dimensional lumber to engineered wood products, plywood to OSB, Weyerhaeuser’s product are used wherever quality, durability, and value are required. But they also know how to build a solid foundation for reliability. In this session, we’ll talk about the basic components that any company needs to execute on precision lubrication and learn firsthand how Weyerhaeuser is building the elements of a best-in-class, sustainable lubrication program.

Some Practical Steps toward IoT, Connected Plant, Predictive Analytics and Improved Business Results

Some Practical Steps toward IoT, Connected Plant, Predictive Analytics and Improved Business Results

TRC-2018 Learning Zone 42:20
by Randy Jones, Southern Company Generation

Everyone wants to achieve a connected plant and to leverage IoT, APR, predictive analytics, and other enhancements to improve business results. This presentation will discuss some practical steps to be considered and some basic foundational elements that will enable moving forward along this journey.

Building the Offer: Finding the Value

Building the Offer: Finding the Value

TRC-2018 Learning Zone 41:32
by David Shannon, Parker-Hannifin

Digital transformation is a journey in a large established company. One of the journeys surrounds packaging up an offer and figuring out how to sell it. These include technical issues and capabilities needed to simply connect and collect data from your product, notwithstanding the many forces that can make this effort challenging and potentially derail innovative ideas. Using the development and launch of the Parker-Hannifin’s Voice of the Machine™ IoT platform as a case study, David Shannon shares how Parker adopted a common set of standards and best practices for new business models and pricing across all its operating groups and technologies.

How We Used Machine Learning to Predict Engine Failures

How We Used Machine Learning to Predict Engine Failures

TRC-2018 Learning Zone 23:47
by Robert Kalwarowsky, Fluidlife

Are machine learning and artificial intelligence all hype? Find out how we used machine learning to predict engine failures using oil analysis results. Learn what mistakes we made, what we learned and how to use predictive analytics on your own equipment. We will speak about the basics of machine learning, how to apply it to your own equipment and offer tips and tricks based on our experience. Don’t miss failures and let the computers work for you.

Digitalization of Vibration-Based Condition Monitoring

Digitalization of Vibration-Based Condition Monitoring

TRC-2018 Learning Zone 44:26
by Dries Van Loon and Alain Naets, PRUFTECHNIK

Condition monitoring with non-destructive vibration analysis is experiencing an accelerated development due to several factors that work as a catalyst. Industrial and marine installations are increasingly interconnected by industry standard TCP/IP based networks. Transmission of wireless data is becoming cheaper and much faster. Digital storage of large data volumes is not a costly hurdle any longer and engineers and technicians are used to working with intuitive and mobile tablets and smartphones that virtually connect them via apps to their plants, their homes, and even their own health parameters. New techniques such as data mining and analytics have emerged. They enable us to quickly plow through enormous amounts of data and extract patterns and relations that were thus far hidden from sight. In this presentation, we are exploring how these new technologies will empower technicians and engineers to efficiently and accurately predict and analyze wear and damages in rotating equipment and how these new technologies are boosting the effectiveness of the vibration analyst. The result is an accrued efficiency of industrial production units, marine vessels, and offshore units, rendering them safer, less polluting and more profitable.

Optimizing Condition-Based Maintenance for Industrial Efficiency

Optimizing Condition-Based Maintenance for Industrial Efficiency

TRC-2018 Learning Zone 33:38
by Dave McCarthy, Bsquare

Traditional methods of equipment maintenance are often reactive – servicing equipment once it fails – or based on time intervals or hours of use. Reactive maintenance can represent expensive unplanned downtime and non-routine servicing that may be more costly. Time-based servicing may under- or over-service equipment, which can inflate maintenance costs and reduce asset longevity. This presentation will highlight how tailored maintenance schedules help eliminate over or under servicing to reduce downtime, improve asset longevity and the overall reliability of industrial assets.

Introduction to Critical Asset Surveillance Technologies

Introduction to Critical Asset Surveillance Technologies

TRC-2018 Learning Zone 45:40
by Rudy Wodrich, IRISS

Online Monitoring and the use of IoT devices to facilitate easier data collection and collation can also be referred to as Critical Asset Surveillance Technologies (CAST). Traditional online monitoring techniques including Power Quality and Partial Discharge (PD) monitoring will be briefly examined. For industrial and commercial buildings, temperature monitoring may hold the most promise as a surveillance technique to catch problems early in the P-F curve. There are many options to consider when considering the implementation of online temperature monitoring. Keep in mind that the goal of temperature monitoring is to DETECT a potential, ANALYZE the data and determine criticality of further investigation, INSPECT the equipment in question to pinpoint the problem and finally to REPAIR the problem. With this in mind, we will weigh the technology options to be considered when choosing a temperature monitoring solution including:

  • Contact (point based) or non-contact (area based) monitoring
  • Wired or Wireless Communication
  • Wired or Battery Powered
  • CLOUD based or Firewalled Data
  • Data Collection Frequency
  • Stand-alone or part of Building Management System (BMS) or SCADA Platform
  • Alarm Communication Methodology
  • Reporting features / Data Bridging
Create 3D Models of Your Assets to Work in a Visual Maintenance Environment

Create 3D Models of Your Assets to Work in a Visual Maintenance Environment

TRC-2018 Learning Zone 41:11
by Scotty McLean, Bentley Systems

Today, maintenance professionals can work in a realistic 3D visualization environment, set up quickly with reality modeling software to create 3D models of your assets from photographs you take of your assets. Wouldn’t your job of maintenance be easier if you could see the assets in 3D to plan and understand the context within which the asset was designed, built, and operated? Now you can work in an immersive 3D environment for asset inspections and health monitoring, reliability and maintenance planning as well as work execution. Other benefits include simplifying training for young maintenance professionals and simplified and more understandable standard procedures. Attend this session and see how much better it will be when you can pinpoint locations and understand the geo-coordinates of the asset and know specifically where you need to inspect and/ or address an issue.

How Machine Learning Is Revolutionizing Asset Reliability and Predictive Maintenance Practices

How Machine Learning Is Revolutionizing Asset Reliability and Predictive Maintenance Practices

TRC-2018 Learning Zone 41:12
by Aaron Beazley, Bentley Systems

While machine learning has been researched for decades, its use in applying artificial intelligence in industrial plants and infrastructure asset operations is now advancing exponentially. This is due to the growth in big data and the expansion of the Internet of Things (IoT); the ability to provide the processing power needed to analyze larger data sets, and the need for superior predictive and prescriptive capabilities required to manage today’s complex assets as well as the availability of machine learning methods. While machine learning has typically been linked with industries such as transportation and banking (think self-driving cars and fraud monitoring respectively), there are many uses for machine learning within the industrial sector. This presentation will focus on some of the principles within machine learning, and how four such industries that are primed to take advantage of the application of machine learning can maximize the benefits it brings to improve situational intelligence, performance, and reliability.

VFDs Play the Flute: How to Prevent the Phenomena

VFDs Play the Flute: How to Prevent the Phenomena

TRC-2018 Learning Zones 21:35
by Glenn Eyle and Ken Bates, EMCOR Government Services

The drive to go green and consume less energy has, especially in facilities operation, has increased the regularity of variable frequency drive (VFD) installation to new and existing mechanical systems. The drive’s capability to adjust the speed of a motor on a mechanical reduces power consumption. By making VFDs more accessible and field serviceable, they have become a nearly standard, go-to choice for an assured return-on-investment in facilities energy conservation projects. It is important to know the harm the VFD can cause, how to diagnose it, and how to mitigate the damage it generates. The cost-saving, energy reducing benefits of VFDs come with one significant adverse effect on the induction motor’s roller element bearing: fluting! This paper seeks to describe the fluting phenomena, the grooving damage created by the VFD, and the technology that has been developed to address it. There is no way to determine when this fluting will occur, but it absolutely will occur. At NASA’s Jet Propulsion Laboratory, we have a robust PT&I program that actually measured and recorded fluting after VFDs were installed on the facility before it even had a name. Our Vibration Analyst learned of fluting, and how to mitigate it, by installing a shaft grounding protection ring, from a Vibration Institute Conference in 2012. However, even after installing the protection ring on motors, we have continued to detect bearing failures. This failure led us to research available technology to validate the operation of the shaft grounding protection ring before and after installation. After researching viable ESD measuring devices, we selected the Electrostatic Discharge Pen. Based on documented PT&I finds here at JPL, this paper will make the case that this pen is an affordable, rapidly responsive solution to discerning the arcing that occurs before its damage is done to the motor bearings. 

Predictive Analytics and Remote Monitoring of Mobile Assets

Predictive Analytics and Remote Monitoring of Mobile Assets

IMC-2017 Learning Session (41 Minutes)
by Jason Mann, Wi-Tronix LLC

Today’s high value mobile assets such as locomotives and work boats are constantly generating large amounts of data. Wi-Nostix interprets and analyzes this data along with inserting a human element. The Wi-Nostix Service bridges the gap from Big Data to provide actionable mobile asset specific repair and troubleshooting recommendations. The mission of the Wi-Nostix Service is to provide best in class proactive prognostic asset monitoring services and repair recommendations for multiple OEM providers of engines, locomotives and marine equipment using the latest developments in statistical modeling algorithms and technician experience. We design our applications to meet the specific needs of our customers.

 Next Generation FluidScan Portable Oil Analyzer

Next Generation FluidScan Portable Oil Analyzer

CHELMSFORD, Mass.--(BUSINESS WIRE)--Spectro Scientific, one of the world’s largest suppliers of oil, fuel, and processed-water analysis instrumentation and software, has released a new generation of its field-proven FluidScan® mid-infrared spectrometer handheld oil analyzer.

Project Maintenance Management Plan (PMMP)

Project Maintenance Management Plan (PMMP)

IMC-2017 Learning Session 41:11
by James Sadler, HQ, U.S. Army Corps of Engineers.

The U.S. Army Corps of Engineers (USACE) Civil Works oversees and administers an asset portfolio with more than $250 billion in capital investments and over 1,500 operating projects located in all 50 states, as well as several international river basins. The portfolio continues to deliver daily benefits to almost every U.S. household that range from clean hydro-electric power and low-emission transport to recreational opportunities and flood mitigation. Reliable performance of the nation’s investment in infrastructure is essential to the asset portfolio’s ability to deliver safe and dependable service. The cornerstone of reliability is a maintenance management strategy developed to meet the organizational performance objectives.

The Project Management Maintenance Plan (PMMP) is an integral part of the USACE Maintenance Management Improvement Plan (MMIP). The PMMP identifies assets at each civil works project, establishes maintenance activities for those assets, then determines what maintenance activities are required as either a cost of ownership, to minimally operate the asset, or fully maintain the asset in compliance with suggested manufacturer’s schedules or established practices. The costs of the maintenance activities are estimated within the above categories to optimize strategic execution of limited Federal budgets. The PMMP:

  • is a site specific written maintenance management plan that completely summarizes the project’s maintenance needs.
  • compiles the annual cost of maintenance for each asset by frequency, and allows maintenance managers to regularly update assets to gauge required maintenance.
  • also identifies the desired relationship between maintenance investments and asset performance and totals the predicted investment need based on the project’s portfolio.
  • provides managers with a means to document and communicate maintenance decisions under circumstances of less than full funding.
 Leak detection in the age of digitalization with SONOCHEK

Leak detection in the age of digitalization with SONOCHEK

Ismaning, October 16, 2018 – Together with the update of the SONOCHEK apps SONOLEVEL and SONOLEAK, PRUFTECHNIK launches the SONOLEVEL DATAVIEWER, a new visualization PC-software for leak analysis. SONOCHEK is an innovative digital leak inspection device used to localize leaks in compressed air, gas and vacuum systems. The device includes automatic leak classification and its broad bandwidth of 20 to 100 kHz allows detecting leaks even at an early stage. SONOCHEK is also used effectively for electrical inspection and monitoring of bearing lubrication.

 October - November 2018

October - November 2018

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