Spectro Scientific Blog

Retesting And Resampling Can Save Millions

Introduction 

Power plants today face headwinds in delivering power to customers. Power suppliers must meet the “Three Rs” for power system reliability: resource adequacy (people, equipment, facilities, availability), system resiliency (ability to bounce back from disruption) and operational reliability (assets performing without unplanned downtime).1

Introduction 

Downtime for critical equipment is costly in terms of dollar expense, productivity and human lives. Oil analysis is one of the most important and reliable techniques to keep these assets up and running.

Introduction 

This article is the first in a series to make a strong case for performing more and better testing of in service lubricants in order to replace unplanned repairs and unplanned downtime with planned repairs during scheduled time. In other words, this article is about using oil analysis to help improve reliability, planning and scheduling. More and better testing involves more lubricant sample points with better focus on large wear particle analysis.

Introduction 

Comprehensive oil analysis requires sampling, testing and analyzing in-service industrial lubricants to evaluate the wear condition of machinery, the contamination condition of lubrication systems, and chemistry condition of the lubricants. This article intentionally focuses attention on analysis of large wear particles because the resulting analysis information enables informed users time for planned maintenance instead of surprise, reactive unplanned repairs.

Practical Steps to Increase Your Site’s Ability to Detect
and Manage Abnormal Lubrication Events

There is a lot of discussion about artificial intelligence (AI), internet of things (IoT) and how these can be applied in all areas of reliability programs, particularly oil analysis. In this technology, many users struggle to understand and trust how alarms are set, maintained, and adapted to meet the changing conditions with lubricated mechanical equipment. All of these intelligence initiatives are ineffective if the data is not trustworthy.

Spectro Scientific's Oil Analysis Handbook

This Oil Analysis Handbook covers a wide variety of topics ranging from specific oil analysis techniques to applications for oil analysis, to success stories of companies that use on-site oil analysis to lower costs and improve uptime. The applications for oil analysis range from mining and trucking to water treatment, service providers, and industrial plants.  Learn how to improve reliability while cutting maintenance costs and avoiding costly downtime.

Oil analysis is a core practice recognized within the reliability professional community to improve machine reliability and save money.  Many companies and organizations already employ some type of oil analysis program within their maintenance practices.   

Point of care oil analysis is now established and accelerating as companies find reliability improvements and cost savings.

In a recent reliability survey, between 60 to 70% of industrial facilities employ oil analysis as an important component of their reliability programs. Oil analysis gives a snapshot of machinery health, preventing unnecessary oil changes and predicting equipment failures before they happen. Most organizations draw oil analysis samples and ship them off-site to be analyzed in a laboratory. The results are sent back anywhere from days to weeks depending on location and industry.

Point of care oil analysis (today’s on-site oil analysis) has grown rapidly in the last three years as leading companies in power generation, mining, food production and industrial manufacturing invest in tools and software solutions to insource at each production site. Benefits experienced by these early leaders indicates that this trend will accelerate more now, despite current challenges. Here are 5 reasons why organizations across the world are investing in point of care solutions:

The Beginner's Guide to Trending Parameters for Machinery Wear on the LaserNet 200 Series

Establishing alarm limits and condemnation levels for large machinery wear particles is a common topic discussed among reliability professionals. Equipment manufacturers are often not forthcoming with this information since each piece of equipment potentially generates wear at a different rate.  Trending and monitoring deviations from trends is the recommended way for developing alarm limits and condemnation levels on the component. As part of the MiniLab system, the LaserNet 200 Series is a powerful tool to trend particle counts, classify wear particles and monitor ferrous debris levels.

What is lubricant mix-up?

Lubricant mix-up describes any situation where the lubricant, new or in service, does not meet the exact specification requirement.