Organizations have used oil analysis for decades to identify lubrication problems that could require equipment repair or even shut down an entire line of heavy machinery. Although the technique for sample collection remains predominantly unchanged, technology has revolutionized the information available once the sample is analyzed. Improved technology, however, can mean a sea of data, which may be overwhelming to even the most business-savvy customer. There are many oil analysis software programs that promise to process complicated data, interpret results and offer recommendations. Additionally, beyond traditional sample analysis, software programs now offer systems for managing maintenance schedules, advanced data graphing and data-mining applications.
Not surprisingly, today’s plant engineers and fleet managers have several options when selecting software to manage their oil analysis needs. Choosing the proper software and maximizing its features can provide a huge payback for the user through reduced machinery maintenance expenses.
For more than 50 years, oil analysis has been used to help diagnose the internal condition of oil-wetted components. Original testing methods focused on visual inspection coupled with a simple smell test. First used in the railroad industry in 1946, laboratory analysts detected problems in diesel engines through evaluation of metals in used oils. By 1955, the United States Naval Bureau of Weapons had adopted oil analysis procedures to predict aircraft component failure.
Testing and evaluation practices have evolved dramatically over the last five decades, making oil analysis one of the most effective predictive maintenance technologies available. Monumental changes have taken place within the laboratory in the areas of sample evaluation and more importantly in how the data is reported and managed.
As recently as 10 years ago, customers collected an oil sample, hand-wrote information on a label and mailed the sample to the laboratory via traditional mail services. Two or three weeks later, the customer would receive a hard copy of the laboratory report in the mail. Today, improved instrumentation, streamlined delivery services and enhanced technology put comprehensive results in a customer’s hand within 24 hours. This shortened result cycle is essential in the identification of critical samples and can prevent expensive equipment repairs and costly downtime.
Additional benefits of a properly executed oil analysis program include reduced lubricant costs, decreased energy consumption, enhanced equipment efficacy, improved production, and reduced risk of injury and environmental damage.
As research and technology have advanced over the years, progress in lubricant testing has kept pace. The following are some of the key areas of technology enhancement in the oil analysis industry:
Once limited to a single hard copy of a distinct sample, customers can now review results online, download reports and share them with colleagues. The delivery cycle has also been condensed from several weeks to within 24 hours.
Online labeling offers the ability to print pre-registered
sample labels for quick and proper processing.
“I can do oil analysis 24 hours a day, seven days a week, 365 days a year,” says industry expert and consultant John Underwood. “I used to have to wait for weeks for the paper to show up in the mail two weeks after I submitted the sample.”
Within the last decade, technology has allowed field technicians to use the Internet to input comprehensive data about each oil sample. This improvement has reduced the risk of incorrect information gleaned from hand-written forms as well as increased the amount of information technicians can provide to laboratories about each sample.
Current oil analysis software programs offer improved reporting capabilities that extend far beyond the examination of a single sample. In addition to maintenance program management tools, software developments have enabled cross-comparison of makes, models and lubricant types within the asset population. Maintenance administrators can manage equipment information online and provide it to laboratory experts, which in turn enables data-mining capabilities that can identify critical trends. Graphing tools can also give a visual representation of the results.
Choosing a laboratory and technology partner for your predictive maintenance program is not a decision to be taken lightly. Rather, it is important for this strategic evaluation to consider several essential factors:
By selecting an independent lab, customers are assured non-biased information from an organization that encourages total access and utilization of all the data and management tools available. Brand-specific laboratories may be experts on their own products, but they may not be trained on a variety of equipment or lubricants. While independent sources are always fee-based, these organizations offer the most state-of-the-art technology and services available. The bottom line is that it’s your data, and you should have access to as much information as possible.
While technology is ever evolving, the importance of expert human involvement cannot be overstated. Search for a lab with depth of knowledge and experience as well as important industry credentials.
Look for a system that allows you to proactively manage equipment records, including location, name or identification, make, model and lubricant information.
Not every member of a team needs access to every piece of information. The best software programs allow maximum flexibility, enabling mangers to self-administer and control customized permissions. Choose a system that lets administrators add and delete users, establish and manage groups of users, and grant individualized access permissions. Other beneficial tools include customizable views and layouts, which put the most useful and important information right where you need it when you need it most.
One of the most recent and helpful technological developments is customized graphing and result capability. Gone are the days of pouring over spreadsheets searching for tendencies and clues. Trend graphs utilize user-defined criteria to provide a visual representation of general wear, contamination and other common problems. Comparison graphing allows users to compare specific pieces of equipment against like machines or an entire population of equipment. Providing complicated information in an easy-to-understand format, these reports deliver useful information for maintenance and purchasing decisions.
Dashboards provide users with easy-to-understand graphs
regarding sampling program performance.
The return on your oil analysis program depends greatly on what you put into it. Industry research indicates that most maintenance programs achieve only 10 percent of the benefits available from oil analysis. User adoption of a more technological marketplace has been slow, and many fear information overload. However, by employing a few key strategies, you can maximize your oil analysis software for maximum results.
At its most basic level, training can consist of the proper technique for sampling. Even with just simple computer skills, users can learn to navigate software programs and take full advantage of their services and benefits.
“Training is critical to helping users understand what the programs can do to make their jobs easier and more effective,” Underwood says.
Many programs provide training via workshops, online videos, webinars, onsite training, newsletters or downloadable PDFs. Encourage your team to utilize these educational modalities. As users become comfortable with the basics, they can add to their learning based on their role or the company’s needs. For example, lubrication technicians can learn more about sampling techniques and data input, while engineers can explore more technical graphing tools. If the software program offers ongoing customer service, don’t hesitate to contact the hotline for product-specific guidance.
Customizable features make managing an oil analysis program easier and more effective than ever. Beyond tracking and storing results, modern systems help users record maintenance events such as sampling dates, usage hours and time in service. You can also create customized alarms to routinely collect samples on a prescribed basis. Whether your maintenance practices require collection every 500 hours or every quarter, these predictive samplings can prevent condition-based situations that may signal imminent failure. Also, look for scalable programs that adjust to your individual needs.
The adage “garbage in, garbage out” never rang more true than when collecting a lubricant sample.
“Technology cannot make up for a bad sample,” Underwood warns.
Incomplete or illegible information can lead to data-entry errors and limited testing that yields suboptimal reporting. Once restricted to whatever information could be scribbled on a small label, the latest software programs allow maintenance technicians to input critical information, including equipment (make, model, identification number, location, etc.), hours of operation, maintenance activities, drain interval and more.
Equipment management functions enable users to fully register
critical information about each piece of equipment.
While incomplete information doesn’t affect the test results, it significantly impacts the analyst’s ability to draw conclusions or detect trends. Therefore, it is essential that users provide repetitive, information-rich and credible samples to ensure quality and meaningful reports. When more data points are given during the sampling process, laboratory analysts can deliver more comprehensive reports. With consistent and complete sample information, labs can ensure normalization of results based on the organization’s result history.
A highly technical area of computer science, data mining extracts information from a set of data and transforms it into understandable and actionable information. In oil analysis, this process uses data management and complex metrics to detect abnormalities in single samples or groups of samples.
While laboratory experts excel in extracting comprehensive information from a sample, end users may find it difficult to put technical information into practical terms. The average manager typically isn’t interested in particle counts or the presence of iron or metals in a single piece of equipment. However, the ability to recognize trends across a population of equipment can signal a bigger problem that could result in lost revenue from downtime or expensive repairs.
According to Underwood, data mining is particularly helpful when managing fleets.
“The ability to compare units and equivalent services helps companies determine what the best product on the market is for their particular business,” he says.
It is important to note that data mining is not the end user’s responsibility but rather an important and integrated component of any effective software program.
Graphs and other visual representations highlight the severity of non-conforming data far better than tables and spreadsheets. Keep in mind that if a report isn’t readable, it won’t get read.
Comparison graphing offers a visual comparison of equipment performance
against a population of data, allowing plant personnel to determine
which makes and models are best suited for each site.
“A picture is worth a thousand words,” Underwood says. “People understand a graphical data presentation much more readily than a bunch of numbers, so it is a critical component to any software program.”
Users should be able to select different graphing styles (line, bar, area, spider, etc.) based on preference and need. Especially helpful in comparing a pre-defined set of parameters, graphs can use data normalization to identify wear rates and predict equipment failures. Beyond looking at a single piece of equipment or sample, graphs can provide a cross-comparison that allows users to compare units regardless of make, model or other specifications.
Graphing sample conditions enables users to easily spot
trends in specific units, equipment types, makes or models.
Graphs also present a visual picture of a single piece of equipment when compared to the entire population of machinery. While graphing tools should be easy to use, getting the most out of this new technology may require additional training.
Managing a plant or fleet and its maintenance program is a collaborative effort requiring a team of technicians, engineers, administrators and manufacturers. Communication between team members, especially in a critical situation, is vital. Today’s software programs allow administrators to authorize which users can view information, manage equipment and more. It’s even possible to share information with equipment and lubricant manufacturers, leveraging all available resources for maximum results. By establishing alerts, messaging, preferences and access for all essential team members, administrators can create a highly specialized network of shared information.
In this extremely competitive era of reduced profit margins, companies are forced to squeeze the most out of their maintenance budgets. People, equipment and systems are expected to do more with fewer resources. Information technology is necessary for any organization’s preventative maintenance program. With increased access to information, oil analysis software companies are helping maintenance managers spot trends, compare equipment and identify dangerous problems before they happen. Yet only 10 percent of users maximize their software programs. Ongoing training will help managers and administrators make the most of the ever-changing tools available.
Through the use of program management tools, proper sample registration, data-mining tools, graphical interpretations and data sharing, organizations can ensure the longevity of their equipment and a more robust bottom line. Technology will continue to advance, providing additional tools to the analysts, manufacturers, service providers and end users. How effectively that technology is leveraged will determine the ultimate success of the company.
Cary Forgeron is the national field service manager for Analysts Inc. He has more than 10 years of experience in developing oil sampling programs for end users to meet their organization’s maintenance and reliability goals. Contact Cary at firstname.lastname@example.org.