Page 74 - Intro Predictive Maintenance

Benefits of Predictive Maintenance 65

budget of survey participants ($12,053,000), the average annual savings are about $1.6
million.

A successful predictive maintenance program, according to most publications, should
generate a return on investment of between 10:1 and 12:1. In other words, the plant
should save $10 to $12 for every dollar invested. The survey results clearly indicate
that this is not the case. Based on the statistics, the average return on investment was
only 1.13:1, slightly better than breakeven. If this statistic were true, few financial
managers would authorize an investment in predictive maintenance.

The statistics generated by the survey may be misleading. If you look carefully at the
responses, you will see that 26.2 percent of respondents indicated that their programs
recovered invested costs; 13 percent did not know; and 50.8 percent did not recover
costs. From these statistics, one would have to question the worth of predictive tech-
nology; however, before you judge its worth, consider the remaining 10 percent. These
plants not only recovered costs but also generated additional savings that increased
bottom-line plant profitability. Almost half of these plants generated a profit five times
greater than their total incurred cost, a return on investment of 5:1. Although this return
is well below the reported norm of successful predictive maintenance programs, it
does have a substantial, positive effect on profitability.

The statistics also confirm our belief that few plants are taking full advantage of pre-
dictive maintenance capabilities. When fully utilized, these technologies can generate
a return on investment well above 100:1 or $100 for every dollar invested. As we have
stated many times, the technology is available, but it must be used properly to gain
maximum benefits. The survey results clearly show that this is not yet occurring for
many companies.

Which Technology Is Most Beneficial
Each of the participants was asked to rank each of the traditional predictive mainte-
nance technologies based on its benefits to improved performance. Vibration analysis
was selected as the most beneficial by 54.6 percent of respondents. This statistic is
not surprising for two reasons. First, most of the equipment, machines, and systems
that constitute a typical plant are mechanical and well suited for vibration monitor-
ing. The second reason has two parts. First, vibration-monitoring technology and
instruments have evolved much faster than some of the other technologies. In the
past 10 years, data collection instrumentation and its associated software packages
have evolved to a point that almost anyone can use this technology effectively. The
same is not true of predictive technologies, which still require manual collection and
analysis.

The second part is that most users view vibration monitoring as being relatively
easy. Simply follow the data collection route displayed on a portable data collector;
download acquired data to a PC; print an exception report; and repeat the process a
few weeks or months later. Don’t laugh. This is exactly the way many vibration-
monitoring programs are done. Will this approach reduce the number and frequency