Page 78 - An Introduction To Predictive Maintenance

68 An Introduction to Predictive Maintenance

problem is not limited to effective measurement of predictive maintenance programs,
but severely restricts the ability to manage all plant functions.

The ability to effectively use predictive maintenance technologies strictly depends on
your ability to measure change. Therefore, it is essential that the plant implements and
maintains an effective plant performance evaluation program. Universal use of a
viable set of measurement criteria is essential.

More Management Involvement. Only 1 percent of the survey participants stated that
more management involvement was needed. Of all the survey responses, this is the
greatest surprise. Lack of management commitment and involvement is the primary
reason that most predictive maintenance programs fail. Based on the other responses,
this view may be a result of the respondents’ failure to recognize the real reason
for ineffective programs. Most of the responses, including increasing the monitoring
frequency, have their roots in a lack of management involvement. Why else would
the frequency be too great?

When you consider that 30.7 percent of these programs were implemented because of
management directives, one would conclude that management commitment is auto-
matic. Unfortunately, this is too often not the case. Like most of those interviewed,
plant management does not have a complete understanding of predictive maintenance.
They do not understand the absolute necessity of regular, timely monitoring cycles;
the labor required to gain maximum benefits; or the need to fully use the information
generated by the program. As a result, too many programs are only partially imple-
mented. Staffing, training, and universal use of data are restricted in a misguided
attempt to minimize cost.

Conclusions
The survey revealed many positive changes in the application and use of predictive
maintenance technology. More participants are beginning to understand that this tool
offers more than just the ability to prevent catastrophic failure of plant machinery. In
addition, more plants are adopting these technologies and either have or plan to imple-
ment them in their plants. Apparently, few question the merit of these technologies
as a tool to improve product quality, increase capacity, and reduce costs. These are
all positive indications that predictive maintenance has gained credibility and will
continue to be used by a growing number of plants.

The bad news is that too many plants are not fully utilizing predictive maintenance.
Many of you have heard about or read my adamant opinion that predictive mainte-
nance is not working. The survey results confirm this viewpoint. When fewer than 10
percent of the programs generate a positive return on investment, it would be difficult
to disagree with this point. Is this a failure of the technology or are we doing some-
thing wrong?

In my opinion, the latter is the sole reason that predictive maintenance has failed to
consistently achieve its full potential. The technology is real, and the evolution of