Efficient Plant October 2017 - 29

```feature | reliability strategies

Looking For
Failure

WHEN NEW EQUIPMENT is
put into service, it's usually integrated into a plant's equipment-monitoring
program. The purpose of this program is to check
the progress of degradation, i.e., to look for failure. Typically,
that's a two-step process. The first step is to measure important operating parameters at regular intervals. The second is
to plot the measurements against time to understand how
things are progressing. When a measured parameter exceeds
its safe operating limit, the equipment is removed from service and refurbished. There is, however, an error trap in the
first step: It involves "regular intervals."
Most "regular intervals" are based on monitoring equipment as it performs in Zone II of its Weibull probability density
curve. Failure, though, typically occurs in Zone III. Sampling
periods sufficient to monitor equipment performance in Zone II
are typically insufficient to provide adequate warning of impending
failure when the equipment is operating in Zone III. In short, you're
looking for failure in the wrong places.

WHAT'S HAPPENING?
Let's start this discussion with a refresher on Zones I, II, and III.
As well-informed reliability and maintenance engineers know, a
plot of equipment failure rate versus its service time tends to follow
a mixed Weibull probability density curve (see Sidebar on p. 30),
otherwise known as the bathtub curve
While the information needed to generate a specific bathtub
curve from its fundamental Weibull probability density function
depends upon several parameters, the principles embedded in a
generalized curve of this type are fundamental to understanding
equipment reliability.
A typical bathtub curve is composed of three distinct parts, or
zones.
 Zone I has a Weibull function β shape factor, sometimes
called the Weibull slope, equal to about 0.5. This portion of
the bathtub curve is typically associated with equipment

OCTOBER 2017

in All the

Wrong
Places
Focus on 'zones' when
reliability of plant equipment
is concerned.
Randall Noon, P.E.

infant mortality failures, where the failure rate decreases with
time in service. Failures in this part of the curve are the result
of equipment installation errors, equipment assembly errors
at the factory, or part defects. This is sometimes referred to
as the break-in or shake-down period. Normally, this reflects
the shortest portion of the bathtub curve with respect to time.
In general, the most reliable operating time of the equipment,
i.e., its lowest failure rate, occurs directly after the equipment
EFFICIENTPLANTMAG.COM |

29

```
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Editorial
Implementations
Profitable Reliability Control On Your Horizon
Experts Provide IIoT Insights
Fluid-Flow Challenges
Looking For Failure In All The Wrong Places
Closer Human/Robot Collaboration
Note These Causes Of Motor Failure
Reliable Pumping Supplement: Food & Beverage Processing
On The Floor
Uptime
IIoT
Pump 'Cavitation' Might Not Be
Never Too Late For Basic Navigation
Audit or Assess? Understand The Difference
A Perfect Pair: Barcodes and Your CMMS
Lubrication Strategies
Products
Showcase
Efficiency Insight
Efficient Plant October 2017 - 1
Efficient Plant October 2017 - Cover1
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Efficient Plant October 2017 - 1
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Efficient Plant October 2017 - Editorial
Efficient Plant October 2017 - 9
Efficient Plant October 2017 - Implementations
Efficient Plant October 2017 - 11
Efficient Plant October 2017 - Profitable Reliability Control On Your Horizon
Efficient Plant October 2017 - 13
Efficient Plant October 2017 - 14
Efficient Plant October 2017 - 15
Efficient Plant October 2017 - Experts Provide IIoT Insights
Efficient Plant October 2017 - Integrating Automation Into Shade Manufacturing
Efficient Plant October 2017 - 21
Efficient Plant October 2017 - 22
Efficient Plant October 2017 - 23
Efficient Plant October 2017 - 17
Efficient Plant October 2017 - 18
Efficient Plant October 2017 - 19
Efficient Plant October 2017 - Integrating Automation Into Shade Manufacturing
Efficient Plant October 2017 - 21
Efficient Plant October 2017 - 22
Efficient Plant October 2017 - 23
Efficient Plant October 2017 - 24
Efficient Plant October 2017 - Fluid-Flow Challenges
Efficient Plant October 2017 - 26
Efficient Plant October 2017 - 27
Efficient Plant October 2017 - 28
Efficient Plant October 2017 - Looking For Failure In All The Wrong Places
Efficient Plant October 2017 - 30
Efficient Plant October 2017 - 31
Efficient Plant October 2017 - 32
Efficient Plant October 2017 - 33
Efficient Plant October 2017 - Closer Human/Robot Collaboration
Efficient Plant October 2017 - 35
Efficient Plant October 2017 - Note These Causes Of Motor Failure
Efficient Plant October 2017 - 37
Efficient Plant October 2017 - 38
Efficient Plant October 2017 - Reliable Pumping Supplement: Food & Beverage Processing
Efficient Plant October 2017 - 40
Efficient Plant October 2017 - 41
Efficient Plant October 2017 - 42
Efficient Plant October 2017 - 43
Efficient Plant October 2017 - 44
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Efficient Plant October 2017 - 46
Efficient Plant October 2017 - On The Floor
Efficient Plant October 2017 - 48
Efficient Plant October 2017 - Uptime
Efficient Plant October 2017 - IIoT
Efficient Plant October 2017 - Pump 'Cavitation' Might Not Be
Efficient Plant October 2017 - Never Too Late For Basic Navigation
Efficient Plant October 2017 - Audit or Assess? Understand The Difference
Efficient Plant October 2017 - A Perfect Pair: Barcodes and Your CMMS
Efficient Plant October 2017 - Lubrication Strategies
Efficient Plant October 2017 - 56
Efficient Plant October 2017 - 57
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Efficient Plant October 2017 - Products
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