Maintenance Tools &Techniques
Not every maintenance tool fits on a tool belt, and not
every maintenance tool is designed
for repairing assets. Other tools exist that help
maintenance teams improve things beyond
physical assets. For instance, various types of analyses are
used to gather insights about
why and when assets fail. And standards, regulations, and
other documentation exist to
keep maintenance teams organized and compliant.
Using these maintenance tools will help you build an
environment in which proactive
maintenance and precision maintenance can
thrive.
Analysis
P-F Curve
A P-F curve is a graph that shows the health of equipment
over time to identify the
interval between potential failure and functional failure.
P-F Curve
What is a P-F curve?
A P-F curve is a graph that shows the health of equipment
over time to identify the
interval between potential failure and functional failure.
Overview
The eventual failure of any equipment is inevitable. Wear
and tear naturally occur with
continual usage. In the same way your pair of shoes
eventually get worn out after
500 miles of walking, your key plant equipment (e.g. pumps,
motor bearings)
will ultimately reach its functional failure point.
The good news is that the functional failure point (i.e. the end of equipment
life) takes
a long time to occur. The P-F curve helps to
characterize the behavior of equipment
over time. Its used to assess the maximum usage that
can be gained from the equipment.
Potential failure and functional failure
There are two main points of the P-F curve that need to be
identified.
1. Potential
failure indicates the point at which we notice that equipment is starting
to deteriorate and fail.
2. Functional failure is
the point at which equipment has reached its useful limit and is no longer
operational.
These two points define what’s called as the P-F
interval—the time between when the failure
is initially noticed and when the equipment fails
completely.
How to create a P-F curve
The basic parts of the P-F curve are given above. Actual
data can be expected to vary on a case to case basis. For instance, the
lifespan of a heavy duty pump might not be the same as that of a mechanical
bandsaw. It then follows that expected failure points for different equipment
will vary. Care must be considered when building P-F curves. Different types of
equipment are expected to have varying interval values.
For example, assume that a pump that’s been normally operating for eight months
suddenly produces more noise than usual. Unnecessary noise can be a sign of
failure. With the inspection and confirmation of maintenance personnel, we can
then say that the first noticed sign of failure (i.e. the potential failure
point) occurred at eight months.
Note that the actual start of deterioration might have happened before the
eight-month mark. So we can assume that the actual start of failure happened
some time before point P. However, it is only the potential point of failure
that we can measure in time with certainty as it was the first event when
noticeable symptoms of failure were recorded.
For the same example, we can suppose that the pump continues to operate for
another six months until it totally breaks down—that is the functional failure
point at 14 months.
How to maximize the P-F curve
Now that we’ve visualized how the P-F curve relates to
real-life scenarios, we have the chance to prepare for the inevitable
functional failure. The idea is to balance our resources to prolong the P-F
interval economically.
Common practice is to maximize the use of the P-F curve with condition-based
maintenance (CBM). By applying CBM and proactively checking the condition of
the equipment, we are able to infer the rate of deterioration over time.
Maintenance personnel are then able to plan and assess whether it is
cost-efficient to mitigate the causes of failure given the projected P-F
interval.
The P-F curve and CBM
At the early signs of failure, it may be helpful to perform
routine CBM tasks to assess the health of the equipment.
Continuing with our pump example, a P-F curve coupled with CBM tasks to monitor
pressure and flow rate conditions may resemble the following graph:
A maintenance team can attach condition monitoring sensors to the equipment
after the point of potential failure to assess ho
w much more the equipment can be maximized.
Key Takeaways
- Functional
failure does not happen overnight; it is important to plan out and
maximize the equipment’s life cycle
- Potential
failure is the first noticeable signs of failure; the actual start of
failure may have occurred earlier but gone unrecognized
- CBM
is a type of maintenance that complements the P-F curve analysis as it
monitors the health and condition of equipment
- Prolonging
the interval from a potential failure to the functional failure should be
maximized
FMEA
Failure Mode and Effects Analysis (FMEA) is a process that
is available to organizations to identify potential failures with assets and
other areas of business.
FMEA is the systematic process to evaluate failure modes,
causes associated with failures and the effect of such failures. The cross
functional core committee needs to identify known and potential areas of
failure and the root-causes of such failure through why–why analysis.
Brainstorming through small group activities may be carried out involving the
frontline supervisors and even operators. The failure modes can be prioritised
by assigning Risk Priority Number (RPN), which is a product of occurrence (frequency
of failure O), severity (seriousness of the failures S) and detection (ability
to detect the failure D).
RPN = O x S x D
Details of the failure analysis need to be documented.
Acronym for Failure Modes and Effects Analysis. FMEA is a
risk assessment tool, that evaluates the severity, occurrence and detection of
risks to prioritize which ones are the most urgent. The two most popular types
of FMEAs are Process (PFMEA) and Design (DFMEA).
Each category has a scoring matrix with a 1-10 scale.
- Severity
of 1 denotes low risk to the end customer, and a score of 10 denotes high
risk to the customer.
- Occurrence
of 1 denotes low probability of the risk happening, and a 10 denotes a
very high probability of the risk happening.
- Detection
of 1 denotes a process that WILL likely catch a failure, and a 10 means
the process will likely NOT catch a failure.
Here are some sample scoring tables for your reference
After scoring of each category is complete for each risk, the three scores are
multiplied together (Severity x Occurrence x Detection) to determine the Risk
Priority Number (RPN). The RPNs are sorted from largest to smallest, and
actions are taken on the top risks in order to reduce the overall risk.
Typically, the severity cannot be reduced, so the team
should evaluate ways to reduce occurrence or increase detection. After actions
are completed, the RPNs are recalculated and new risks are determined.
Root Cause Analysis
Root cause analysis (RCA) is a systematic process of
identifying the origin of an incident.
Next to defining a problem accurately, root cause analysis
is one of the most important elements of problem-solving in quality management.
That’s because if you’re not aiming at the right target, you’ll never be able
to eliminate the real problem that’s hurting quality.
So which type of root cause analysis tool is the best one to
use? Manufacturers have a range of methods at their fingertips, each of which
is appropriate for different situations. Below we discuss five common root
cause analysis tools, including:
- Pareto
Chart
- The
5 Whys
- Fishbone
Diagram
- Scatter
Diagram
- Failure
Mode and Effects Analysis (FMEA)
1. Pareto Chart
A Pareto chart is a histogram or bar chart combined with a
line graph that groups the frequency or cost of different problems to show
their relative significance. The bars show frequency in descending order, while
the line shows cumulative percentage or total as you move from left to right.
The Pareto chart example above is a report from layered
process audit software that groups together the top seven categories of
failed audit questions for a given facility. Layered process audits (LPAs)
allow you to check high-risk processes daily to verify conformance to
standards. LPAs identify process variations that cause defects, making Pareto
charts a powerful reporting tool for analyzing LPA findings.
Pareto charts are one of the seven basic tools of quality
described by quality pioneer Joseph Juran. Pareto charts are based on Pareto’s
law, also called the 80/20
rule, which says that 20% of inputs drive 80% of results.
2. 5 Whys
The 5 Whys is a method that uses a series of questions to
drill down into successive layers of a problem. The basic idea is that each
time you ask why, the answer becomes the basis of the next why. It’s a simple
tool useful for problems where you don’t need advanced statistics, so you don’t
necessarily want to use it for complex problems.
One application of this technique is to more deeply analyze
the results of a Pareto analysis. Here’s an example of how to use the 5 Whys:
Problem: Final assembly time exceeds target
- Why
is downtime in final assembly higher than our goal? According to the
Pareto chart, the biggest factor is operators needing to constantly adjust
Machine A
- Why
do operators need to constantly adjust Machine A? Because it keeps having
alignment problems
- Why
does Machine A keep having alignment problems? Because the seals are worn
- Why
are Machine A’s seals worn? Because they aren’t being replaced as part of
our preventive maintenance program
- Why
aren’t they being replaced as part of our preventive maintenance
program? Because seal replacement wasn’t captured in the needs
assessment
Of course, it may take asking why more than five times to
solve the problem—the point is to peel away surface-level issues to get to the
root cause.
3. Fishbone Diagram
A fishbone diagram sorts possible causes into various
categories that branch off from the original problem. Also called a
cause-and-effect or Ishakawa diagram, a fishbone diagram may have multiple
sub-causes branching off of each identified category.
4. Scatter Plot Diagram
A scatter plot or scatter diagram uses pairs of data points
to help uncover relationships between variables. A scatter plot is a
quantitative method for determining whether two variables are correlated, such
as testing potential causes identified in your fishbone diagram.
Making a scatter diagram is as simple as plotting your
independent variable (or suspected cause) on the x-axis, and your dependent
variable (the effect) on the y-axis. If the pattern shows a clear line or
curve, you know the variables are correlated and you can proceed to regression
or correlation analysis.
5. Failure Mode and Effects Analysis (FMEA)
Failure mode and effects analysis (FMEA) is a method used
during product or process design to explore potential defects or failures. An
FMEA chart outlines:
- Potential
failures, consequences and causes
- Current
controls to prevent each type of failure
Severity (S), occurrence (O) and detection (D) ratings that
allow you to calculate a risk priority number (RPN) for determining further
action
Lean Six Sigma
Lean Six Sigma is a process that aims to systematically
eliminate waste and reduce variation.
https://textilesworldwide.blogspot.com/2017/04/six-sigma-lean-six-sigma-benifits-for.html
SCADA System
Supervisory control and data acquisition (SCADA) systems are
a computer system used to monitor and control plant processes.
SCADA
Supervisory control and data acquisition (SCADA) is a system
of software and hardware elements that allows industrial organizations to:
- Control
industrial processes locally or at remote locations
- Monitor,
gather, and process real-time data
- Directly
interact with devices such as sensors, valves, pumps, motors, and more
through human-machine interface (HMI) software
- Record
events into a log file
SCADA systems are crucial for industrial organizations since
they help to maintain efficiency, process data for smarter decisions, and
communicate system issues to help mitigate downtime.
The basic SCADA architecture begins with programmable logic controllers (PLCs)
or remote terminal units (RTUs). PLCs and RTUs are microcomputers that
communicate with an array of objects such as factory machines, HMIs, sensors,
and end devices, and then route the information from those objects to computers
with SCADA software. The SCADA software processes, distributes, and displays
the data, helping operators and other employees analyze the data and make
important decisions.
For example, the SCADA system quickly notifies an operator that a batch of
product is showing a high incidence of errors. The operator pauses the
operation and views the SCADA system data via an HMI to determine the cause of
the issue. The operator reviews the data and discovers that Machine 4 was
malfunctioning. The SCADA system’s ability to notify the operator of an issue
helps him to resolve it and prevent further loss of product.
Planned Maintenance Optimization
Planned Maintenance Optimization (PMO) is a method of
improving maintenance strategies based on existing preventive maintenance (PM)
routines and available failure history.
What is planned maintenance optimization?
Planned Maintenance Optimization (PMO) is a method of
improving maintenance strategies based on existing preventive maintenance (PM)
routines and available failure history.
Overview
While most companies have identified the need for a
preventive maintenance (PM) program, the effective execution of such
maintenance activities can be challenging given the everyday demands of a
facility. Unseen circumstances that require urgent attention can easily derail
planned activities and can potentially disrupt a smoothly running plant.
While alternatives such as reliability centered maintenance (RCM) addresses
some of the factors that make PM a cost- and labor-intensive process, coming up
with a robust RCM strategy may take long periods of time.
PMO provides a method through which maintenance activities are carried out more
efficiently. By performing PMO, a new maintenance strategy is derived from
existing PM tasks. Given the existing tasks, modifications on the schedule and
frequency of the routines are done based on the failure history of the
equipment. With a relatively shorter time to develop, the resulting strategy
can be similar to performing RCM.
The three phases of PMO
The PMO process can be summarized in three phases:
Data collection
Any attempt at optimization starts with good, reliable data.
Data on equipment performance, particularly on failure history over time, must
be collected. A minimum time period must be set to ensure that enough insight
is obtained from the data. Tools such as a CMMS program can make this process
easier and more accurate.
Data analysis, review, and recommendations
The collected data must be analyzed to identify which
equipment is the most critical. Some points to consider are criticality to the
plant’s operations, cost to repair, MTBF, and MTR.
The information gathered from analyzing the data must then be reviewed against
existing PM routines. Some key points to review are: 1) whether the PM routines
are scheduled correctly to align with the MTBF and MTR data points, and 2)
whether failure points are within acceptable tolerances set by original
equipment manufacturer (OEM) specifications or industry standards. Any
substantial deviations from such checks can be a source of improvement from a
maintenance standpoint.
Based on the review, recommendations on modifications for the PM tasks should
be made. Schedules and frequencies of activities need to be optimized to meet
MTBF and MTR constraints. Any missing maintenance activities, as well as
redundancies in tasks, need to be addressed accordingly.
Agreement and execution
Agreed action items must be delegated properly. Identified
task owners should be accountable for any required action and monitored for
progress. Note that the PMO process is a continuous effort and reviews should
be done habitually.
Benefits of applying PMO
Regular maintenance activities are clearly a key part in
ensuring a plant’s reliability. But PMO further increases the benefits of
maintenance activities by showing substantial reductions in costs.
In the laboratory and life sciences industry, a PMO program is estimated to
reduce overall maintenance costs by around 25%. Payback periods of investing in
a PMO strategy are estimated at around 12 to 24 months, just considering the
measured savings from maintenance costs.
Aside from the improvements in uptime and reliability that come with a robust
maintenance strategy, PMO methods enable company resources to be spent more
wisely without sacrificing the quality of execution of maintenance tasks.
Conclusion
Maintenance activities, particularly PM activities, are
already proven concepts that increase the overall performance of a plant. With
continuous practice, PMO is a tool that can help execute PM activities more
efficiently and effectively.
Standards
ISO 55000
To comply with ISO 55000 you must have an asset management
system. The goal of an asset management system is to establish the policies,
objectives, and processes needed to achieve an organization’s goals.
ISO 55001
The components of an asset management system that are listed
out in ISO 55000 are elaborated on in ISO 55001. These components include
organizational context, leadership, planning, support, operation, performance
evaluation, and improvement.
ISO 55002
ISO 55002 provides the most significant details needed to
achieve compliance with ISO 55000.
SAE JA1011
SAE JA1011 was initially developed by the commercial
aviation industry to improve the safety and reliability of their equipment.
Because of this, it’s known as a Reliability-Centered Maintenance (RCM)
process.
Regulations
FDA Maintenance Regulations
FDA inspections are typically conducted by reviewing systems
which correspond to the Subparts that are applicable to the type of
product/facility being audited. In the case of maintenance, Subparts for
Buildings and Facilities and Equipment are of the main concern.
OSHA Maintenance Regulations
Maintenance workers are among the many workers that are
exposed to workplace hazards on a daily basis. OSHA aims to protect them by
providing access to information for vulnerable workers in high-risk jobs.
IRS Maintenance Regulations
There are specific deductible and capital improvement costs
that are directly related to maintenance operations and the IRS provides
information about how it allows businesses to recover those costs.
Documents
Equipment Maintenance Log
An equipment maintenance log is a document that records
activities that have been performed on an asset.
Operation and Maintenance Manual
An operation and maintenance manual is a comprehensive
document that provides all the details necessary about a physical plant as well
as individual pieces of equipment to help the maintenance staff keep everything
running smoothly.
