Maintenance Tools & Techniques

Not every maintenance tool fits on a tool belt, and not every maintenance tool is designed

for repairing assets. O+ther 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.

Potential failure indicates the point at which we notice that equipment is starting to deteriorate and fail.
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

potential failure to assess ho

w much more the equipment can 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, & 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.

Sunday, September 8, 2019