project manufacture
TRANSCRIPT
Department of Industrial Engineering
Special Topics in Industrial Engineering
Predictive Maintenance
Prepared by: Azamat Kibekbaev
Student No: 50071102
Supervised by: Prof. Dr. CEVDET MERIC
December 2011
Abstract
This paper aims at proposing reference models to integrate the predictive maintenance in
manufacturing system. To keep our operations running on schedule and budget, predictive
maintenance management has become an important part of our overall business strategy. We
need to proactively manage our predictive maintenance activities efficiently and effectively by
increasing collaboration between our production and maintenance resources, while optimizing
the performance of our equipment. Maintenance costs are a major part of the total operating costs
of all manufacturing or production plants. Depending on the specific industry, maintenance costs
can represent between 15 and 60 percent of the cost of goods produced. For example, in food
related industries, average maintenance costs represent about 15 percent of the cost of goods
produced, whereas maintenance costs for iron and steel, pulp and paper, and other heavy
industries represent up to 60 percent of the total production costs.
Introduction
What is maintenance and why is it performed? Past and current maintenance practices in both the
private and government sectors would imply that maintenance is the actions associated with
equipment repair after it is broken. The dictionary defines maintenance as follows: “the work of
keeping something in proper condition; upkeep.” This would imply that maintenance should be
actions taken to prevent a device or component from failing or to repair normal equipment
degradation experienced with the operation of the device to keep it in proper working order.
Unfortunately, data obtained in many studies over the past decade indicates that most private and
government facilities do not expend the necessary resources to maintain equipment in proper
working order. Rather, they wait for equipment failure to occur and then take whatever actions
are necessary to repair or replace the equipment. Nothing lasts forever and all equipment has
associated with it some predefined life expectancy or operational life. For example, equipment
may be designed to operate at full design load for 5,000 hours and may be designed to go
through 15,000 starts and stop cycles (1).
The need for maintenance is predicated on actual or impending failure – ideally, maintenance is
performed to keep equipment and systems running efficiently for at least design life of the
component(s). As such, the practical operation of a component is time-based function. If one
were to graph the failure rate a component population versus time, it is likely the graph would
take the “bathtub” shape shown in Figure 5.1.1. In the figure the Y axis represents the failure rate
and the X axis is time. From its shape, the curve can be divided into three distinct: infant
mortality, useful life, and wear-out periods.
The initial infant mortality period of bathtub curve is characterized by high failure rate followed
by a period of decreasing failure. Many of the failures associated with this region are linked to
poor design, poor installation, or misapplication. The infant mortality period is followed by a
nearly constant failure rate period known as useful life. There are many theories on why
components fail in this region, most acknowledge that poor O&M often plays significant role. It
is also generally agreed that exceptional maintenance practices encompassing preventive and
predictive elements can extend this period. The wear-out period is characterized by a rapid
increasing failure rate with time. In most cases this period encompasses the normal distribution
of design life failures (2).
The design life of most equipment requires periodic maintenance. Belts need adjustment,
alignment needs to be maintained, and proper lubrication on rotating equipment is required, and
so on. In some cases, certain components need replacement, (e.g., a wheel bearing on a motor
vehicle) to ensure the main piece of equipment (in this case a car) last for its design life. Anytime
we fail to perform maintenance activities intended by the equipment’s designer, we shorten the
operating life of the equipment. But what options do we have? Over the last 30 years, different
approaches to how maintenance can be performed to ensure equipment reaches or exceeds its
design life have been developed in the United States. In addition to waiting for a piece of
equipment to fail (reactive maintenance), we can utilize preventive maintenance, predictive
maintenance, or reliability centered maintenance (2).
(Lindley R. Higgins, Dale P. Brautigam, and R. Keith Mobley, Maintenance Engineering)
Literature Review
Reactive Maintenance
Reactive maintenance is basically the “run it till it breaks” maintenance mode. No actions or
efforts are taken to maintain the equipment as the designer originally intended to ensure design
life is reached. Studies as recent as the winter of 2000 indicate this is still the predominant mode
of maintenance in the United States. The referenced study breaks down the average maintenance
program as follows:
55% Reactive
31% Preventive
12% Predictive
2% Other
Note that more than 55% of maintenance resources and activities of an average facility are still
reactive.
Advantages to reactive maintenance can be viewed as a double-edged sword. If we are dealing
with new equipment, we can expect minimal incidents of failure. If our maintenance program is
purely reactive, we will not expend manpower dollars or incur capital cost until something
breaks. Since we do not see any associated maintenance cost, we could view this period as
saving money. The downside is reality. In reality, during the time we believe we are saving
maintenance and capital cost, we are really spending more dollars than we would have under a
different maintenance approach. We are spending more dollars associated with capital cost
because, while waiting for the equipment to break, we are shortening the life of the equipment
resulting in more frequent replacement. We may incur cost upon failure of the primary device
associated with its failure causing the failure of a secondary device. This is an increased cost we
would not have experienced if our maintenance program was more proactive. Our labor cost
associated with repair will probably be higher than normal because the failure will most likely
require more extensive repairs than would have been required if the piece of equipment had not
been run to failure. Chances are the piece of equipment will fail during off hours or close to the
end of the normal workday. If it is a critical piece of equipment that needs to be back on-line
quickly, we will have to pay maintenance overtime cost. Since we expect to run equipment to
failure, we will require a large material inventory of repair parts. This is a cost we could
minimize under a different maintenance strategy (2).
Preventive Maintenance
Preventive maintenance can be defined as follows: Actions performed on a time- or machine-
run-based schedule that detect, preclude, or mitigate degradation of a component or system with
the aim of sustaining or extending its useful life through controlling degradation to an acceptable
level.
The U.S. Navy pioneered preventive maintenance as a means to increase the reliability of their
vessels. By simply expending the necessary resources to conduct maintenance activities intended
by the equipment designer, equipment life is extended and its reliability is increased. In addition
to an increase in reliability, dollars are saved over that of a program just using reactive
maintenance. Studies indicate that this savings can amount to as much as 12% to 18% on the
average. Depending on the facilities current maintenance practices, present equipment reliability,
and facility downtime, there is little doubt that many facilities purely reliant on reactive
maintenance could save much more than 18% by instituting a proper preventive maintenance
program.
While preventive maintenance is not the optimum maintenance program, it does have several
advantages over that of a purely reactive program. By performing the preventive maintenance as
the equipment designer envisioned, we will extend the life of the equipment closer to design.
This translates into dollar savings. Preventive maintenance (lubrication, filter change, etc.) will
generally run the equipment more efficiently resulting in dollar savings. While we will not
prevent equipment catastrophic failures, we will decrease the number of failures. Minimizing
failures translate into maintenance and capital cost savings (8).
Reliability Centered Maintenance
Reliability centered maintenance (RCM) magazine provides the following definition of RCM: “a
process used to determine the maintenance requirements of any physical asset in its operating
context.”
Basically, RCM methodology deals with some key issues not dealt with by other maintenance
programs. It recognizes that all equipment in a facility is not of equal importance to either the
process or facility safety. It recognizes that equipment design and operation differs and that
different equipment will have a higher probability to undergo failures from different degradation
mechanisms than others. It also approaches the structuring of a maintenance program
recognizing that a facility does not have unlimited financial and personnel resources and that the
use of both need to be prioritized and optimized. In a nutshell, RCM is a systematic approach to
evaluate a facility’s equipment and resources to best mate the two and result in a high degree of
facility reliability and cost-effectiveness. RCM is highly reliant on predictive maintenance but
also recognizes that maintenance activities on equipment that is inexpensive and unimportant to
facility reliability may best be left to a reactive maintenance approach. The following
maintenance program breakdowns of continually top-performing facilities would echo the RCM
approach to utilize all available maintenance approaches with the predominant methodology
being predictive.
Because RCM is so heavily weighted in utilization of predictive maintenance technologies, its
program advantages and disadvantages mirror those of predictive maintenance. In addition to
these advantages, RCM will allow a facility to more closely match resources to need while
improving reliability and decreasing cost (3), (9).
Predictive Maintenance
Predictive maintenance can be defined as measurements that detect the onset of degradation
mechanism, thereby allowing causal stressors to be eliminated or controlled prior to any
significant deterioration in the component physical state. Results indicate current and future
functional capability. Basically, predictive maintenance differs from preventive maintenance by
basing maintenance need on the actual condition of the machine rather than on some preset
schedule. Preventive maintenance is time-based. Activities such as changing lubricant are based
on time, like calendar time or equipment run time. For example, most people change the oil in
their vehicles every 5,000 to 8,000 Kms travelled. This is effectively basing the oil change needs
on equipment run time. No concern is given to the actual condition and performance capability
of the oil. It is changed because it is time. This methodology would be analogous to a preventive
maintenance task. If, on the other hand, the operator of the car discounted the vehicle run
time and had the oil analyzed at some periodicity to determine its actual condition and
lubrication properties, he/she may be able to extend the oil change until the vehicle had
travelled 15,000 Kms. This is the fundamental difference between predictive maintenance and
preventive maintenance, whereby predictive maintenance is used to define needed maintenance
task based on quantified material/equipment condition.
Predictive maintenance can be defined as follows also: Measurements that detect the onset of
system degradation (lower functional state), thereby allowing causal stressors to be eliminated or
controlled prior to any significant deterioration in the component physical state. Results indicate
current and future functional capability.
Basically, predictive maintenance differs from preventive maintenance by basing maintenance
need on the actual condition of the machine rather than on some preset schedule. You will recall
that preventive maintenance is time-based. Activities such as changing lubricant are based on
time, like calendar time or equipment run time. For example, most people change the oil in their
vehicles every 3,000 to 5,000 miles traveled. This is effectively basing the oil change needs on
equipment run time. No concern is given to the actual condition and performance capability of
the oil. It is changed because it is time. This methodology would be analogous to a preventive
maintenance task. If, on the other hand, the operator of the car discounted the vehicle run time
and had the oil analyzed at some periodicity to determine its actual condition and lubrication
properties, he/she may be able to extend the oil change until the vehicle had traveled 10,000
miles. This is the fundamental difference between predictive maintenance and preventive
maintenance, whereby predictive maintenance is used to define needed maintenance task based
on quantified material/equipment condition.
The advantages of predictive maintenance are many. A well-orchestrated predictive
maintenance program will all but eliminate catastrophic equipment failures. We will be able to
schedule maintenance activities to minimize or delete overtime cost. We will be able to minimize
inventory and order parts, as required, well ahead of time to support the downstream
maintenance needs. We can optimize the operation of the equipment, saving energy cost and
increasing plant reliability. Past studies have estimated that a properly functioning predictive
maintenance program can provide a savings of 8% to 12% over a program utilizing preventive
maintenance alone. Depending on a facility’s reliance on reactive maintenance and material
condition, it could easily recognize savings opportunities exceeding 30% to 40%. In fact,
independent surveys indicate the following industrial average savings resultant from initiation of
a functional predictive maintenance program:
Return on investment: 10 times
Reduction in maintenance costs: 25% to 30%
Elimination of breakdowns: 70% to 75%
Reduction in downtime: 35% to 45%
Increase in production: 20% to 25%.
On the down side, too initially start into the predictive maintenance world is not inexpensive.
Much of the equipment requires cost in excess of $50,000. Training of in-plant personnel to
effectively utilize predictive maintenance technologies will require considerable funding.
Program development will require an understanding of predictive maintenance and a firm
commitment to make the program work by all facility organizations and management.
Predictive maintenance is a condition-driven preventive maintenance program. Instead of relying
on industrial or in-plant average-life statistics, i.e. mean-time-to-failure, to schedule maintenance
activities, predictive maintenance uses direct monitoring of the operating condition, efficiency,
heat distribution and other indicators to determine the actual mean-time-to-failure or loss of
efficiency that would be detrimental to plant operations for all critical systems in the plant or
facility. At best, traditional time-driven methods provide a guideline to normal machine-train life
spans. The final decision, in preventive or run-to-failure programs, on repair or rebuild schedules
must be made on the bases of intuition and the personal experience of the maintenance manager.
The addition of a comprehensive predictive maintenance program can and will provide factual
data on the actual operating condition of critical assets, including their efficiency, as well as the
actual mechanical condition of each machine- train and the operating efficiency of each process
system. Instead of relying on industrial or in-plant average-life statistics, i.e. mean-time-to-
failure, to schedule maintenance activities, predictive maintenance uses direct monitoring of the
mechanical condition, system efficiency and other indicators to determine the actual mean-time-
to-failure or loss of efficiency for each machine-train and system in the plant. This data provides
maintenance management the factual data needed for effective planning and scheduling
maintenance activities.
Predictive maintenance is much more. It is the means of improving productivity, product quality
and overall effectiveness of our manufacturing and production plants. Predictive maintenance is
not vibration monitoring or thermal imaging or lubricating oil analysis or any of the other
nondestructive testing techniques that are being marketed as predictive maintenance tools.
Rather, it is a philosophy or attitude that simply stated uses the actual operating condition of
plant equipment and systems to optimize total plant operation. A comprehensive predictive
maintenance management program utilizes a combination of the most cost-effective tools, i.e.
thermal imaging, vibration monitoring, tribology and other nondestructive testing methods, to
obtain the actual operating condition of critical plant systems and based on this factual data
schedules all maintenance activities on an as-needed basis.
Including predictive maintenance in a comprehensive maintenance management program will
provide the ability to optimize the availability of process machinery and greatly reduce the cost
of maintenance. It will also provide the means to improve product quality, productivity and
profitability.
A predictive maintenance program can minimize unscheduled breakdowns of all electrical and
mechanical equipment in the plant and ensure that repaired equipment is inacceptable condition.
The program can also identify problems before they become serious. Most problems can be
minimized if they are detected and repaired early. Normal mechanical failure modes degrade at a
speed directly proportional to their severity. If the problem is detected early, major repairs can
be prevented, in most instances (5), (6).
Benefits (4)
Effective use of preventive maintenance, including predictive technologies, will eliminate much
of the 33 % to 50 % of maintenance expenditures that are wasted by most manufacturing and
production plants. Based on historical data in the USA, the initial savings generated by effective
preventive/predictive maintenance programs fall into the following areas:
1. Elimination of unscheduled downtime caused by equipment or system failures. Typically,
reductions of 40 % to 60 % are achieved within the first two years and up to 90 % reductions
have been achieved and sustained within five years.
2. Increased manpower utilization. Statistically, the average “wrench-time” of a maintenance
craftsperson is 24.5 % or about 2 hours per shift. By identifying the precise repair task needed to
correct deficiencies within a plant asset, as well as the parts, tools and support needed to rectify
the problem, preventive/predictive maintenance can dramatically increase effective “wrench-
time”. Most plants have been able to achieve and sustain 75 % to 85 % effective utilization.
3. Increased capacity. The primary benefit of effective preventive/predictive maintenance
programs is an increase in the throughput or production capacity of the plant. Short-term, i.e. 1-
to-3 years, increases in sustainable capacity have ranged between 15 % and 40 %. Long-term
improvements of 75 % to 80 % have been achieved.
4. Reduction of maintenance expenditures. In some cases, actual maintenance expenditures will
increase during the first year following implementation of an effective preventive/ predictive
program. This increase, typically 10 % to 15 %, is caused by the inherent reliability problems
discovered by the use of predictive technologies. When these problems are eliminated, the
typical result is a reduction in labor and material cost of between 35 % and 60 %.
5. Increased useful life. Typically, the useful operating life of plant assets will be extended by 33
% to 60 %. Detecting incipient problems or deviations from optimum operating conditions
before damage to equipment occurs derives this benefit. Making minor adjustments or repairs
and not permitting a minor deficiency from becoming a serious problem can extend the effective
useful life extended almost indefinitely.
Predictive maintenance, on the other hand, determines when the machine REQUIRES repair.
Plant machinery is therefore only repaired WHEN REQUIRED. The benefits of predictive
maintenance can be separated into two main categories.
INCREASED SAFETY: Predictive maintenance provides the reassurance of safe, continued
plant operation. By reducing the likelihood of unexpected equipment breakdown, the safety of
employees is improved. Although difficult to quantify, there is a definite economic benefit in
improved employee and union relationships.
IMPROVED OPERATING EFFICIENCY: There are many areas in which a predictive
maintenance program can increase the efficiency of your process. Please see chart below.
(SACHS, Neville W., Predictive Maintenance Cuts Costs)
Predictive maintenance requirements (4)
Predictive maintenance is mainly based on the study of the variations of the system status in
terms of pertinent information or data materializing the degradation and the drift behavior of the
system.
The dynamic of degradation describes its past, present and future values, as a control variable, to
represent the degradation through time (Figure 2). This representation is required to implement
function linked to the predictive maintenance objectives.
In this way, predictive maintenance has to control degradation by acting on the degraded system
to realise a nominal or a degraded function. This action allows applying resumption, emergency
procedure, reconfiguration, key locking, redundant functioning…
So, the concept of predictive maintenance is closed to control theory, but by considering that the
predictive maintenance goal is to monitor, diagnose, and prognosticate online the degradation of
manufacturing system to compensate, correct or operate just in time.
To act on the degraded manufacturing system, the predictive maintenance must authorize actions
only in total coherence with the manufacturing system behavior in order to be sure that these
actions allow retrieving a normal state from an abnormal one in safety conditions.
Predictive maintenance on the production line (7)
Nowadays maintenance is considered as a key point for the manufacturing system
competitiveness because first its cost represents the major part of the operational cost, and
second, a system failure can have an important impact on product quality, equipment availability,
environment, and operator.
The two reasons for stopping a production line are due to regularly scheduled maintenance or
equipment failure. Performing timely maintenance is critical to preventing failures that may
result in costly production interruptions, but relying on a fixed schedule may result in higher than
necessary costs for both parts and labor. Predictive maintenance leverages the rich set of data
those manufacturers already have available, such as equipment type, number of days in
operation, operating voltage, days from last service, days to next service, failure history, costs for
planned and unplanned maintenance, parts analysis and other data depending upon the
machinery involved.
A fully automated process analyzes this data in real time. It quickly detects failure patterns and
identifies the root cause of the problem. Because engineers have 24/7 access to the reliability of
every piece of equipment, they can evaluate the current status of every asset and build a
maintenance schedule that performs inspections and/or maintenance just in time to prevent
failures. This eliminates the need for shutting down a line simply to perform “regularly
scheduled maintenance” that may not be really necessary.
As operating conditions change, the reliability of every piece of equipment is updated in real
time. The advanced algorithms contained in the predictive maintenance software can determine
the reliability of every asset at any point in the future, so that inspections and maintenance can be
performed at the optimal and most cost-effective moment. Predictive maintenance also identifies
the replacement parts required to support this highly accurate maintenance schedule. It
eliminates the need for unnecessary and expensive overstocking of spare parts.
Using predictive maintenance, the manufacturer can determine if certain production runs fail
more often than others. They conduct a root cause analysis to determine the problem’s source,
and then analyze the financial implications of the failure to determine whether those runs warrant
a recall or just a service bulletin to their distributors. Their analysis also shows where the failures
will occur and what the demand in a given region will be for the replacement parts. They can
then ensure that the correct supply of replacement parts can be available at the appropriate time.
Reducing warranty claims (7)
As a result, the company avoids many costly warranty claims by providing the resolution to its
service channel even before most customers know a problem exists.
In many situations like this, predictive maintenance can identify when equipment in the field is
likely to fail or need maintenance in order to predict future warranty claims costs and maximize
uptime/in-service time for equipment sold to customers or for equipment used to deliver service.
This helps manufacturers avoid high services costs and product recalls due to late product issue
identification. It also minimizes or eliminates bad publicity and the resulting lost sales from
recalls or negative customer product reviews.
Advantages and Disadvantages of Predictive Maintenance
Predictive maintenance is a more condition-based approach to maintenance. The approach is
based on measuring of the equipment condition in order to assess whether equipment will fail
during some future period, and then taking action to avoid the consequences of that failures. This
is where predictive technologies (i.e. vibration analysis, infrared thermographs, ultrasonic
detection, etc.) are utilized to determine the condition of equipment, and to decide on any
necessary repairs. This approach is more economically feasible strategy as labors, materials and
production schedules are used much more efficiently.
Advantages of Predictive Maintenance
Provides increased component operational life and availability.
Results in decrease in equipment and/or process downtime.
Lowers costs for parts and labor.
Provides better product quality.
Improves worker and environmental safety
Raises worker morale.
Increases energy savings.
Increased component operational life/availability
Allows for preemptive corrective actions
Decrease in equipment or process downtime
Better product quality
Improved worker and environmental safety
Improved worker morale
Energy savings.
Estimated 8% to 12% cost savings over preventive maintenance programme
Disadvantages of Predictive Maintenance
Increases investment in diagnostic equipment.
Increases investment in staff training.
Savings potential is readily seen by management.
Developing a predictive maintenance application
While each company is different, a typical approach to developing a predictive maintenance
application can be found below:
1. Identify the problem by focusing on failures of specific asset types or specific events.
2. Notice as many data sources (e.g. asset information, maintenance history, inspection reports,
RFIDs) as possible.
3. Integrate all data sources, such as combining “fixed” attributes (e.g. asset type) and “dynamic”
attributes (e.g. temperature).
4. Derive any additional fields to help with modeling, such as creating a “1” or “0” to signify if
a part failed or not or calculating average cost per part, in addition to existing data of total cost
and number of parts.
5. Identify the best predictors of failure.
6. Evaluate resultant models for modeling accuracy and quick logic test based on your own
experiences.
7. Focus on the most effective methods of deployment within your organization (e.g. asset
management, workforce management systems, business intelligence).
8. Create an information and response feedback loop to maintain accuracy and make continual
improvements.
9. Monitor and track progress.
Conclusion
As manufacturers face increasing pressures to control costs and improve productivity, preventive
maintenance has emerged as an essential capability. Supported by predictive analytics, predictive
maintenance prevents production interruptions, improves usability and service levels for
customers and helps to reduce warranty costs. It empowers manufacturers to isolate and solve
maintenance and operational issues before they become significant and expensive problems. For
manufacturers that need to achieve the highest levels of uptime and minimize the expense and
labor of downtime, it’s a game-changing technology.
Artificially high maintenance costs caused by a combination of ineffective management methods
and the lack of timely, factual knowledge of asset condition represent a substantial opportunity
for almost every manufacturing and production facility worldwide. Effective use of the
preventive/predictive technologies provides the means to take advantage of this opportunity.
Used correctly, the 33 % to 50 % of wasted maintenance expenditures can be eliminated and
effective use of plant resources; both production and maintenance can be achieved and sustained.
Acknowledgment:
I want to thank our professor CEVDET MERIC for helping and supporting us in this course and
give us the chance to prepare this project.
References
1) Lindley R. Higgins, Dale P. Brautigam, and R. Keith Mobley, Maintenance Engineering
Handbook, McGraw Hill Text, 5th Edition, September 1994
2) Joseph D. Patton, Jr. Maintainability and Maintenance Management, Instrument Society
of America, 3rd Revision, February 1994
3) John Moubray, Reliability-Centered Maintenance, Industrial Press, 2nd Edition, April
1997
4) J-b. Leger, E. Neunreuther, B. Iung, G. Morel, cran-gsip Nancy Research Centre of
Automatic Control. “Integration of the Predictive Maintenance in Manufacturing
System”, 2010
5) Mobley K, Introduction to Predictive Maintenance. Van Nostrand Reinhold, New York,
1989
6) Mobley K, Predictive Maintenance Handbook , 1998
7) ibm.com/software/analytics/industrial-products. Predictive Maintenance for
Manufacturing How to improve productivity, minimize downtime and reduce costs.2011
8) Moinuddin Madki, Workshop on: Predictive & Preventive Maintenance Basics &
Practices. 19 – 20, September 2011
9) NASA. Reliability Centered Maintenance Guide for Facilities and Collateral
Equipment. National Aeronautics and Space Administration, Washington, D.C. 2000
10) SACHS, Neville W., Predictive Maintenance Cuts Costs , Power Transmission Design ,
November 1986.