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Historical Overview of Maintenance Management Strategies: Development from Breakdown Maintenance to Predictive Maintenance in Accordance with Four Industrial Revolutions

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Every industrial revolution causes changes in technological, socioeconomic and cultural features. Among the technological features belongs also maintenance management. The approach towards equipment maintenance has changed throughout the revolutions from reactive towards predictive. Instead of fixing breakdowns, companies try to predict them and minimalize the risks and costs associated with it. The main objective of this article is to put the changes in maintenance management strategies in the context of industrial revolutions. Throughout a literature review, the article summarizes the characteristics of each industrial revolution and maintenance management approach together with paradigm shifts that accompanied them. Namely the relation of the first industrial revolution with breakdown maintenance, the second industrial revolution with preventive maintenance, the third industrial revolution with preventive maintenance and finally the fourth industrial revolution with predictive maintenance.
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Proceedings of the International Conference on Industrial Engineering and Operations Management
Pilsen, Czech Republic, July 23-26, 2019
© IEOM Society International
Historical Overview of Maintenance Management
Strategies: Development from Breakdown Maintenance to
Predictive Maintenance in Accordance with Four Industrial
Revolutions
Peter Poór, David Ženíšek, Josef Basl
Department of Industrial Engineering and Management
University of West Bohemia
Univerzitní 8, 306 14 Pilsen, Czech Republic
poorpeter@gmail.com, zenisekd@kpv.zcu.cz, basljo@kpv.zcu.cz
Abstract
Every industrial revolution causes changes in technological, socioeconomic and cultural features. Among the
technological features belongs also maintenance management. The approach towards equipment maintenance has
changed throughout the revolutions from reactive towards predictive. Instead of fixing breakdowns, companies try to
predict them and minimalize the risks and costs associated with it.
The main objective of this article is to put the changes in maintenance management strategies in the context of
industrial revolutions. Throughout a literature review, the article summarizes the characteristics of each industrial
revolution and maintenance management approach together with paradigm shifts that accompanied them. Namely the
relation of the first industrial revolution with breakdown maintenance, the second industrial revolution with preventive
maintenance, the third industrial revolution with preventive maintenance and finally the fourth industrial revolution
with predictive maintenance.
Keywords
Maintenance management strategy, Industrial revolution, Industry 4.0, predictive maintenance
1. Introduction to maintenance
Production machines, equipment and devices will always be liable to wear and the requirement for maintenance.
Alongside the advancement of industry goes the improvement of maintenance. As far back as the mankind began
making devices that fulfilled their requirements there was the requirement for maintenance. Records of maintenance
can be found already in the ancient Egypt. An old Egyptian document, dated 600 b.c. mentions a stoppage of supply
of cedar wood required for the maintenance of sacred boat of Amun Ra. (Brugsch-Bey, H. 1881)
The approach towards maintenance has changed throughout the years. It has been transformed from reactive
(corrective) actions to ongoing predictive activities with an aim to optimize the time, costs and quality. While
nowadays it could be foreseen as a competitive advantage or area, whose improvement may increase profit and
bring many benefits, some still consider maintenance as the “necessary evil”. In this paper, we identified four key
maintenance concepts that correspond to the industrial revolutions.
Nowadays the maintenance management aims to decrease both the unscheduled downtime and scheduled downtime,
which both reduce the available time, in combination with optimization of safety, environmental risks and costs.
Available time, production quality and performance are the basic key performance indicators (KPI), which
combined give the overall equipment effectiveness (OEE) (Legát et al. 2007).
Literature gives many definitions of maintenance. Swedish standard SS-EN 13306 characterize it as a “Combination
of all technical, administrative and managerial actions during the life cycle of an item intended to retain it in, or restore
it to, a state in which it can perform the required function” (API STD 689 2007 ).
Maintenance management covers all actions including inspection, adjustments, cleaning, lubrication, testing, and
replacement of expendable parts, as necessary to maintain the serviceability of the equipment (API RP 8B 2012).
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Simeu-Abazi and Sassine state, that “the main purpose of maintenance engineering is to reduce the adverse effects of
breakdown and to increase the availability at a lower cost, in order to increase performance and improve the
dependability level”(Simeu-Abazi, Z. and Sassine, C. 2001).
Gits (Gits, C.W., 1994)considers modern maintenance as a procedure that is needed by production processes; it is
the essential procedure where the input is changed in output and maintenance is an auxiliary procedure that causes the
first to the accomplishment of production.
According to Bagadia,(Bagadia, 2006) maintenance implies all measures that assist to save and re-make the required
condition of machinery and equipment. They lead to identification and assessment of genuine condition of specialized
establishments overall and the consequent technical measures to reestablish every of its capacities in the required
quality.
ISO defines maintenance as set of activities performed during the operating life of a structure to ensure it is fit-for-
purpose (ISO 19901-7:2013).
2. Maintenance management parallel to the industrial revolutions
The term Industrial Revolution was first popularized by English economic historian Arnold Toynbee to describe
Britain’s economic growth from 1760 to 1840. Since that, the term has grown on its popularity. Industry revolution is
defined as “the comparatively sudden and violent change which launches the industrialized society into being,
transforming that society in a way which none of the earlier so-called industrial revolutions ever did” (Coleman, D.
C. 1956). The impact of the Industrial revolution concerns technological, socioeconomic and cultural features. Among
the impacted technological features belongs also maintenance (Calvert, P. 1970).
1.1. Industry 1.0 and Reactive Maintenance
The first industrial revolution is an idea everybody knows as the main industrial revolution and is now taught at
schools. It could be compared with the Neolithic Revolution which caused the society to shift from hunters and
collectors to agriculture. It was a giant leap towards today's form of society. It started in England and was characterized
as a change in the use of energy sources, forms of transport, information transfer and industrialization of production.
It was also a crucial period of social, cultural and political changes in individual countries. The symbol of the first
industrial revolution was a steam engine invented by James Watt in 1765 (Spear, B. 2008).
Since the start of the first industrial revolution, there has been a massive increase in labor productivity through the
introduction of new ways in agriculture the introduction of machinery and alternate field cultivation. All this led to
the industrialization of the countries the transformation from the agrarian country into a industrial one (Volek, T.,
& Novotna, M. 2017).
The revolution hugely affected society (Maciej Dzikuć, Janusz Adamczyk, Arkadiusz Piwowar 2017). The population
of England has doubled while the mortality reduced, thanks to the improvement of hygiene, less hunger and improved
medical care. Urbanization took place, large urban industrial centres with factories with high chimneys, new roads,
railroads, bridges emerged and attracted people from rural areas. At that point in time, Manchester, Liverpool,
Birmingham and Glasgow became the most advanced cities.
The most characteristic maintenance form during this period was the breakdown maintenance (also known as “reactive
maintenance” or “corrective maintenance”). Break down maintenance is a form of maintenance, where repairs are
done only after the breakdown. The aim of it is to put the broken machine back to the regular operational conditions.
The breakdown maintenance has its pros and cons. As pros we could list the fact, that it takes less time and money to
do nothing than it does to do something, there is no initial cost, and it requires far less planning. On the other hand,
the unpredictable nature of breakdowns leads to shorter asset life, safety issues, inefficient use of time, and can get a
lot more expensive. (Christer, A. H., & Whitelaw, J. 1983).
The strategy of "letting the device work until it goes wrong" was the first that humankind naturally applied. On first
sight it is the easiest and natural way of maintenance. Machines were rather simple and therefore there was no need
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for a specialist that would know how to repair it, at the beginning. Even nowadays, reactive maintenance is the most
widely used maintenance activity (over 55% according to Bloch and Geitner). Never the less with the increasing
complexity of machines, especially after the beginning of the first industrial revolution a new trend started appearing
among the industries. (Bloch, H. P., & Geitner, F. K. 1997).
1.2. Industry 2.0 and Preventive Maintenance
The Second Industrial Revolution began about one hundred years later in 1870 and was connected to electrification
and assembly lines. It resulted in mass production based on division work and electrically powered lines. In 1870 the
first large scale assembly line was built up in a slaughterhouse in Cincinnati. Later, the assembly line idea was adopted
by Henry Ford for his Model T automobiles factories. Another extraordinary innovation was the light bulb by T. A.
Edison in 1879 and transformer, designed by Nicole Tesla (Jonnes, J. 2004).
Work organization was improved by Frederick Taylor, who came up with ways to boost factory profitability up by to
a hundred times. His principles of work organization aimed for precise determination of the work process and
performance-based wage (Nof, S. Y., Wilhelm, W. E., & Warnecke, H. J. 1997). Other inventions of the second
industrial revolution were e.g. dynamite, phone, aircraft and many others. All these inventions and principles are being
used till today.
Due to these new inventions, the way of life has changed. Science was suddenly connected to the technology, research
results from natural sciences were being applied in industry. This led to the creation of new materials that replaced
the natural manmade fertilizes, dyes and therapeutic substances. After the invention of the combustion engine,
diesel started to be applied and electric motors were produced. Electricity was used to illuminate cities, run trams and
to enable communication via telephone.
Sometimes the Second Industrial Revolution is known as the Revolution of the Technical Science. Darwin came with
his evolutionary theory. In the material sciences, Newton came up with mechanical origination of nature. Discovery
of the microscope made possible to find what one doesn't see with his bare eye. X-rays and radioactivity were found.
Max Planck presented quantum theory and Albert Einstein his theory of relativity. Sigmund Freud investigated human
personality through the hypothesis of unconsciousness, so-called psychoanalysis (Henderson, W. O. 2013).
The supply of goods began to grow, on the contrary demand fell. Free capital was created, which was necessary for
export. States have exported capital to their industrial-building colonies, which on the contrary delivered cheap labour.
With this, a struggle began between the Great Powers and the Territorial Colonies, which led to the start of the First
World War (Dewey, D. 1959).
With the peak of the second industrial revolution the machines became more complex and production grew rapidly.
Breakdowns caused higher and higher expenses and therefore first attempts of preventive maintenance (also known
as planned maintenance) appeared. Even Henry Ford recommended preventive maintenance in his FORD MANUAL
from 1919. (Ford Motor Company 1919) Frequently inspect the running gear. See that no unnecessary play exists in
either front or rear wheels and that all bolts and nuts are tight. Make a practice of taking care of every repair or
adjustment as soon as its necessity is discovered. This attention requires but little time and may avoid delay or possible
accident on the road.”
Preventive maintenance can be characterized as: Action based on a specific timetable that identifies, avoids or
mitigates the decay of component or framework state so in order to maintain or expand its life by means of controlled
corruption to an adequate level (Butler, K. L. 1996). There are two essential kinds of preventive maintenance -
maintenance in periodic cycles or maintenance dependent on equipment status. Maintenance in periodic cycles
anyway seems to be unreasonably costly for about 92% of machine parts. Device-based (proactive) maintenance
exchanges parts and interferes with the machine only when deviations begin to show up in its procedure, making it
more efficient (Kurkin, O., Kleinová, J., Čechura, T., & Broum, T. 2011).
Preventive maintenance brings less likelihood of breakdowns, fewer downtimes and might be more savvy than
reactive. Then again, it builds costs with customary substitutions, there is a requirement for extra parts and planned
downtime increases (Poór, P., Šimon, M., & Karková, M. 2016).
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As indicated by Bloch and Geitner, (Bloch, H. P., and Geitner, F. K. 1997) by simply spending the necessary resources
to carry out the maintenance activities of the designer, the facility's life is extended, and its reliability is increased. In
addition to increase reliability, savings are also being made. This savings can be up to 12% on average to 18% of
saved costs.
Depending on the current state of maintenance, device reliability and downtimes, many companies dependent on
purely reactive maintenance can save much more than 18% by starting the right preventive maintenance program.
Although preventive maintenance is not an optimal machine maintenance program, it has several advantages over
purely reactive maintenance (Straka et al. 2016). Performing preventive maintenance on the device as designed by the
designer will prolong the life of the device. This means saving money. Preventive maintenance (lubrication, filter
replacement, etc.) will usually result in higher device efficiency, which will be reflected in savings. Even if we do not
prevent the catastrophic scenario, the number of disorders will go down.
1.3. Industry 3.0 and Proactive maintenance
With the Third Industrial Revolution, most people have personal experience, whether good or bad. The length of this
industrial revolution is the shortest this time, only about a forty-year period from about the end of the Second World
War to the late 1980s. The beginning of this revolution dates back to not much of a milestone in human history, the
drop of atomic bombs on the Japanese cities of Hiroshima and Nagasaki in August 1945. The use of technology
controlled thermonuclear reaction of atomic bombs started a third industrial revolution. Its termination dates back to
the early 1990s, by the time of the decentralized merger of thousands, then by millions of people through the Internet
using personal computers and mobile phones (Metodická příručka "Člověk a stroj").
The beginning of the Third Industrial Revolution goes back to 1969, when the first programmable logic controller,
e.g. PLC, was made (Jensen, M. C. 1993). It is a small industrial computer, a control unit, for real-time automation of
processes. For PLC it is characteristic that the program is performed in so-called cycles. The key characteristics of
this period were automation, the boom in electronics and information technology. These features were subsequently
introduced into production in order to drive machines and automate them (Rosenberg, N. 1963).
The third industrial revolution is most often associated with automation, electronics and the expansion of information
technology. Just as the transition from coal and steam to electricity was relatively continuous and logical, the transition
from mechanics to automation was more a result of natural evolution than a real revolution.
The Third Industrial Revolution is often referred to as a period of scientific and technological revolution and, as has
already been said, the arrival of computers. Its content is the cross-penetration of scientific and technological
development into the production process, which leads to innovations up to fourth level (M. Toms 1981) fundamental
changes in technology and technology on the basis of new discoveries in automation and cybernetics, energy, research
into the atomic and molecular structure of matter in biology, genetics, cosmology (Martin Fassmann 2016) Reactions
to fundamental transformations in the productive forces are adequate shifts in marketing and management processes
(Peter F. Drucker 1985) especially in the onset of automated control systems not only of production lines, but also of
transport and complex machinery and equipment. All this is dramatically reflected in the labour market.
Productive Maintenance (also referred to as PM) started appearing after the second world war. This new approach
towards maintenance combines Corrective Maintenance and Preventive Maintenance with a data-driven, analytical
approach, and is performed to increase the broadly economic efficiency of production (Aziz, Iftekhar, Sazedul Karim,
and M. Hossain 2012). It strives to identify and address the problems that can lead to breakdowns in the first place,
such as improper machinery lubrication, misalignment, contamination and other suboptimal conditions.
Productive maintenance brings longer lifespan of equipment, decreased downtime (both planned and unplanned),
lower spare parts inventory and is more cost-effective. The big challenge, however is, that it requires, unlike previous
maintenance approaches, a large shift of paradigms and organizational changes. Maintenance is integrated into the
company strategy and is recognized as improvement worthy. Data starts being collected and, in some cases, real-time
monitoring is enabled. Statistical models are applied and new discoveries concerning fatigue are made.
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Perhaps the two best-known methods which developed during the period of the third industrial revolution were Total
Productive Maintenance (TPM) with origin in Japan and Reliability Centered Maintenance (RCM) with origin in the
USA. Let's take a brief look at them.
1.3.1. Reliability Centered Maintenance
Reliability-based maintenance is "a procedure to establish maintenance requirements for any physical asset in its
operational context." (Moubray, J. 1997) It guarantees that systems keep on doing what their user requires in their
present working setting. The reliability-oriented maintenance strategy addresses fundamental issues not secured by
other maintenance programs. Perceives that not all machinery in a company has a similar significance that the
construction and operation of the equipment are different, and that is more likely to cause a fault for various reasons.
It also considers the way that the company does not have a boundless budget and personal assets and should be
optimized.
The RCM technique screens the activity of every component and characterizes the outcomes of its failures. The RCM
makes a structure of outcomes in decreasing order of severity of individual disorders, to do this, it uses a FMEA
analysis. While deciding the outcomes, every one of the activities of the elements of the monitored device must be
determined (Šimon, M., & Broum, T. 2018). If the level of risk due to failure cannot be can't be decreased by the
chosen maintenance mode, then it is necessary to reconstruct the element. Thus, RCM also deals with the assessment
of possible causes of device failures (eg. neglected maintenance, wear, etc.).
RCM prompts an expansion in cost-effectiveness, reliability, machine uptime, and a greater comprehension of the
dimension of risk. It is characterized by the specialized standard SAE JA1011 (JA1011, S. A. E. 1999).
1.3.2. Total Productive Maintenance (TPM)
TPM was presented by Seichi Nakajima, who during the 60s studied Preventive Maintenance systems in the US and
Europe. He worked out his knowledge in a complex system that was given a working name Total Productive
Maintenance. In 1971, he brought the framework into Japanese organizations (Nakajima, S. 1988).
T as Total - participation of all organization employees.
P as Productive - efficiency of maintenance and production equipment, constantly improving.
M as Maintenance - of machinery and equipment in good technical condition.
Total productive maintenance is equipped to connecting all staff in the workshop to exercises that minimize downtime,
limit accidents and occurrences. The TPM is about beating the conventional division of people into workers working
on the machine, and "workers who fix it". It depends on the way that the worker who deals with the machine gets the
opportunity to initially catch the anomalies in his work and sources of future equipment failure. Motto of TPM is:
"Protect your machine and take care of it with your own hands." (Legat, V. 2013) Thus, the greatest diagnostic and
maintenance activities in TPM are exchanged from the traditional support straightforwardly to the production workers
- the production sections (Petr Baron et al.). It usually starts with enhancing the work environment, cleaning machines
and checking their condition (Broum, T., & Kleinová, J. 2018) Besides, the operator figures out how to "understand
his machine", to figure out how to carry on as his "very own". Notwithstanding maintainers and operators, different
professions, for example, technical preparation of production are involved in TPM (Ahmed, S., Hj. Hassan, M., &
Taha, Z. 2005).
The move in thinking must be done mainly in optimizing (Orosz T., 2017) the "man-machine" relationship, where the
operator performs not just the job, but additionally the job of active maintenance co-worker (Poór, P., Kamaryt, T., &
Simon, M. 2015). It is significant that the whole framework is secured by dynamic management support for TPM
implementation projects and the collaboration of technical staff throughout the organization (Waeyenbergh, G., &
Pintelon, L. 2002). It is an enterprise-wide system k that incorporates preventive maintenance. The TPM depends on
the help of item maintenance by little gathering activities (production groups). The TPM is applicable wherever where
production (operation, equipment) is based on technological service (operators). TPM objectives are (Islam, S. 2011):
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- zero downtime,
- zero errors,
- zero disturbances (Baluch, N. H., Abdullah, C. S., & Mohtar, S. 2012).
The premise of the TPM theory is, from one viewpoint, to expand the effectiveness of machinery and to decrease
maintenance expenses and misfortunes because of downtimes, then again, based on great correspondence between the
operator and the maintainer.
1.4. Industry 4.0 and Predictive Maintenance
Curiously, the first three industrial revolutions happened first and, afterwards they have been named. With the Fourth
industrial revolution, it's not the same case. The revolution is still happening, and we already realized it (Hořánek, V.
Basl J.: 2018). The changes are happening faster due to the interconnection of the world.
The following period of the Industrial Revolution is the development of the Internet. The Internet has basically existed
since 1962, yet in 1987 the expression "Web" was made. Its commercialization occurred just in the year 1994. From
that point on, it very well may be said that the Internet enters into all regions of human action. Since the late 1990s
there has been a gigantic increment in Internet clients, which presently comes to around billions (Smith, B. L. 2001).
1.5. Predictive Maintenance
Predictive maintenance (nowadays also called PdM 4.0) is now the highest form of maintenance as of today. It is a
method of preventing asset failure by analyzing production data to identify patterns and predict issues before they
happen (Kmec, Valenčík, Gombár, Karková, Vagaská 2016). The key to this is a combination of big data analytics
and artificial intelligence in order to create insights and detect patterns and anomalies. It includes continuous real-
time monitoring of assets in combination with external data (e.g. environmental data, usage, etc.) with alerts based on
predictive techniques such as regression analysis, for at least one important asset (Orosz et al., 2015).
The basic components of predictive maintenance in the context of industry 4.0 are: Sensors, Cyber-Physical
Systems, Internet of Things, Big Data, Cloud computing, Networks and Artificial Intelligence, Mobile networks,
WIFI. Also, the job titles involved in Maintenance changed. Instead of experienced craftsmen and drained
inspectors, businesses must employ reliability engineers and data scientists (Mihalov, Pietrikova, Balaz, Mados,
Adam 2018). The data used for predictive maintenance are growing in count, as the companies collect data about the
condition of assets, usage of assets, maintenance history, data from other assets that are relative to the work of
monitored machine, both from inside and outside of the company (e.g. assets of our suppliers), environmental data
and others.
Some of the key critical success factors for the predictive maintenance implementation are budget, culture,
technological solutions, availability of data, data security and others. A well-functioning predictive maintenance
program can mean savings of 8% to 12%. Depending on the equipment and material conditions, it is possible to save
30% to 40% (US Department of energy 2010).
The following savings resulting from the use of predictive maintenance are:
• Return on investment: 10 times
• Reduction of maintenance costs: 25% to 30%
• Troubleshooting: 70% to 75%
• Reduction of downtime: 35% to 45%
• Increased production: 20% to 25% (Bloch, H. P., and Geitner, F. K. 1997).
But the start of predictive maintenance is not cheap. A large part of the equipment requires a cost of more than €
30,000. Staff training also requires additional funding.
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Table 1. Correlation of Industrial Revolution and Maintenance (Coleman, Damodaran, Chandramouli, Deuel, 2017)
Industry
revolution
Industry 1.0
Industry 2.0
Industry 3.0
Industry 4.0
Characteristics of
the industrial
revolution
Mechanization,
steam power,
weaving loom
Mass production,
assembly lines,
electrical energy
Automation,
computers,
electronics
Cyber Physical
Systems, IoT,
networks, cloud,
BDA
Type of
maintenance
Reactive
maintenance
Planned
maintenance
Productive
maintenance
Predictive
maintenance
Inspection
Visual inspection
Instrumental
inspection
Sensor monitoring
Predictive analysis
OEE
<50%
50-75%
75-90%
>90%
Maintenance team
reinforcement
Trained craftsmen
Inspectors
Reliability
engineers
Data scientists
3. Conclusion
Based on the presented facts, we can clearly see a correlation between the industrial revolutions and machinery
maintenance. From the earliest ones (corrective maintenance), during times of first industrial revolution and
introduction of steam machines, through planned maintenance during the era of Ford automobile cars. Here, Henry
Ford recommended preventive maintenance in his FORD MANUAL to his customers. With the 3rd generation of
industrial revolution automation and computerization are the main phenomena. This has resulted in the use of
productive maintenance Total Productive Maintenance or Reliability Centered Maintenance, with the great help of
beginning automation and computerization. Concept of relatively new Industry 4.0 fully used the advantage of cyber
systems, cloud storage or Internet of Things resulting in the most advanced form of maintenance “Predictive
Maintenance”. As seen in the table at the end of the article, there is also an inverse correlation between the level of
Maintenance and its “factor” OEE. The more developed maintenance, the higher the Overall Effectivity of Equipment
is. This “model” is only the beginning of our research and we will continue to develop this topic of Predictive
Maintenance and its place in Industry 4.0.
Acknowledgements
This research has been supported by the Technology Agency of the Czech Republic under the project Software
platform to accelerate the implementation of management systems and process automation project No.
TH02010577.
References
Ahmed, S., Hj. Hassan, M., & Taha, Z. (2005). TPM can go beyond maintenance: excerpt from a case implementation.
Journal of Quality in Maintenance Engineering, 11(1), 19-42
API RP 8B, Recommended Practice for Procedures for Inspections, Maintenance, Repair and Remanufacture of
Hoisting Equipment, Seventh Edition, March 2002 (Reaffirmed: August 2012
API STD 689, Collection and Exchange of Reliability and Maintenance Data for Equipment, First Edition, July 2007
Aziz, Iftekhar, Sazedul Karim, and M. Hossain. "Effective implementation of total productive maintenance and
impacts on breakdown time and repair & maintenancea case study of a printing industry in Bangladesh."
Proceedings of the Global Engineering, Science and Technology Conference. 2012.
Baluch, N. H., Abdullah, C. S., & Mohtar, S. (2012). TPM and LEAN Maintenance-a critical review. Interdisciplinary
Journal of Contemporary Research in Business (IJCRB)
Bagadia, Kishan: Computerized maintenance management systems made easy: how to evaluate, select, and manage
CMMS. McGraw-Hill Professional, 2006. ISBN 0071469850, 9780071469852
501
Proceedings of the International Conference on Industrial Engineering and Operations Management
Pilsen, Czech Republic, July 23-26, 2019
© IEOM Society International
Baluch, N. H., Abdullah, C. S., & Mohtar, S. (2012). TPM and LEAN Maintenance-a critical review. Interdisciplinary
Journal of Contemporary Research in Business (IJCRB)
Baron Petr et al.: Research and application of methods of technical diagnostics for the verification of the design node
- 2016. In: Measurement. Vol. 94 (2016), p. 245-253. - ISSN 0263-2241
Bloch, H. P., & Geitner, F. K. (1997). Major process equipment maintenance and repair (Vol. 4). Elsevier
Broum, T., & Kleinová, J. (2018). The cumulative functions concept. Paper presented at the Annals of DAAAM and
Proceedings of the International DAAAM Symposium, 29(1) 0306-0311. doi:
10.2507/29th.daaam.proceedings.044
Brugsch-Bey, H. (1881). A History of Egypt under the Pharaohs. Edited by Philip Smith. London.]
Butler, K. L. (1996, January). An expert system-based framework for an incipient failure detection and predictive
maintenance system. In Intelligent Systems Applications to Power Systems, 1996. Proceedings, ISAP'96.,
International Conference on (pp. 321-326). IEEE
Chris Coleman, Satish Damodaran, Mahesh Chandramouli, Ed Deuel, "Making maintenance smarter-Predictive
maintenance and the digital supply network", May 09, 2017, Deloitte University Press,
https://www2.deloitte.com/insights/us/en/focus/industry-4-0/usingpredictive-technologies-for-asset-
maintenance.html
Christer, A. H., & Whitelaw, J. (1983). An operational research approach to breakdown maintenance: problem
recognition. Journal of the Operational Research Society, 34(11), 1041-1052
Coleman, D. C. (1956). Industrial growth and industrial revolutions. Economica, 23(89), 1-22.
Dewey, D. (1959). Monopoly in economics and law (pp. 7-24). Chicago: Rand McNally
Drucker Peter F.: Inovace a podnikavost. Praxe a principy. MANAGEMENT PRESS. Praha 1985. ISBN 80-85603-
29-2
Dzikuć Maciej, Adamczyk Janusz , Piwowar Arkadiusz (2017). Problems associated with the emissions limitations
from road transport in the Lubuskie Province (Poland), Atmospheric Environment, 160: 1-8.
Doi.org/10.1016/j.atmosenv.2017.04.011
Ford Motor Company (1919): Ford Manual for Owners and Operators of Ford Cars and Trucks Detroit: Ford Motor
Company
Gits, C.W., (1994), “Structuring Maintenance Control Systems”, International Journal of Operations & Production
Management, Vol. 14, No. 7
Henderson, W. O. (2013). Industrial Revolution on the Continent: Germany, France, Russia 1800-1914. Routledge
HOŘÁNEK V., BASL J.: Overview and Comparison of Tools for Assessing the Readiness of Companies for Industry
4.0, In: the 32nd International Business Information Management Association Conference. Khalid S. Soliman,
2018. p. 1797 1807
ISO 19901-7:2013, Petroleum and natural gas industries Specific requirements for offshore structures Part 7:
Stationkeeping systems for floating offshore structures and mobile offshore units
Islam, S. (2011). Improvement of overall equipment efficiency (OEE) by total productive maintenance (TPM)-a case
study.
JA1011, S. A. E. (1999). Evaluation criteria for reliability-centered maintenance (RCM) processes. Society for
Automotive Engineers.
Jensen, M. C. (1993). The modern industrial revolution, exit, and the failure of internal control systems. the Journal
of Finance, 48(3), 831-880
Jonnes, J. (2004). Empires of light: Edison, Tesla, Westinghouse, and the race to electrify the world. Random House
Trade Paperbacks
KMEC, Ján, Štefan VALENČÍK, Miroslav GOMBÁR, Monika KARKOVÁ a Alena VAGASKÁ. Logistic Approach
of Building and Development of Production System. Nase More, Dubrovnik: University of Dubrovnik, 2016, roč.
63, č. 3, s. 145-149. ISSN 0469-6255
Kurkin, O., Kleinová, J., Čechura, T., & Broum, T. (2011). Cost evaluation of the RC model innovation. Paper
presented at the Creating Global Competitive Economies: A 360-Degree Approach - Proceedings of the 17th
International Business Information Management Association Conference, IBIMA 2011, , 4 613-618
LEGÁT a kol.: Systémy managementu jakosti a spolehlivosti v údržbě. ČSJ, Praha, 2007, ISBN 978 SJ, Praha, 2007,
ISBN 978-80-02-01949-7
Legat, V. Management and maintenance engineering. Praha: Professional Publishing, 2013. ISBN 978-80-7431-119-
2.
Metodická příručka "Člověk a stroj"
https://ipodpora.odbory.info/soubory/dms/ukony/20134/6/%C4%8Clov%C4%9Bk%20a%20stroj.pdf
502
Proceedings of the International Conference on Industrial Engineering and Operations Management
Pilsen, Czech Republic, July 23-26, 2019
© IEOM Society International
Mihalov Juraj, Pietrikova Emilia , Balaz Anton, Mados Branislav , Adam Norbert : Potential of Low Cost Motion
Sensors Compared to Programming Environments. In: Acta Polytechnica Hungarica, vol. 15, no. 6, pp. 155-
177, 2018, doi: 10.12700/APH.15.6.2018.6.9.
Moubray, J. (1997). Reliability-centered maintenance. Industrial Press Inc.
Nakajima, S. (1988). Introduction to TPM: Total Productive Maintenance (preventative maintenance series).
Hardcover. ISBN 0-91529-923-2.
Nof, S. Y., Wilhelm, W. E., & Warnecke, H. J. (1997). Introduction and fundamental concepts of assembly. In
Industrial Assembly (pp. 1-44). Springer, Boston, MA
Orosz, T. (2017). Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods. Periodica
Polytechnica Electrical Engineering and Computer Science.
Orosz, T., rés, P., Raisz, D., & Tamus, Á. Z. (2015). Analysis of the green power transition on optimal power
transformer designs. Periodica Polytechnica Electrical Engineering and Computer Science, 59(3), 125-131.
Poór, P., Šimon, M., & Karková, M. (2016). CMMS as an effective solution for company maintenance costs reduction.
In Production Management and Engineering Sciences (Vol. 241, No. 246, pp. 241-246).
Poór, P., Kamaryt, T., & Simon, M. (2015). Introducing autonomous maintenance by implementing OTH hybrid
positions and TPM methods in metallurgical company. International Journal of Engineering and Technology,
7(3), 817-824
Rosenberg, N. (1963). Technological change in the machine tool industry, 18401910. The Journal of Economic
History, 23(4), 414-443
Simeu-Abazi, Z. and Sassine, C. (2001), “Maintenance integration in manufacturing systems: fromthe modelling tool
to evaluation”,International Journal of Flexible Manufacturing Systems,Vol. 13 No. 2, pp. 267-285
Smith, B. L. (2001). The third industrial revolution: policymaking for the Internet. Colum. Sci. & Tech. L. Rev., 3, 1
Spear, B. (2008). James Watt: The steam engine and the commercialization of patents. World patent information,
30(1), 53-58.
Straka Martin et al.: Simulation of the process for production of plastics films as a way to increase the competitiveness
of the company / 2016.In: Przemysl chemiczny. Vol. 95, no. 1 (2016), p. 37-41. - ISSN 0033-2496
Šimon, M., & Broum, T. (2018). Layout calculations related to product insourcing. Paper presented at the Annals of
DAAAM and Proceedings of the International DAAAM Symposium, 29(1) 0312-0318. doi:
10.2507/29th.daaam.proceedings.045
Toms. M.: Měření efektů v socialistické ekonomice nástin teorie. Svoboda. Praha 1981, str. 202
US department of energy, “Operations & Maintenance Best Practices”, release 3.0, August 2010
Volek, T., & Novotna, M. (2017). LABOUR MARKET IN THE CONTEXT OF INDUSTRY 4.0. In Loster, T and
Pavelka, T (Ed.), 11TH INTERNATIONAL DAYS OF STATISTICS AND ECONOMICS (s. 1790–1799).
FUGNEROVA 691, SLANY, 27401, CZECH REPUBLIC: MELANDRIUM
Waeyenbergh, G., & Pintelon, L. (2002). A framework for maintenance concept development. International journal
of production economics, 77(3), 299-313
Biographies
Peter Poór is a Post-Doc Researcher at Department of Industrial Engineering and Management at University of West
Bohemia in Pilsen, Czech Republic. He earned Ing. in the field of Finance, Banking and Investment at Faculty of
Economics, Technical University of Kosice, Slovakia and Ph.D. in the field of Industrial Engineering at the
Department of Industrial Engineering and Management Faculty at Technical University of Kosice. He has published
Journals and conference papers. He also worked for IPE Paris for the delivery of Online MBA program. His research
interests include Industrial Engineering, Maintenance, Facility Management. He has experience in management,
marketing, product lifecycle and development, branding, communication and market research. He visited NYU
Polytechnic School of Engineering, DTU Copenhagen, also Anglia Ruskin University in England. He also had lectures
in Japan, Germany, Spain, and many others.
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Pilsen, Czech Republic, July 23-26, 2019
© IEOM Society International
David Ženíšek is a PhD student at the Department of Industrial Engineering in Faculty of Mechanical Engineering at
the University of West Bohemia (UWB). He specializes on the Maintenance Management with relation to Industry
4.0. He finished master's degree in system engineering with focus on Process and Project Management at the Faculty
of Economics at UWB. He is also a member of the Czech Organization for Maintenance and an alumni member of
IAESTE Czech Republic.
Prof. Josef Basl works at the Department of industrial engineering and management at the Faculty of mechanical
engineering at University of West Bohemia in Pilsen. His research area is focusing on enterprise information systems,
business process optimization and industry 4.0 readiness. He is the president of the Czech Society for Systems
Integration. He is author many publication in international journals and books. He has completed several foreign
internships in Poland, Germany, the UK and the USA. He is a member of several scientific councils, doctoral degree
programs, a member of the program committees of several major conferences.”
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... During the last seven decades, several waves have appeared to provide effective maintenance strategies. These waves are classified in three categories: preventive, productive and predictive maintenance technologies [35] . Each phase is related to certain industrial developments, such as the Internet, automation, electric energy, etc. ...
... In order to compare these three waves, we can find several characteristics in literature. There is a factor so-called the OEE (Overall Equipment Effectiveness) for evaluating the effectiveness rate [35] . The corresponding OEE value for preventive maintenance strategy belongs to the range of 50-75%. ...
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Objective: Traditional manufacturing has several issues to determine a general maintenance strategy. Additive Manufacturing (AM) is a special type of fabrication, which possesses different issues, especially uncertainty failure cases. This forms a big obstacle to becoming an industrialized production strategy. The objective of this work is to provide the most suitable maintenance strategy in order to reduce the likelihood of failure that can help in industrializing the AM technology. Methods: Among the different maintenance strategies, Predictive Maintenance (PdM) became widely treated in academia and industry. According to the methods used for detecting the failure signs, it can be classified into two types: Condition-Based Predictive Maintenance (CBPdM) and Statistical-Based Predictive Maintenance (SBPdM). The use of the last type highly depends on available and accessible data. However, CBPdM depends on only periodic or continuous condition monitoring tools for detecting the failure signs. Results: The existence of various types of failure cases yields to a big difficulty to predict failures. In addition, because of insufficient data, SBPdM cannot be selected as a suitable maintenance strategy for additive manufacturing. According to the presented examples, the CBPdM can be considered here as the best maintenance strategy for AM. Conclusion: CBPdM strategy is the best compromise between cost and applicability where there is not enough data. This selected maintenance approach represents an efficient tool in industrializing AM technology.
... In the US, about 33 cents of every dollar spent on maintenance is lost to unnecessary maintenance tasks [1]. With the emergence of Industry 4.0, new approaches have been developed for product maintenance, incorporating components such as wireless and intelligent sensors, big data, and artificial intelligence techniques [2]. Predictive maintenance (PdM) involves anticipating maintenance actions when deterioration or a drop in performance is detected in machine patterns. ...
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Introduction/Importance of Study: Predictive Maintenance (PdM) is a key challenge within the Industrial Internet of Things (IIoT). It aims to enhance system operations by minimizing equipment failures, leading to smoother operations and increased productivity. By anticipating maintenance needs before failures occur, PdM ensures more reliable and efficient industrial processes. Novelty Statement: This study examines maintenance techniques and datasets that leverage AI and ML for predictive maintenance in the context of industrial IoT. The primary goal is to enhance productivity, identify faults before failures occur, and minimize downtime. By utilizing advanced algorithms, the study aims to improve the efficiency and reliability of industrial systems. Material and Method: A systematic literature review of state-of-the-art predictive maintenance in the context of industrial IoT, incorporating machine learning (ML) and artificial intelligence (AI) methods, is conducted. This review is based on research articles retrieved from the Dimensions.ai database, covering publications from 2018 to 2024. Result and Discussion: This comprehensive analysis offers valuable insights for advancing Predictive Maintenance (PdM) strategies in the Industrial Internet of Things (IIoT), ultimately contributing to more efficient manufacturing processes. The study highlights leading publication venues and top keywords in this research area, providing a clear picture of emerging trends. It also explores the prognosis of PdM within the manufacturing industry. Additionally, the review discusses relevant models, methods, input variables, and datasets in the PdM and IIoT domain, with a particular focus on machine learning (ML) and artificial intelligence (AI) techniques. Among the most widely used techniques for PdM in IIoT are deep learning, artificial neural networks, and random forest. Concluding Remarks: Subsequently, the study highlights various challenges, offering future research directions aimed at refining predictive maintenance techniques.
... The advent of IoT and AI has markedly transformed maintenance strategies in many industrial sectors, propelled by the combination of advanced networks and predictive modeling, enabling real-time data acquisition and processing from production equipment [1]. This novel maintenance paradigm, staying at the forefront of Industry 4.0 applications, originates from a long evolution through the centuries, as highlighted by Poor et al. [2], moving from visual inspections of trained craftsmen to data-driven condition-based maintenance being largely adopted for diagnosing the health parameters of observed systems [3,4]. The predictive maintenance (PdM) approach, which extends condition-based maintenance (CbM) with prognostic features, requires amalgamating multiple data sources from a network of sensors. ...
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Despite considerable advancements in integrating the Internet of Things (IoT) and artificial intelligence (AI) within the industrial maintenance framework, the increasing reliance on these innovative technologies introduces significant vulnerabilities due to cybersecurity risks, potentially compromising the integrity of decision-making processes. Accordingly, this study aims to offer comprehensive insights into the cybersecurity challenges associated with predictive maintenance, proposing a novel methodology that leverages generative AI for data augmentation, enhancing threat detection capabilities. Experimental evaluations conducted using the NASA Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) dataset affirm the viability of this approach leveraging the state-of-the-art TimeGAN model for temporal-aware data generation and building a recurrent classifier for attack discrimination in a balanced dataset. The classifier’s results demonstrate the satisfactory and robust performance achieved in terms of accuracy (between 80% and 90%) and how the strategic generation of data can effectively bolster the resilience of intelligent maintenance systems against cyber threats.
... Paper [10] examines the methodologies used to assess the lifecycle of various engine components based on usage patterns and environmental factors. The economic impact of engine maintenance is also essential in the literature, papers [11,12] analyse the cost-effectiveness of the automotive industry's different maintenance strategies, including reactive, preventive, and predictive maintenance. ...
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Developing Communication protocols has played a crucial role in the industry’s success. The featured article deals with the main communication protocols used in industrial automation. Section 2 summarizes different technologies in primary communication protocols used between devices, represented by the automation pyramid that occurs at different levels or layers. The main contribution of the article is presented in section 3 as a practical study on using industry protocols with EdMES software to automate production processes. This is maintained by using different communication technologies in an automated process. The article’s conclusion specifies the communication technologies identified and how they allow the interaction between other process actors, which are a part of the earlier presented automation pyramid.
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Reliability and Maintainability analyses are necessary actions to be taken on machines in order to reduce operation cost and enhance production efficiency. They are among the design attributes of a machine. Therefore, engineers and machine’s operators need uphold their standard in order to ensure seamless production over the production cycle, reduce wastage due to downtime and maximize profit. This work considers the reliability analysis and preventive maintenance of a mechanically repairable machine -Table Saw machine. The inter-failure times of the machine was shown to follow the Burr XII distribution with scale and shape parameters;
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Transformer design is a challenging engineering task, where the different physical fields have to be harmonized together to fulfill the implied specifications. Due to the difficulty of this task, it can be separated into several subproblems. The first subproblem, in the pre-concept phase, during the transformer design is the calculation of the cost optimal key-design parameters, where not only the technical but also the economical parameters have to be considered, as well. This subproblem belongs to the most general branch of the non-linear mathematical optimization problems. This paper presents the main directions of the evolution and trends in the power transformer design. Main directions of the considered research and the future trends in the field of preliminary design transformer optimization methods are summarized.
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According to the report of the World Health Organization (WHO) on the list of 50 cities with the most polluted air in Europe as many as 33 are located in Poland. All the cities that are on the list exceed the maximum concentration of dust recommended by WHO at least three times. In the Lubuskie Province there is a very serious problem of maintaining good air quality. The air in Poland is among the most polluted in the European Union and this also applies to less-industrialized areas, such as Lubuskie, where the concentration levels of substances hazardous to human health and the environment are recorded as exceeded. One of the main factors affecting the poor air quality in the region is road transport. It is not just a problem near roads with heavy traffic, but also applies to the cities, where there is a large movement of cars, which are often old and do not meet current environmental standards. This article aims to identify the main sources of low emission from road transport and identify potential solutions to help reduce emission from this sector. The actions aimed at limiting low emission from road transport can bring a significant positive ecological effect. The aim of this article is to review one of the main sources of low emission in the province of Lubuskie, which is transportation. Moreover, the authors of the paper indicate the main problems associated with the emission coming from road transport and describe the possibilities for opportunities to reduce pollution from this sector. In addition, the article presents the three-scenario simulation of annual emissions from passenger cars that could take place in 2020.
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The article investigates systems, which represent a modern and popular approach to Virtual Reality and controlling systems. We would like to focus on low-cost motion sensors used in applications which are oriented on object tracking and gesture recognition. There are various types of sensors. Some of them measure the infrared light reflected from the opposing surface, previously emitted by the device in to gather information about any movement in the observed environment. Another way how to recognize not only a moving object present in the environment, but also its gestures and further characteristics of the movement is to use the Kinect. Therefore, we included Kinect also in our research. There is also a sensoric device called Leap Motion, which is specially developed to analyze gestures of human hands and track their motion with very high accuracy. We will provide pros and cons of every mentioned type of sensors or sensoric devices. Our aim is to summarize specific characteristics of mentioned devices to evaluate their ability to be beneficial in the recently very intensively expanding IoT sector. Considering new trends, we decided to focus on low cost sensors in to make our research more relevant also for small businesses and start-ups whose initiative leads to further development of sensoric soloutions and involving them in IoT. We decided to include also Myo Armband. It uses eight electromyography sensors, combined with a gyroscope and an accelerometer to sense electrical activity produced by the muscles of the forearm. Of the multiple programming environments available, we decided to compare and evaluate three programming engines most frequently used for programming applications processing sensoric data. For gaming purposes, the Unreal and Unity 3D engines are the most frequent. For robotics, medicine or for industrial purposes usually LabVIEW is the best choice. In this, we compare the aforementioned three programming environments using different algorithms, utilizing the three motion controllers, and we discuss their (dis)advantages and programming perspectives. © 2018, Budapest Tech Polytechnical Institution. All rights reserved.
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Each manufacturing plant wants to operate their production systems and devices in a reliable manner. What organizations do not want, are manufacturing systems or processes collapsing, leading to production of defective or malfunctioning products. Failures will be reflected, for example, in losses of quality and productivity. One of the most important aspects of well-organized production is machinery maintenance. This article deals first with maintenance as a phenomenon in a manufacturing company, the second part of the article illustrates a practical implementation of a CMMS system.
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From perspective of needs and prosperity of operational practice machinery has central role in any factory. In terms of competitiveness, in global world companies must have synergistically developed all areas, processes and systems that are carried out there. Unstructured development of these ingredients promotes competition advancement and development. For this reason, problems of machinery and equipment maintenance appear as important. © 2015 International Journal of Engineering and Technology (IJET).
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Reliability-centered maintenance is a process used to determine - systematically and scientifically - what must be done to ensure that physical assets continue to do what their users want them to do. Widely recognized by maintenance professionals as the most cost-effective way to develop world-class maintenance strategies, RCM leads to rapid, sustained and substantial improvements in plant availability and reliability, product quality, safety and environmental integrity. The author and his associates have helped users apply RCM and its more modern derivative, RCM2, on more than 700 sites in 34 countries. These sites include all types of manufacturing (especially automobile, steel, paper, petrochemical, pharmaceutical, and food manufacturing), utilities (water, gas, and electricity), armed forces, building services, mining, telecommunications, and transport. This book summarizes this experience in the form of an authoritative and practical description of what RCM2 is and how it should be applied. This book will be of value to maintenance managers, and to anyone else concerned with the reliability, productivity, safety, and environmental integrity of physical assets. Its straightforward, plant-based approach makes the book especially well suited to use in centers of higher education.