Maintenance Management Strategy: Analysis of Machine Performance

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Added on  2023/01/19

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AI Summary
This presentation provides a comprehensive overview of maintenance management strategies, focusing on assessing machine performance and implementing effective maintenance plans. It introduces two key models: the Decision Making model and the Jack-Knife model, to analyze machine failures based on downtime and frequency. The presentation covers the importance of machine performance, including frequency and downtime, and emphasizes the use of predictive maintenance strategies for businesses. It includes a case study on DMG and JKD, demonstrating the application of these methods in real-world scenarios. The presentation concludes by highlighting the effectiveness of reducing downtime and frequency rates to improve machine performance and overall business outcomes, with references to relevant literature. The presentation aims to provide a comprehensive understanding of maintenance management strategies, including predictive maintenance, decision-making grids, and jack-knife diagrams. It emphasizes the importance of reducing downtime and frequency rates to improve machine performance and overall business outcomes. It explores maintenance management strategies for enhanced machine performance. Analyze downtime, frequency, and decision-making models for optimal results. Improve reliability with this presentation.
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Maintenance
Management strategy
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Introduction
Assessment of the machine performance
Criteria is used to analyse the performances
of machines in business
Two models are used that include the
Decision making model and the Jack-Knife
model
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Maintenance management
Maintenance management is a systematic
approach that is involved in the
administrative, financial and technical
framework
Operations of an organisation is linked with
maintenance for prevention of damage of
employees
The availability and use of machines can be
attributed to the development of maintenance
within an organisation
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Machine performance
Machine performance involves identifying the
strength of the machines
The capability of the machines are
determined by the manner in which the
performance of the machines can be
appreciated
Frequency and time can be considered as two
parameters undertaken by machines
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Contd..
Machine performance is used to develop and
identify effective machines
It is used to perform critical tasks
It is necessary to consider the downtime and
the durability of the machines
Understand the technical progress of the
machines for development
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Frequency
Machine frequency denotes the repeatability
of the work load that can be undertaken by
the machines
The manner in which the machines response
is considered as essential for the effective
work performance of an organisation
Along with this, the unproductive nature of
the machines is also considered in terms of
its frequency
The repetitive nature allows the machines to
be functional in terms of crisis
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Downtime
Downtime of the machines involves the
inactive time of the machines
The failure to be productive is considered as
non-usage time of the machines
The recovery time can be considered as
another factor related to the downtime of the
machines
It leads to the loss of productivity in an
organisation
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Breakdown of downtime elements
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Ranking machines in terms of downtime
and frequency
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Appropriate maintenance strategy
Predictive maintenance strategy can be used
It can help in estimating the number of times
a machine can fail
Existing failures and past failure records can
be analysed to identify the performance of
the machines
It helps to maintain a low maintenance
frequency as well as a high reliability within
the business
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Flow chart of the maintenance strategy
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Decision making grid
The decision making grid is used to analyse
the failure of the machines
The failures are located as per multiple
criteria
The dimensions that are considered includes
the downtime and the failure frequency
Downtime is commonly known as the Mean
Time between failures
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Jack-Knife diagram
Jack-Knife diagram is considered as a critical
mathematical calculation of the electrical
failure
The codes for assessment can be taken into
account for its analysis
The major disadvantage can be the hyperbole
system
The use of the diagram is mainly based on
the development of the codes that cause
major downtimes
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Case study on DMG and JKD
Machines are identified with performance
being indicated
The analysis is made based on the low
frequency and high downtime
JKD is the acute region
MTTR is used to characterise DMG
A pessimistic finding is obtained compared to
the classification
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Case study on DMG and JKD
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Conclusion
The application of DMG and JKD can help in
the development of the machines
The use of machineries can be considered as
effective only by reducing its downtime and
frequency rate
The case study helps to identify the effective
manner in which the two methods can be
considered for business
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Bibliography
Arcos Jiménez, A., Gómez Muñoz, C. and García Márquez, F., 2018. Machine learning
for wind turbine blades maintenance management. Energies, 11(1), p.13.
Bevilacqua, M., Ciarapica, F.E., Giacchetta, G., Paciarotti, C. and Marchetti, B., 2016.
Innovative Maintenance Management Methods in Oil Refineries. In Quality and
Reliability Management and Its Applications (pp. 197-226). Springer, London.
Campbell, J.D. and Reyes-Picknell, J.V., 2015. Uptime: Strategies for excellence in
maintenance management. Productivity Press.
Campbell, J.D., Jardine, A.K. and McGlynn, J. eds., 2016. Asset management
excellence: optimizing equipment life-cycle decisions. CRC Press.
Hesla, E., Fowler, C. and Huber, J., 2018, September. Maintenance Management of
Multiple Plants. In 2018 IEEE Industry Applications Society Annual Meeting
(IAS) (pp. 1-5). IEEE.
Navarro, T.S., Towse, B.W., Burgess, N., Barry, C. and Doeller, C.F., 2017. Optimal
decision making using grid cells under spatial uncertainty.
Ramachandran, S., Rajendran, C., Veeraragavan, A. and Ramya, R., 2017, August. A
Framework for Maintenance Management of Pavement Networks under
Performance-Based Multi-Objective Optimization. In International Conference on
Highway Pavements and Airfield Technology 2017.
Seecharan, T., Labib, A. and Jardine, A., 2018. Maintenance strategies: Decision
Making Grid vs Jack-Knife Diagram. Journal of Quality in Maintenance
Engineering, 24(1), pp.61-78.
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