A Model for Determining the Dependability of Continuous Subsystems in Coal Mines Using the Fuzzy Logic Approach
Abstract
:1. Introduction
2. Case Study: Open Pit Gacko, Continuous Parts of the Combined System
3. Methodology
3.1. Dependability
- performances of reliability;
- performances of maintainability;
- performances of logistic support for maintenance.
3.2. Development Fuzzy Model
Results of Expert Evaluation
3.3. Determination the Partial Indicator of Maintainability M
3.4. Determination of Partial Indicators of Reliability and Logistical Support of Parts of the Continuous Prats of Combined System R and F
3.5. Dependability of the CCS System at the Open Pit Gacko
4. Verification of Fuzzy Model
- technological failures;
- electrical failures;
- mechanical failures;
- shift of workers;
- equipment overhaul;
- daily review;
- weather conditions.
- Technological failures are consistently high and vary from 20.1% to 33.4% per year, which accounts for the largest part of total downtime (29% for a period of 6 years).
- Shift of workers and equipment overhaul are also significant downtime factors, with overall percentages of 23% and 22%.
- Electrical failures and mechanical failures have a relatively smaller share, but show variations between years.
- Weather conditions have the least participation in total downtime (0.5% for a period of 6 years).
- Daily review varies by year, but records a significant participation of 17% for the entire observed period.
5. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix B
Expert | Type | poor | adeq | aver | good | exc | Expert | Type | poor | adeq | aver | good | exc |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | R | 0 | 0.5 | 0.5 | 0 | 0 | 6 | R | 0 | 0 | 0 | 0.6 | 0.4 |
t | 0 | 0.2 | 0.8 | 0 | 0 | t | 0 | 0.4 | 0.6 | 0 | 0 | ||
e | 0 | 0.6 | 0.4 | 0 | 0 | e | 0 | 0.2 | 0.8 | 0 | 0 | ||
u | 0.2 | 0.8 | 0 | 0 | 0 | u | 0 | 0.1 | 0.9 | 0 | 0 | ||
d | 0 | 0.5 | 0.5 | 0 | 0 | d | 0 | 0.4 | 0.6 | 0 | 0 | ||
m | 0 | 0.3 | 0.7 | 0 | 0 | m | 0 | 0.3 | 0.7 | 0 | 0 | ||
s | 0 | 0.1 | 0.9 | 0 | 0 | s | 0 | 0.7 | 0.3 | 0 | 0 | ||
F | 0.4 | 0.6 | 0 | 0 | 0 | F | 0.2 | 0.8 | 0 | 0 | 0 | ||
2 | R | 0 | 0 | 0.3 | 0.7 | 0 | 7 | R | 0 | 0 | 0.3 | 0.7 | 0 |
t | 0 | 0 | 0.35 | 0.65 | 0 | t | 0 | 0 | 0.2 | 0.8 | 0 | ||
e | 0 | 0 | 0.2 | 0.8 | 0 | e | 0 | 0 | 0 | 0.4 | 0.6 | ||
u | 0 | 0 | 0.6 | 0.4 | 0 | u | 0 | 0.4 | 0.6 | 0 | 0 | ||
d | 0.2 | 0.8 | 0 | 0 | 0 | d | 0 | 0 | 0 | 0.6 | 0.4 | ||
m | 0.5 | 0.5 | 0 | 0 | 0 | m | 0 | 0 | 0.2 | 0.8 | 0 | ||
s | 0 | 0.7 | 0.3 | 0 | 0 | s | 0 | 0 | 0.3 | 0.7 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.4 | 0.6 | 0 | 0 | ||
3 | R | 0 | 0 | 0.3 | 0.7 | 0 | 8 | R | 0 | 0 | 0 | 0.8 | 0.2 |
t | 0 | 0 | 0.4 | 0.6 | 0 | t | 0 | 0.4 | 0.6 | 0 | 0 | ||
e | 0 | 0 | 0.45 | 0.55 | 0 | e | 0 | 0.3 | 0.7 | 0 | 0 | ||
u | 0 | 0.25 | 0.75 | 0 | 0 | u | 0 | 0.6 | 0.4 | 0 | 0 | ||
d | 0 | 0.1 | 0.9 | 0 | 0 | d | 0 | 0 | 0.2 | 0.8 | 0 | ||
m | 0.4 | 0.6 | 0 | 0 | 0 | m | 0 | 0 | 0.7 | 0.3 | 0 | ||
s | 0 | 0.6 | 0.4 | 0 | 0 | s | 0 | 0.4 | 0.6 | 0 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.1 | 0.9 | 0 | 0 | ||
4 | R | 0 | 0 | 0.1 | 0.9 | 0 | 9 | R | 0 | 0 | 0 | 0.9 | 0.1 |
t | 0 | 0 | 0.2 | 0.8 | 0 | t | 0 | 0.3 | 0.7 | 0 | 0 | ||
e | 0 | 0.5 | 0.5 | 0 | 0 | e | 0 | 0 | 0.2 | 0.8 | 0 | ||
u | 0.4 | 0.6 | 0 | 0 | 0 | u | 0 | 0 | 0.4 | 0.6 | 0 | ||
d | 0 | 0.4 | 0.6 | 0 | 0 | d | 0 | 0 | 0.2 | 0.8 | 0 | ||
m | 0.3 | 0.7 | 0 | 0 | 0 | m | 0 | 0 | 0.7 | 0.3 | 0 | ||
s | 0.25 | 0.75 | 0 | 0 | 0 | s | 0 | 0.3 | 0.7 | 0 | 0 | ||
F | 0.15 | 0.85 | 0 | 0 | 0 | F | 0.2 | 0.8 | 0 | 0 | 0 | ||
5 | R | 0 | 0 | 0.3 | 0.7 | 0 | 10 | R | 0 | 0 | 0.6 | 0.4 | 0 |
t | 0 | 0.3 | 0.7 | 0 | 0 | t | 0 | 0.3 | 0.7 | 0 | 0 | ||
e | 0 | 0.7 | 0.3 | 0 | 0 | e | 0 | 0.4 | 0.6 | 0 | 0 | ||
u | 0 | 0.4 | 0.6 | 0 | 0 | u | 0 | 0.6 | 0.4 | 0 | 0 | ||
d | 0.3 | 0.7 | 0 | 0 | 0 | d | 0 | 0.1 | 0.9 | 0 | 0 | ||
m | 0 | 0.6 | 0.4 | 0 | 0 | m | 0 | 0.7 | 0.3 | 0 | 0 | ||
s | 0.3 | 0.7 | 0 | 0 | 0 | s | 0 | 0.2 | 0.8 | 0 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.4 | 0.6 | 0 | 0 |
Expert | Type | poor | adeq | aver | good | exc | Expert | Type | poor | adeq | aver | good | exc |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | R | 0 | 0 | 0 | 0.6 | 0.4 | 6 | R | 0 | 0 | 0 | 0.6 | 0.4 |
t | 0 | 0 | 0.2 | 0.8 | 0 | t | 0 | 0.4 | 0.6 | 0 | 0 | ||
e | 0 | 0 | 0 | 0.7 | 0.3 | e | 0 | 0.2 | 0.8 | 0 | 0 | ||
u | 0.45 | 0.55 | 0 | 0 | 0 | u | 0 | 0.1 | 0.9 | 0 | 0 | ||
d | 0 | 0 | 0.1 | 0.9 | 0 | d | 0 | 0.4 | 0.6 | 0 | 0 | ||
m | 0 | 0.3 | 0.7 | 0 | 0 | m | 0 | 0.3 | 0.7 | 0 | 0 | ||
s | 0 | 0.2 | 0.8 | 0 | 0 | s | 0 | 0.7 | 0.3 | 0 | 0 | ||
F | 0 | 0 | 0.4 | 0.6 | 0 | F | 0.2 | 0.8 | 0 | 0 | 0 | ||
2 | R | 0 | 0 | 0.3 | 0.7 | 0 | 7 | R | 0 | 0 | 0.3 | 0.7 | 0 |
t | 0 | 0 | 0 | 0.3 | 0.7 | t | 0 | 0 | 0.2 | 0.8 | 0 | ||
e | 0 | 0 | 0 | 0.4 | 0.6 | e | 0 | 0 | 0 | 0.4 | 0.6 | ||
u | 0 | 0 | 0.2 | 0.8 | 0 | u | 0 | 0.4 | 0.6 | 0 | 0 | ||
d | 0 | 0 | 0.4 | 0.6 | 0 | d | 0 | 0 | 0 | 0.6 | 0.4 | ||
m | 0.5 | 0.5 | 0 | 0 | 0 | m | 0 | 0 | 0.2 | 0.8 | 0 | ||
s | 0 | 0 | 0.8 | 0.2 | 0 | s | 0 | 0 | 0.3 | 0.7 | 0 | ||
F | 0 | 0 | 0.2 | 0.8 | 0 | F | 0 | 0.4 | 0.6 | 0 | 0 | ||
3 | R | 0 | 0 | 0.3 | 0.7 | 0 | 8 | R | 0 | 0 | 0 | 0.8 | 0.2 |
t | 0 | 0 | 0.4 | 0.6 | 0 | t | 0 | 0.4 | 0.6 | 0 | 0 | ||
e | 0 | 0 | 0.45 | 0.55 | 0 | e | 0 | 0.3 | 0.7 | 0 | 0 | ||
u | 0 | 0.25 | 0.75 | 0 | 0 | u | 0 | 0.6 | 0.4 | 0 | 0 | ||
d | 0 | 0.1 | 0.9 | 0 | 0 | d | 0 | 0 | 0.2 | 0.8 | 0 | ||
m | 0.4 | 0.6 | 0 | 0 | 0 | m | 0 | 0 | 0.7 | 0.3 | 0 | ||
s | 0 | 0.6 | 0.4 | 0 | 0 | s | 0 | 0.4 | 0.6 | 0 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.1 | 0.9 | 0 | 0 | ||
4 | R | 0 | 0 | 0.1 | 0.9 | 0 | 9 | R | 0 | 0 | 0 | 0.9 | 0.1 |
t | 0 | 0 | 0.2 | 0.8 | 0 | t | 0 | 0.3 | 0.7 | 0 | 0 | ||
e | 0 | 0.5 | 0.5 | 0 | 0 | e | 0 | 0 | 0.2 | 0.8 | 0 | ||
u | 0.4 | 0.6 | 0 | 0 | 0 | u | 0 | 0 | 0.4 | 0.6 | 0 | ||
d | 0 | 0.4 | 0.6 | 0 | 0 | d | 0 | 0 | 0.7 | 0.3 | 0 | ||
m | 0.3 | 0.7 | 0 | 0 | 0 | m | 0 | 0 | 0.4 | 0.6 | 0 | ||
s | 0.25 | 0.75 | 0 | 0 | 0 | s | 0 | 0.3 | 0.7 | 0 | 0 | ||
F | 0.15 | 0.85 | 0 | 0 | 0 | F | 0.2 | 0.8 | 0 | 0 | 0 | ||
5 | R | 0 | 0 | 0.3 | 0.7 | 0 | 10 | R | 0 | 0 | 0.6 | 0.4 | 0 |
t | 0 | 0.3 | 0.7 | 0 | 0 | t | 0 | 0.3 | 0.7 | 0 | 0 | ||
e | 0 | 0.7 | 0.3 | 0 | 0 | e | 0 | 0.4 | 0.6 | 0 | 0 | ||
u | 0 | 0.4 | 0.6 | 0 | 0 | u | 0 | 0.6 | 0.4 | 0 | 0 | ||
d | 0.3 | 0.7 | 0 | 0 | 0 | d | 0 | 0.1 | 0.9 | 0 | 0 | ||
m | 0 | 0.6 | 0.4 | 0 | 0 | m | 0 | 0.7 | 0.3 | 0 | 0 | ||
s | 0.3 | 0.7 | 0 | 0 | 0 | s | 0 | 0.2 | 0.8 | 0 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.4 | 0.6 | 0 | 0 |
Expert | Type | poor | adeq | aver | good | exc | Expert | Type | poor | adeq | aver | good | exc |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | R | 0 | 0.5 | 0.5 | 0 | 0 | 6 | R | 0 | 0 | 0 | 0.6 | 0.4 |
t | 0 | 0.2 | 0.8 | 0 | 0 | t | 0 | 0.4 | 0.6 | 0 | 0 | ||
e | 0 | 0.6 | 0.4 | 0 | 0 | e | 0 | 0.2 | 0.8 | 0 | 0 | ||
u | 0.2 | 0.8 | 0 | 0 | 0 | u | 0 | 0.1 | 0.9 | 0 | 0 | ||
d | 0 | 0.5 | 0.5 | 0 | 0 | d | 0 | 0.4 | 0.6 | 0 | 0 | ||
m | 0 | 0.3 | 0.7 | 0 | 0 | m | 0 | 0.3 | 0.7 | 0 | 0 | ||
s | 0 | 0.1 | 0.9 | 0 | 0 | s | 0 | 0.7 | 0.3 | 0 | 0 | ||
F | 0.4 | 0.6 | 0 | 0 | 0 | F | 0.2 | 0.8 | 0 | 0 | 0 | ||
2 | R | 0 | 0 | 0.3 | 0.7 | 0 | 7 | R | 0 | 0 | 0.3 | 0.7 | 0 |
t | 0 | 0 | 0.35 | 0.65 | 0 | t | 0 | 0 | 0.2 | 0.8 | 0 | ||
e | 0 | 0 | 0.2 | 0.8 | 0 | e | 0 | 0 | 0 | 0.4 | 0.6 | ||
u | 0 | 0 | 0.6 | 0.4 | 0 | u | 0 | 0.4 | 0.6 | 0 | 0 | ||
d | 0.2 | 0.8 | 0 | 0 | 0 | d | 0 | 0 | 0 | 0.6 | 0.4 | ||
m | 0.5 | 0.5 | 0 | 0 | 0 | m | 0 | 0 | 0.2 | 0.8 | 0 | ||
s | 0 | 0.7 | 0.3 | 0 | 0 | s | 0 | 0 | 0.3 | 0.7 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.4 | 0.6 | 0 | 0 | ||
3 | R | 0 | 0 | 0.3 | 0.7 | 0 | 8 | R | 0 | 0 | 0 | 0.8 | 0.2 |
t | 0 | 0 | 0.4 | 0.6 | 0 | t | 0 | 0.4 | 0.6 | 0 | 0 | ||
e | 0 | 0 | 0.45 | 0.55 | 0 | e | 0 | 0.3 | 0.7 | 0 | 0 | ||
u | 0 | 0.25 | 0.75 | 0 | 0 | u | 0 | 0.6 | 0.4 | 0 | 0 | ||
d | 0 | 0.1 | 0.9 | 0 | 0 | d | 0 | 0 | 0.2 | 0.8 | 0 | ||
m | 0.4 | 0.6 | 0 | 0 | 0 | m | 0 | 0 | 0.7 | 0.3 | 0 | ||
s | 0 | 0.6 | 0.4 | 0 | 0 | s | 0 | 0.4 | 0.6 | 0 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.1 | 0.9 | 0 | 0 | ||
4 | R | 0 | 0 | 0.1 | 0.9 | 0 | 9 | R | 0 | 0 | 0 | 0.9 | 0.1 |
t | 0 | 0 | 0.2 | 0.8 | 0 | t | 0 | 0.3 | 0.7 | 0 | 0 | ||
e | 0 | 0.5 | 0.5 | 0 | 0 | e | 0 | 0 | 0.2 | 0.8 | 0 | ||
u | 0.4 | 0.6 | 0 | 0 | 0 | u | 0 | 0 | 0.4 | 0.6 | 0 | ||
d | 0 | 0.4 | 0.6 | 0 | 0 | d | 0 | 0 | 0.7 | 0.3 | 0 | ||
m | 0.3 | 0.7 | 0 | 0 | 0 | m | 0 | 0 | 0.4 | 0.6 | 0 | ||
s | 0.25 | 0.75 | 0 | 0 | 0 | s | 0 | 0.3 | 0.7 | 0 | 0 | ||
F | 0.15 | 0.85 | 0 | 0 | 0 | F | 0.2 | 0.8 | 0 | 0 | 0 | ||
5 | R | 0 | 0 | 0.3 | 0.7 | 0 | 10 | R | 0 | 0 | 0.6 | 0.4 | 0 |
t | 0 | 0.3 | 0.7 | 0 | 0 | t | 0 | 0.3 | 0.7 | 0 | 0 | ||
e | 0 | 0.7 | 0.3 | 0 | 0 | e | 0 | 0.4 | 0.6 | 0 | 0 | ||
u | 0 | 0.4 | 0.6 | 0 | 0 | u | 0 | 0.6 | 0.4 | 0 | 0 | ||
d | 0.3 | 0.7 | 0 | 0 | 0 | d | 0 | 0.1 | 0.9 | 0 | 0 | ||
m | 0 | 0.6 | 0.4 | 0 | 0 | m | 0 | 0.7 | 0.3 | 0 | 0 | ||
s | 0.3 | 0.7 | 0 | 0 | 0 | s | 0 | 0.2 | 0.8 | 0 | 0 | ||
F | 0 | 0.3 | 0.7 | 0 | 0 | F | 0 | 0.4 | 0.6 | 0 | 0 |
References
- Ali, S.H.; Giurco, D.; Arndt, N.; Nickless, E.; Brown, G.; Demetriades, A.; Durrheim, R.; Enriquez, M.A.; Kinnaird, J.; Littleboy, A.; et al. Mineral supply for sustainable development requires resource governance. Nature 2017, 543, 367–372. [Google Scholar] [CrossRef] [PubMed]
- Dubiński, J. Sustainable Development of Mining Mineral Resources. J. Sustain. Min. 2013, 12, 1–6. [Google Scholar] [CrossRef]
- Purhamadani, E.; Bagherpour, R.; Tudeshki, H. Energy consumption in open-pit mining operations relying on reduced energy consumption for haulage using in-pit crusher systems. J. Clean. Prod. 2020, 291, 125228. [Google Scholar] [CrossRef]
- Zhang, S.; Xia, X. Modeling and energy efficiency optimization of belt conveyors. Appl. Energy 2011, 88, 3061–3071. [Google Scholar] [CrossRef]
- Tabelin, C.B.; Dallas, J.; Casanova, S.; Pelech, T.; Bournival, G.; Saydam, S.; Canbulat, I. Towards a low-carbon society: A review of lithium resource availability, challenges and innovations in mining, extraction and recycling, and future perspectives. Miner. Eng. 2021, 163, 106743. [Google Scholar] [CrossRef]
- Ercelebi, S.G.; Bascetin, A. Optimization of shovel-truck system for surface mining. J. S. Afr. Inst. Min. Metall. 2009, 109, 433–439. [Google Scholar]
- Bao, H.; Knights, P.; Kizil, M.; Nehring, M. Electrification Alternatives for Open Pit Mine Haulage. Mining 2023, 3, 1–25. [Google Scholar] [CrossRef]
- Issa, M.; Ilinca, A.; Rousse, D.R.; Boulon, L.; Groleau, P. Renewable Energy and Decarbonization in the Canadian Mining Industry: Opportunities and Challenges. Energies 2023, 16, 6967. [Google Scholar] [CrossRef]
- Kim, H.; Lee, W.-H.; Lee, C.-H.; Kim, S.-M. Development of Monitoring Technology for Mine Haulage Road through Sensor-Connected Digital Device and Smartphone Application. Appl. Sci. 2022, 12, 12166. [Google Scholar] [CrossRef]
- Petrović, D.V.; Tanasijević, M.; Stojadinović, S.; Ivaz, J.; Stojković, P. Fuzzy Model for Risk Assessment of Machinery Failures. Symmetry 2020, 12, 525. [Google Scholar] [CrossRef]
- Gomilanovic, M.; Tanasijevic, M.; Stepanovic, S. Determining the Availability of Continuous Systems at Open Pits Applying Fuzzy Logic. Energies 2022, 15, 6786. [Google Scholar] [CrossRef]
- Djenadic, S.; Ignjatovic, D.; Tanasijevic, M.; Bugaric, U.; Jankovic, I.; Subaranovic, T. Development of the Availability Concept by Using Fuzzy Theory with AHP Correction, a Case Study: Bulldozers in the Open-Pit Lignite Mine. Energies 2019, 12, 4044. [Google Scholar] [CrossRef]
- Gomilanovic, M.; Bugaric, U.; Bankovic, M.; Stanic, N.; Stepanovic, S. Determining the Availability of Continuous Systems in Open Pits Using ANFIS and a Simulation Model. Energies 2024, 17, 1138. [Google Scholar] [CrossRef]
- Gomilanovic, M.; Tanasijevic, M.; Stepanovic, S.; Miletic, F. A Model for Determining Fuzzy Evaluations of Partial Indicators of Availability for High-Capacity Continuous Systems at Coal Open Pits Using a Neuro-Fuzzy Inference System. Energies 2023, 16, 2958. [Google Scholar] [CrossRef]
- Jovančić, P.; Tanasijević, M.; Milisavljević, V.; Cvjetić, A.; Ivezić, D.; Bugarić, U. Applying the Fuzzy Inference Model in Maintenance Centered to Safety: Case Study—Bucket Wheel Excavator. In Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0; IGI Global: Hershey, PA, USA, 2020; pp. 142–165. [Google Scholar] [CrossRef]
- Khanlari, A.; Mohammadi, K.; Sohrabi, B. Prioritizing equipments for preventive maintenance (PM) activities using fuzzy rules. Comput. Ind. Eng. 2008, 54, 169–184. [Google Scholar] [CrossRef]
- Tanasijevic, M.; Ivezic, D.; Ignjatovic, D.; Polovina, D. Dependability as criteria for bucket wheel excavator revitalization. J. Sci. Ind. Res. 2011, 70, 13–19. [Google Scholar]
- Čelebić, M.; Bajić, D.; Bajić, S.; Banković, M.; Torbica, D.; Milošević, A.; Stevanović, D. Development of an Integrated Model for Open-Pit-Mine Discontinuous Haulage System Optimization. Sustainability 2024, 16, 3156. [Google Scholar] [CrossRef]
- Urošević, K.U.; Gligorić, Z.; Miljanović, I.M.; Čedomir; Beljić, B.; Gligorić, M.G.; Moreno-Jiménez, J. Novel Methods in Multiple Criteria Decision-Making Process (MCRAT and RAPS)—Application in the Mining Industry. Mathematics 2021, 9, 1980. [Google Scholar] [CrossRef]
- Halilović, D.; Gligorić, M.; Gligorić, Z.; Pamučar, D. An Underground Mine Ore Pass System Optimization via Fuzzy 0–1 Linear Programming with Novel Torricelli–Simpson Ranking Function. Mathematics 2023, 11, 2914. [Google Scholar] [CrossRef]
- Li, S.; Huang, Q.; Hu, B.; Pan, J.; Chen, J.; Yang, J.; Zhou, X.; Wang, X.; Yu, H. Mining Method Optimization of Difficult-to-Mine Complicated Orebody Using Pythagorean Fuzzy Sets and TOPSIS Method. Sustainability 2023, 15, 3692. [Google Scholar] [CrossRef]
- Bajić, S.; Bajić, D.; Gluščević, B.; Vakanjac, V.R. Application of Fuzzy Analytic Hierarchy Process to Underground Mining Method Selection. Symmetry 2020, 12, 192. [Google Scholar] [CrossRef]
- Jaderi, F.; Ibrahim, Z.Z.; Zahiri, M.R. Criticality Analysis of Petrochemical Assets using Risk Based Maintenance and the Fuzzy Inference System. Process. Saf. Environ. Prot. 2018, 121, 312–325. [Google Scholar] [CrossRef]
- Bakhtavar, E.; Hosseini, S.; Hewage, K.; Sadiq, R. Air Pollution Risk Assessment Using a Hybrid Fuzzy Intelligent Probability-Based Approach: Mine Blasting Dust Impacts. Nat. Resour. Res. 2021, 30, 2607–2627. [Google Scholar] [CrossRef]
- Tubis, A.; Werbińska-Wojciechowska, S.; Wroblewski, A. Risk Assessment Methods in Mining Industry—A Systematic Review. Appl. Sci. 2020, 10, 5172. [Google Scholar] [CrossRef]
- Jiskani, I.M.; Cai, Q.; Zhou, W.; Lu, X. Assessment of risks impeding sustainable mining in Pakistan using fuzzy synthetic evaluation. Resour. Policy 2020, 69, 101820. [Google Scholar] [CrossRef]
- Spanidis, P.-M.; Roumpos, C.; Pavloudakis, F. A Fuzzy-AHP Methodology for Planning the Risk Management of Natural Hazards in Surface Mining Projects. Sustainability 2021, 13, 2369. [Google Scholar] [CrossRef]
- Petrović, D.V.; Tanasijević, M.; Milić, V.; Lilić, N.; Stojadinović, S.; Svrkota, I. Risk assessment model of mining equipment failure based on fuzzy logic. Expert Syst. Appl. 2014, 41, 8157–8164. [Google Scholar] [CrossRef]
- Djenadic, S.; Tanasijevic, M.; Jovancic, P.; Ignjatovic, D.; Petrovic, D.; Bugaric, U. Risk Evaluation: Brief Review and Innovation Model Based on Fuzzy Logic and MCDM. Mathematics 2022, 10, 811. [Google Scholar] [CrossRef]
- Tanasijević, M.; Ivezić, D.; Jovančić, P.; Ignjatović, D.; Bugarić, U. Dependability assesment of open-pit mines equpment—Study on the bases of fuzzy algebra rules. Eksploat. I Niezawodn. 2013, 15, 66–74. [Google Scholar]
- Dimitrijević, B.; Šubaranović, T.; Stević; Kchaou, M.; Alqurashi, F.; Subotić, M. A Novel Hybrid Fuzzy Multiple-Criteria Decision-Making Model for the Selection of the Most Suitable Land Reclamation Variant at Open-Pit Coal Mines. Sustainability 2024, 16, 4424. [Google Scholar] [CrossRef]
- Ebrahimabadi, A.; Pouresmaieli, M.; Afradi, A.; Pouresmaeili, E.; Nouri, S. Comparing Two Methods of PROMETHEE and Fuzzy TOPSIS in Selecting the Best Plant Species for the Reclamation of Sarcheshmeh Copper Mine. Asian J. Water, Environ. Pollut. 2018, 15, 141–152. [Google Scholar] [CrossRef]
- Liang, W.; Dai, B.; Zhao, G.; Wu, H. Assessing the Performance of Green Mines via a Hesitant Fuzzy ORESTE–QUALIFLEX Method. Mathematics 2019, 7, 788. [Google Scholar] [CrossRef]
- Nehring, M.; Knights, P.; Kizil, M.; Hay, E. A comparison of strategic mine planning approaches for in-pit crushing and conveying, and truck/shovel systems. Int. J. Min. Sci. Technol. 2018, 28, 205–214. [Google Scholar] [CrossRef]
- Ivezić, D.; Tanasijević, M.; Ignjatović, D. Fuzzy Approach to Dependability Performance Evaluation. Qual. Reliab. Eng. Int. 2008, 24, 779–792. [Google Scholar] [CrossRef]
- Chen, S.M. Fuzzy system reliability analysis using fuzzy number arithmetic operations. Fuzzy Sets Syst. 1994, 64, 31–38. [Google Scholar] [CrossRef]
- Ebrahimipour, V.; Suzuki, K. A synergetic approach for assessing and improving equipment performance in offshore industry based on dependability. Reliab. Eng. Syst. Saf. 2006, 91, 10–19. [Google Scholar] [CrossRef]
- Emblemsvag, J.; Tonning, L. Decision support in selecting maintenance organization. J. Qual. Maint. Eng. 2003, 9, 11–24. [Google Scholar] [CrossRef]
- Knapp, G.M.; Mahajan, M. Optimization of maintenance organization and manpower in process industries. J. Qual. Maint. Eng. 1998, 4, 168–183. [Google Scholar] [CrossRef]
- Saraswat, S.; Yadava, G.S. An overview on reliability, availability, maintainability and supportability (RAMS) engineering. Int. J. Qual. Reliab. Manag. 2008, 25, 330–344. [Google Scholar] [CrossRef]
- Strandberg, K. IEC 300: The dependability counterpart of ISO 9000. In Proceedings of the Annual Reliability and Maintainability Symposium, Orlando, FL, USA, 29–31 January 1991; pp. 463–467. [Google Scholar]
- Seo, K.K.; Ahn, B.J. A learning algorithm based estimation method for maintenance cost of product concepts. Comput. Ind. Eng. 2006, 50, 66–75. [Google Scholar] [CrossRef]
- Wang, N.; Kang, R.; Jia, Z.; Wang, L. An algorithm for evaluation and analysis of stationary operational availability basing on mission requirements. Eksploat. I Niezawodn. Maint. Reliab. 2010, 46, 31–35. [Google Scholar]
- Jankovic, I. Optimisation of the Life Cycle Concept of Auxiliary MACHINERY at Lignite Open-Pit Mines. Doctoral Dissertation, Faculty of Mining and Geology, University of Belgrade, Beograd, Serbia, 2020. [Google Scholar]
- Todorovic, J. Technical Systems Maintenance Engineering; Yugoslav Society for Engines and Vehicles: Belgrade, Serbia, 1993. [Google Scholar]
- Tanaskovic, T. Maintenance of Mining Machines; Faculty of Mining and Geology, University of Belgrade: Belgrade, Serbia, 2001. [Google Scholar]
- Tanasijevic, M. Dependability of the Mechanical Components of Bucket Wheel. Doctoral Dissertation, Faculty of Mining and Geology, University of Belgrade, Belgrade, Serbia, 2007. [Google Scholar]
- Krunic, D.J. Development of Quality of Service Model for Auxiliary Equipment in Open Pit Lignite Mines. Doctoral Dissertation, Faculty of Mining and Geology, University of Belgrade, Belgrade, Serbia, 2021. [Google Scholar]
- Krunić, D.J.; Vujić, S.; Tanasijević, M.; Dimitrijević, B.; Šubaranović, T.; Ilić, S.; Maksimovic, S. Model Approaches to Life Cycle Assessment of Auxiliary Machines Based on an Example of a Coal Mine in Serbia. J. Min. Sci. 2018, 54, 404–413. [Google Scholar] [CrossRef]
- International Electrotechnical Vocabulary. Dependability and Quality of Service; IEC Standard: Geneva, Switzerland, 1990. [Google Scholar]
- Jovancic, P. Maintenance of Mining Machines; Faculty of Mining and Geology, University of Belgrade: Belgrade, Serbia, 2014; ISBN 978-86-7352-250-0. [Google Scholar]
- Wang, J.; Yang, J.B.; Sen, P. Safety Analyses and Synthesis Using Fuzzy Sets and Evidential Reasoning. Reliab. Eng. Syst. Saf. 1995, 47, 103–118. [Google Scholar] [CrossRef]
Crusher SB 1515 | Crusher SB 1315 | Belt Conveyors | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | |
t | 0.0000 | 0.2850 | 0.5250 | 0.1900 | 0.0000 | 0.1300 | 0.4800 | 0.3200 | 0.0700 | 0.0000 | 0.0700 | 0.3550 | 0.4450 | 0.1300 | 0.0000 |
e | 0.0600 | 0.2550 | 0.4150 | 0.2700 | 0.0000 | 0.3400 | 0.4300 | 0.2000 | 0.0300 | 0.0000 | 0.0800 | 0.3850 | 0.4150 | 0.1200 | 0.0000 |
u | 0.0000 | 0.1000 | 0.4650 | 0.3750 | 0.0600 | 0.0000 | 0.3600 | 0.3500 | 0.2450 | 0.0450 | 0.0000 | 0.1400 | 0.5300 | 0.3300 | 0.0000 |
d | 0.0400 | 0.1700 | 0.4400 | 0.3000 | 0.0500 | 0.1200 | 0.4300 | 0.3500 | 0.1000 | 0.0000 | 0.0040 | 0.2200 | 0.4900 | 0.2500 | 0.0000 |
m | 0.0000 | 0.1700 | 0.3400 | 0.3700 | 0.1200 | 0.0700 | 0.3000 | 0.3300 | 0.2100 | 0.0900 | 0.0070 | 0.1800 | 0.2700 | 0.3700 | 0.1100 |
s | 0.0000 | 0.0700 | 0.4300 | 0.4450 | 0.0055 | 0.0000 | 0.1700 | 0.4500 | 0.3250 | 0.0550 | 0.0000 | 0.0800 | 0.4300 | 0.4600 | 0.0300 |
Crusher SB 1515 | Crusher SB 1315 | Belt Conveyors | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | |
t | 0.0713 | 0.4163 | 0.6438 | 0.3213 | 0.0475 | 0.2500 | 0.5925 | 0.4575 | 0.1500 | 0.0175 | 0.1588 | 0.4838 | 0.5663 | 0.2413 | 0.0325 |
e | 0.1238 | 0.3738 | 0.5463 | 0.3738 | 0.0675 | 0.4475 | 0.5650 | 0.3150 | 0.0800 | 0.0075 | 0.1763 | 0.5088 | 0.5413 | 0.2238 | 0.0300 |
u | 0.0250 | 0.2163 | 0.5838 | 0.5063 | 0.1538 | 0.0900 | 0.4475 | 0.5013 | 0.3438 | 0.1063 | 0.0350 | 0.2725 | 0.6475 | 0.4625 | 0.0825 |
d | 0.8250 | 0.2900 | 0.5575 | 0.4255 | 0.1250 | 0.2275 | 0.5475 | 0.4825 | 0.1875 | 0.0250 | 0.0950 | 0.3525 | 0.6075 | 0.3725 | 0.0625 |
m | 0.0425 | 0.2550 | 0.4750 | 0.4850 | 0.2125 | 0.1450 | 0.4000 | 0.4575 | 0.3150 | 0.1425 | 0.1150 | 0.2650 | 0.4075 | 0.4650 | 0.2025 |
s | 0.0175 | 0.1775 | 0.5588 | 0.5663 | 0.1663 | 0.0425 | 0.2825 | 0.5738 | 0.4513 | 0.1363 | 0.0200 | 0.1875 | 0.5650 | 0.5750 | 0.1450 |
M-Maintainability | poor | adeq | aver | good | exc |
---|---|---|---|---|---|
Crusher SB 1515 | 0.1250 | 0.4845 | 0.4850 | 0.4163 | 0.0713 |
Crusher SB 1315 | 0.0250 | 0.3150 | 0.4575 | 0.4575 | 0.2275 |
Belt conveyors | 0.0625 | 0.4650 | 0.4650 | 0.4650 | 0.0950 |
Crusher SB 1515 | Crusher SB 1315 | Belt Conveyors | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | |
R | 0.0700 | 0.6400 | 0.2400 | 0.0500 | 0.0000 | 0.2700 | 0.6200 | 0.1100 | 0.0000 | 0.0000 | 0.0700 | 0.6500 | 0.2400 | 0.0400 | 0.0000 |
F | 0.0000 | 0.0000 | 0.4200 | 0.4850 | 0.0950 | 0.0000 | 0.2600 | 0.3700 | 0.3250 | 0.0450 | 0.0000 | 0.0000 | 0.4600 | 0.5000 | 0.0400 |
Crusher SB 1515 | Crusher SB 1315 | Belt Conveyors | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | poor | adeq | aver | good | exc | |
R | 0.2300 | 0.7175 | 0.4125 | 0.1100 | 0.1250 | 0.4250 | 0.7150 | 0.2650 | 0.0275 | 0.0000 | 0.2325 | 0.7275 | 0.4125 | 0.1000 | 0.0100 |
M | 0.1250 | 0.4845 | 0.4850 | 0.4163 | 0.0713 | 0.0250 | 0.3150 | 0.4575 | 0.4575 | 0.2275 | 0.0625 | 0.4650 | 0.4650 | 0.4650 | 0.0950 |
F | 0.0000 | 0.1050 | 0.5413 | 0.6138 | 0.2163 | 0.0650 | 0.3525 | 0.5163 | 0.4288 | 0.1263 | 0.0000 | 0.1150 | 0.5850 | 0.6250 | 0.1650 |
D-Dependability | poor | adeq | aver | good | exc |
---|---|---|---|---|---|
Crusher SB 1515 | 0.0713 | 0.4125 | 0.4850 | 0.4850 | 0.1050 |
Crusher SB 1315 | 0.0275 | 0.2650 | 0.3033 | 0.3033 | 0.2478 |
Belt conveyors | 0.0950 | 0.4125 | 0.4650 | 0.4650 | 0.6250 |
SB 1515 | SB 1315 | Belt Conveyors | |
---|---|---|---|
Z | 2.9753 | 2.8754 | 2.7372 |
S | 0.0599 | 0.0278 | 0.0463 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Stanic, N.; Gomilanovic, M.; Markovic, P.; Krzanovic, D.; Doderovic, A.; Stepanovic, S. A Model for Determining the Dependability of Continuous Subsystems in Coal Mines Using the Fuzzy Logic Approach. Appl. Sci. 2024, 14, 7947. https://doi.org/10.3390/app14177947
Stanic N, Gomilanovic M, Markovic P, Krzanovic D, Doderovic A, Stepanovic S. A Model for Determining the Dependability of Continuous Subsystems in Coal Mines Using the Fuzzy Logic Approach. Applied Sciences. 2024; 14(17):7947. https://doi.org/10.3390/app14177947
Chicago/Turabian StyleStanic, Nikola, Miljan Gomilanovic, Petar Markovic, Daniel Krzanovic, Aleksandar Doderovic, and Sasa Stepanovic. 2024. "A Model for Determining the Dependability of Continuous Subsystems in Coal Mines Using the Fuzzy Logic Approach" Applied Sciences 14, no. 17: 7947. https://doi.org/10.3390/app14177947