A comparative study between the system reliability evaluation methods: case study of mining dump trucks

Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-...
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Autor*in:	Moniri-Morad, Amin [verfasserIn] Sattarvand, Javad

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Mining dump truck Haulage operation Reliability evaluation Maintenance management Harsh and heterogeneous environment

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Journal of engineering and applied science - Berlin : Springer Berlin Heidelberg, 1999, 70(2023), 1 vom: 28. Aug.
Übergeordnetes Werk:	volume:70 ; year:2023 ; number:1 ; day:28 ; month:08

Links:	Volltext

DOI / URN:	10.1186/s44147-023-00272-y

Katalog-ID:	SPR052903958

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allfields	10.1186/s44147-023-00272-y doi (DE-627)SPR052903958 (SPR)s44147-023-00272-y-e DE-627 ger DE-627 rakwb eng Moniri-Morad, Amin verfasserin aut A comparative study between the system reliability evaluation methods: case study of mining dump trucks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. Mining dump truck (dpeaa)DE-He213 Haulage operation (dpeaa)DE-He213 Reliability evaluation (dpeaa)DE-He213 Maintenance management (dpeaa)DE-He213 Harsh and heterogeneous environment (dpeaa)DE-He213 Sattarvand, Javad aut Enthalten in Journal of engineering and applied science Berlin : Springer Berlin Heidelberg, 1999 70(2023), 1 vom: 28. Aug. (DE-627)1735158240 (DE-600)3041047-2 2536-9512 nnns volume:70 year:2023 number:1 day:28 month:08 https://dx.doi.org/10.1186/s44147-023-00272-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 70 2023 1 28 08
spelling	10.1186/s44147-023-00272-y doi (DE-627)SPR052903958 (SPR)s44147-023-00272-y-e DE-627 ger DE-627 rakwb eng Moniri-Morad, Amin verfasserin aut A comparative study between the system reliability evaluation methods: case study of mining dump trucks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. Mining dump truck (dpeaa)DE-He213 Haulage operation (dpeaa)DE-He213 Reliability evaluation (dpeaa)DE-He213 Maintenance management (dpeaa)DE-He213 Harsh and heterogeneous environment (dpeaa)DE-He213 Sattarvand, Javad aut Enthalten in Journal of engineering and applied science Berlin : Springer Berlin Heidelberg, 1999 70(2023), 1 vom: 28. Aug. (DE-627)1735158240 (DE-600)3041047-2 2536-9512 nnns volume:70 year:2023 number:1 day:28 month:08 https://dx.doi.org/10.1186/s44147-023-00272-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 70 2023 1 28 08
allfields_unstemmed	10.1186/s44147-023-00272-y doi (DE-627)SPR052903958 (SPR)s44147-023-00272-y-e DE-627 ger DE-627 rakwb eng Moniri-Morad, Amin verfasserin aut A comparative study between the system reliability evaluation methods: case study of mining dump trucks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. Mining dump truck (dpeaa)DE-He213 Haulage operation (dpeaa)DE-He213 Reliability evaluation (dpeaa)DE-He213 Maintenance management (dpeaa)DE-He213 Harsh and heterogeneous environment (dpeaa)DE-He213 Sattarvand, Javad aut Enthalten in Journal of engineering and applied science Berlin : Springer Berlin Heidelberg, 1999 70(2023), 1 vom: 28. Aug. (DE-627)1735158240 (DE-600)3041047-2 2536-9512 nnns volume:70 year:2023 number:1 day:28 month:08 https://dx.doi.org/10.1186/s44147-023-00272-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 70 2023 1 28 08
allfieldsGer	10.1186/s44147-023-00272-y doi (DE-627)SPR052903958 (SPR)s44147-023-00272-y-e DE-627 ger DE-627 rakwb eng Moniri-Morad, Amin verfasserin aut A comparative study between the system reliability evaluation methods: case study of mining dump trucks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. Mining dump truck (dpeaa)DE-He213 Haulage operation (dpeaa)DE-He213 Reliability evaluation (dpeaa)DE-He213 Maintenance management (dpeaa)DE-He213 Harsh and heterogeneous environment (dpeaa)DE-He213 Sattarvand, Javad aut Enthalten in Journal of engineering and applied science Berlin : Springer Berlin Heidelberg, 1999 70(2023), 1 vom: 28. Aug. (DE-627)1735158240 (DE-600)3041047-2 2536-9512 nnns volume:70 year:2023 number:1 day:28 month:08 https://dx.doi.org/10.1186/s44147-023-00272-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 70 2023 1 28 08
allfieldsSound	10.1186/s44147-023-00272-y doi (DE-627)SPR052903958 (SPR)s44147-023-00272-y-e DE-627 ger DE-627 rakwb eng Moniri-Morad, Amin verfasserin aut A comparative study between the system reliability evaluation methods: case study of mining dump trucks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. Mining dump truck (dpeaa)DE-He213 Haulage operation (dpeaa)DE-He213 Reliability evaluation (dpeaa)DE-He213 Maintenance management (dpeaa)DE-He213 Harsh and heterogeneous environment (dpeaa)DE-He213 Sattarvand, Javad aut Enthalten in Journal of engineering and applied science Berlin : Springer Berlin Heidelberg, 1999 70(2023), 1 vom: 28. Aug. (DE-627)1735158240 (DE-600)3041047-2 2536-9512 nnns volume:70 year:2023 number:1 day:28 month:08 https://dx.doi.org/10.1186/s44147-023-00272-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 70 2023 1 28 08
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author	Moniri-Morad, Amin
spellingShingle	Moniri-Morad, Amin misc Mining dump truck misc Haulage operation misc Reliability evaluation misc Maintenance management misc Harsh and heterogeneous environment A comparative study between the system reliability evaluation methods: case study of mining dump trucks
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topic_title	A comparative study between the system reliability evaluation methods: case study of mining dump trucks Mining dump truck (dpeaa)DE-He213 Haulage operation (dpeaa)DE-He213 Reliability evaluation (dpeaa)DE-He213 Maintenance management (dpeaa)DE-He213 Harsh and heterogeneous environment (dpeaa)DE-He213
topic	misc Mining dump truck misc Haulage operation misc Reliability evaluation misc Maintenance management misc Harsh and heterogeneous environment
topic_unstemmed	misc Mining dump truck misc Haulage operation misc Reliability evaluation misc Maintenance management misc Harsh and heterogeneous environment
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title	A comparative study between the system reliability evaluation methods: case study of mining dump trucks
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title_full	A comparative study between the system reliability evaluation methods: case study of mining dump trucks
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title_sort	comparative study between the system reliability evaluation methods: case study of mining dump trucks
title_auth	A comparative study between the system reliability evaluation methods: case study of mining dump trucks
abstract	Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. © The Author(s) 2023
abstractGer	Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. © The Author(s) 2023
abstract_unstemmed	Abstract The shovel-truck system is a widely used technique for haulage systems in surface mining operations. However, predicting the failure patterns of complex systems requires accurate failure prediction techniques. In this study, several major system reliability evaluation groups, including non-parametric, parametric, and semi-parametric methods, are investigated, and their effectiveness is compared to identify the best group for predicting the failure patterns of complex systems such as mining dump trucks, which operate in harsh environments. A historical dataset of time to failure (TTF) and maintenance data was collected. Then, the system’s reliability was evaluated using the major TTF data analysis methods. The findings demonstrated that all the major system reliability evaluation groups produced similar curves; however, the semi-parametric method outperformed the other methods. This result underscores that this system reliability evaluation group is the most effective method for complex systems. Also, it was found that the dump truck reliability dropped to 50% after 40 operation hours, demonstrating the critical importance of implementing preventive maintenance to enhance the system’s performance and ensure operation safety. In addition, this study provided an appropriate insight into the predictive methods and offered an accurate estimation of the failure pattern of complex systems, resulting in availability and productivity improvement. © The Author(s) 2023
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title_short	A comparative study between the system reliability evaluation methods: case study of mining dump trucks
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A comparative study between the system reliability evaluation methods: case study of mining dump trucks

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