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Hoseinie, Seyed Hadi
Alternative names
Publications (10 of 56) Show all publications
Ghodrati, B., Hoseinie, H. & Kumar, U. (2018). Context-driven mean residual life estimation of mining machinery. International Journal of Surface Mining, Reclamation and Environment, 486-494
Open this publication in new window or tab >>Context-driven mean residual life estimation of mining machinery
2018 (English)In: International Journal of Surface Mining, Reclamation and Environment, ISSN 1389-5265, p. 486-494Article in journal (Refereed) Published
Abstract [en]

Maintenance is crucial to ensure production/output and customer satisfaction in the mining sector. The cost of maintenance of mechanised and automated mining systems is very high, necessitating efforts to enhance the effectiveness of maintenance systems and organisation. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. Determining the Mean Residual Life (MRL) of systems allows organisations to more effectively plan maintenance tasks. In this paper, we use a statistical approach to estimate MRL and consider a Weibull proportional hazard model (PHM) with time-independent covariates to model the hazard function so that the operating environment could be integrated into the reliability analysis. The paper explains our methods for calculating the conditional reliability function and computing the MRL as a function of the current conditions. The model is verified and validated using data from the hydraulic system of LHD equipment in a Swedish mine. The results are useful to estimate the remaining useful life of such systems; the method can be used for maintenance planning, helping to control unplanned stoppages of highly mechanised and automated systems.

Place, publisher, year, edition, pages
Taylor & Francis, 2018
Keywords
Mean Residual Life (MRL), proportional hazard model, conditional reliability, Weibull, LHD machine
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63100 (URN)10.1080/17480930.2017.1308067 (DOI)000445077100002 ()2-s2.0-85017207823 (Scopus ID)
Note

Validerad; 2018;Nivå 2;2018-10-10 (svasva)

Available from: 2017-04-21 Created: 2017-04-21 Last updated: 2018-12-05Bibliographically approved
Mundry, S. M., Gajetski, M. & Hoseinie, H. (2017). Productivity drives longwall automation. Coal International, 265(2), 22-25
Open this publication in new window or tab >>Productivity drives longwall automation
2017 (English)In: Coal International, ISSN 1357-6941, Vol. 265, no 2, p. 22-25Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Tradelink Publications, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63544 (URN)2-s2.0-85019168574 (Scopus ID)
Available from: 2017-05-26 Created: 2017-05-26 Last updated: 2018-11-19Bibliographically approved
Ghodrati, B., Hoseinie, H. & Kumar, U. (2016). Lean mining. In: Torbjørn H Netland; Daryl J Powell (Ed.), The Routledge companion to lean management: (pp. 302-310). New York: Routledge
Open this publication in new window or tab >>Lean mining
2016 (English)In: The Routledge companion to lean management / [ed] Torbjørn H Netland; Daryl J Powell, New York: Routledge, 2016, p. 302-310Chapter in book (Refereed)
Place, publisher, year, edition, pages
New York: Routledge, 2016
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-64810 (URN)10.4324/9781315686899 (DOI)2-s2.0-85021058997 (Scopus ID)9781317416517 (ISBN)9781138920590 (ISBN)
Available from: 2017-07-06 Created: 2017-07-06 Last updated: 2017-11-24Bibliographically approved
Morshedlou, A., Dehghani, H. & Hoseinie, H. (2016). Maintenance-based production risk analysis in longwall mines (ed.). Mining Technology
Open this publication in new window or tab >>Maintenance-based production risk analysis in longwall mines
2016 (English)In: Mining Technology, ISSN 1474-9009, E-ISSN 1743-2863Article in journal (Refereed) Accepted
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-9353 (URN)7f429dea-0018-4f42-8266-c9478429308c (Local ID)7f429dea-0018-4f42-8266-c9478429308c (Archive number)7f429dea-0018-4f42-8266-c9478429308c (OAI)
Note

Upprättat; 2015; 20151130 (hadhos)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-04-26
Lanke, A., Hoseinie, H. & Ghodrati, B. (2016). Mine production index (MPI)-extension of OEE for bottleneck detection in mining (ed.). International Journal of Mining Science and Technology, 26(5), 753-760
Open this publication in new window or tab >>Mine production index (MPI)-extension of OEE for bottleneck detection in mining
2016 (English)In: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 26, no 5, p. 753-760Article in journal (Refereed) Published
Abstract [en]

Although mining production depends on various equipments, significant amount of production loss can be attributed a specific equipment or fleet. Bottleneck is defined not only by production loss but also by our satisfaction from the equipment. The user satisfaction could be measured as machine effectiveness. Mining literature on performance improvement and optimization of equipment operations assert importance of availability, utilization and production performance as key parameters. These three parameters are useful for evaluating effectiveness of equipment. Mine production index (MPI), which can represent the effect of these factors, has been applied for continuous operation in mining. MPI uses Fuzzy Delphi Analytical Hierarchy Process to determine importance of each three parameter for individual equipment. A case study in a Swedish open pit mine was done to evaluate the field application of MPI. The results reveal that crusher is the bottleneck equipment in studied mine. As a methodical approach, an algorithm which uses MPI and detects bottleneck in continuous mining operation has been proposed.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-14320 (URN)10.1016/j.ijmst.2016.05.050 (DOI)000383712400002 ()2-s2.0-85006335485 (Scopus ID)dac441fb-01e7-4abb-8794-deb04c2d27fc (Local ID)dac441fb-01e7-4abb-8794-deb04c2d27fc (Archive number)dac441fb-01e7-4abb-8794-deb04c2d27fc (OAI)
Note

Validerad; 2016; Nivå 1; 20151130 (hadhos)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Hamodi, H., Hoseinie, H. & Lundberg, J. (2016). Monte Carlo Reliability Simulation of Underground Mining Drilling Rig (ed.). In: (Ed.), Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde (Ed.), Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective. Paper presented at International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015 (pp. 633-643). : Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Monte Carlo Reliability Simulation of Underground Mining Drilling Rig
2016 (English)In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 633-643Conference paper, Published paper (Refereed)
Abstract [en]

Drilling rigs are widely used in mine development or construction and tunnel engineering projects. The rig consists of 12 subsystems in a series configuration and can be driven by diesel or electrical engines. This paper uses the Kamat-Riley (K-R) event-based Monte Carlo simulation method to perform reliability analysis of an underground mine drilling rig. For data analysis and to increase statistical accuracy, the paper discusses three case studies in an underground mine in Sweden. Researchers built a process to programme the simulation process and used MATLABTM software to run simulations. The results showed the simulation approach is applicable to the reliability analysis of this rig. Moreover, the reliability of all rigs reaches almost zero value after 50 h of operation. Finally, the differences between the reliability of the studied fleet of drilling rigs are a maximum 10 %. Therefore, all maintenance or spare part planning issues can be managed in a similar way

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2016
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-40121 (URN)10.1007/978-3-319-23597-4_46 (DOI)f1cf544e-5618-4af2-adba-8b7120f23fe0 (Local ID)978-3-319-23596-7 (ISBN)978-3-319-23597-4 (ISBN)f1cf544e-5618-4af2-adba-8b7120f23fe0 (Archive number)f1cf544e-5618-4af2-adba-8b7120f23fe0 (OAI)
Conference
International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015
Note
Godkänd; 2016; Bibliografisk uppgift: Containing selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden, collected by editors with years of experiences in Reliability and maintenance modeling, risk assessment, and asset management, this work maximizes reader insights into the current trends in Reliability, Availability, Maintainability and Safety (RAMS) and Risk Management. Featuring a comprehensive analysis of the significance of the role of RAMS and Risk Management in the decision making process during the various phases of design, operation, maintenance, asset management and productivity in Industrial domains, these proceedings discuss key issues and challenges in the operation, maintenance and risk management of complex engineering systems and will serve as a valuable resource for those in the field. ; 20151223 (andbra)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved
Ghodrati, B., Famurewa, S. M. & Hoseinie, H. (2016). Railway switches and crossings reliability analysis. In: 2016 IEEE International Conference on Industrial Engineering and Engineering Management: . Paper presented at IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bali, 4-7/12 2016 (pp. 1412-1416). , 2016-December, Article ID 7798110.
Open this publication in new window or tab >>Railway switches and crossings reliability analysis
2016 (English)In: 2016 IEEE International Conference on Industrial Engineering and Engineering Management, 2016, Vol. 2016-December, p. 1412-1416, article id 7798110Conference paper, Published paper (Refereed)
Abstract [en]

Switches and crossings (S&Cs) connect the rail network, guiding trains from one track to another and supporting path crossing. They are critical systems given the frequency of their functional failure and the consequences on the operation, cost and safety of railway transportation. Reliability studies are required to support the transport objective of providing dependable, sustainable and cost effective transportation. The main objective of this study is to assess the reliability characteristics of S&Cs based on field data collection. As field failure data have censored nature, commercial packages have not been satisfactory for processing them; therefore, the study uses a special statistical software package RDAT® (Reliability Data Analysis Tool). The availability of the studied switches and crossings is estimated based on the estimated reliability characteristics. The results show the availability of the S&Cs varies between x and y. This is useful information, as it helps the contractor plan and schedule maintenance. It also helps the asset owner to identify units whose performance is below the desired target and to make replacement decisions.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-62810 (URN)10.1109/IEEM.2016.7798110 (DOI)000392208100287 ()2-s2.0-85009868507 (Scopus ID)978-1-5090-3665-3 (ISBN)
Conference
IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bali, 4-7/12 2016
Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2018-06-25Bibliographically approved
Rahimdel, M. J., Hoseinie, H. & Ghodrati, B. (2016). Ram analysis of rotary drilling machine. Mining Science, 23, 77-89
Open this publication in new window or tab >>Ram analysis of rotary drilling machine
2016 (English)In: Mining Science, ISSN 2300-9586, Vol. 23, p. 77-89Article in journal (Refereed) Published
Abstract [en]

Rotary drilling machines are the most common machines used for drilling the blast holes in mining and constructions activities. The vital role of drilling operation in mining activities reveals that, the performance analysis of drilling machines and their failure and repair behaviors are essential. There-fore, the present study focuses on the reliability, availability and maintainability (RAM) of drilling ma-chines. In this paper, four rotary drilling machines at Sarcheshmeh Copper Mine in Iran are considered for repair and failure data collection. RAM analysis of drilling machines is done using Markov Approach. Results show that the reliability of drilling fleet is decreased by 0.67% in per hour drilling. The hydraulic system is the main unavailability reason of all machines. Moreover, the most failures of the two newest machines are completely repaired in 25 hours

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-61136 (URN)10.5277/msc162307 (DOI)2-s2.0-84996503837 (Scopus ID)
Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2017-11-24Bibliographically approved
Hoseinie, S. H., Kumar, U. & Ghodrati, B. (2016). Reliability Centered Maintenance (RCM) for Automated Mining Machinery (ed.). Paper presented at . Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Reliability Centered Maintenance (RCM) for Automated Mining Machinery
2016 (English)Report (Other academic)
Abstract [en]

Reliability centered maintenance (RCM) was initiated on 1960s in Boeing company to optimize the maintenance process of aircrafts. Since that date, this method has been applied in wide range of industries and has provided a completely positive results and recommendations for implementation in other industries. RCM is a systematic approach to quantitatively assess and optimize the performance of preventive maintenance tasks and to eliminate non-value adding maintenance actions. It provides considerable cost savings due to optimum maintenance effort, increased safety and productivity. This research considers the feasibility of applying the RCM methodology to fully-automated underground mining machineries as one of the vital requirement of early future modern mining. For this purpose, a literature review has been done to clarify the advantages, requirements, issues and challenges of RCM in other industries such as aviation, marine, nuclear, oil and gas, and process industries. It has been tried to analyze the RCM procedure in detailed and to have a look on the adoption issues and requirement for RCM implementation in fully-automated mining. Mainly, in this research, following RCM documents and standards were used for feasibility study: • Classic RCM in Aviation industry (SAE-JA1011, SAE-JA1012)• NASA RCM guidelines • USA’s military standards MIL-STD-2173• International Atomic Energy Agency (IAEA) RCM documentUsing the above mentioned documents, an implementation issues and challenges in developing a RCM program for fully-automated underground mining machineries has been presented. The result of this study shows that RCM is applicable in maintenance planning for fully-automated underground mining machinery. Because, serious safety restrictions are associated with this kind of mining operation and RCM can properly help the engineers to analyze the safety consequences of any failure and make the best decision for maintenance tasks. However, practical application of RCM has some differences in mining context which in this project are discussed in detail. The investigations show the risk priority number is the suitable measure to select the RCM target component/system. Since, there is no operation in site, detective the some evident failures are become impossible in automated mining. Therefore, we have to consider the smartness level and capabilities of agent-based supervisors to get the real feeling of machinery health and operation condition. Internet of Thing platforms are also required in fully automated mine to develop the machine-to-machine communication and to reduce the risk of failures and failure propagation in fleet level. RCM could apply the outcomes of these advanced technologies to optimize the maintenance actions in automated mines.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2016. p. 76
Series
Project Report
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-21850 (URN)072f2cbe-9d01-4b4f-ab3c-08222f612fd9 (Local ID)978-91-7583-555-6 (ISBN)978-91-7583-556-3 (ISBN)072f2cbe-9d01-4b4f-ab3c-08222f612fd9 (Archive number)072f2cbe-9d01-4b4f-ab3c-08222f612fd9 (OAI)
Note
Godkänd; 2016; Bibliografisk uppgift: VINNOVA SIP-STRIM; 20160316 (hadhos)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Lanke, A., Ghodrati, B. & Hoseinie, H. (2016). Uncertainty Analysis of Production in Open Pit Mines: Effect of environmental conditions. Archives of Mining Sciences
Open this publication in new window or tab >>Uncertainty Analysis of Production in Open Pit Mines: Effect of environmental conditions
2016 (English)In: Archives of Mining Sciences, ISSN 0860-7001, E-ISSN 1689-0469Article in journal (Refereed) Submitted
Abstract [en]

Production volume by mining equipment is influenced by internal and external parameters. External parameters include weather conditions, human factors etc. This study shows impact of temperature, rainfall and snowfall on production volume achieved under influence of these factors in open pit mine.  The case study is carried out which include data from weather station near an open pit mine and production tonnage. Multi regression modelling in performed using stated factors and production volume.  It was observed that Snowfall and rainfall has impact on production volume. Temperature has no effect on payload achieved as represented by model. With increasing snowfall and rainfall decreases. Higher snowfall (0.8 meter to 1 meter) although has tends to lead higher tonnage compared to low snowfall (0 to 0.8meters). Rainfall causes decrease in production of ore, with increase in rainfall from 1.2 mm, there is sharp decrease in production volume. The optimization table shows that with either no snowfall coupled with maximum rainfall (39 mm) it is possible to achieve production levels of 120 thousand per day. With high snowfall (1.06 metres) and no rainfall, it is possible to achieve maximum of 118 thousand tonnes per day.

National Category
Other Engineering and Technologies Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-61122 (URN)
Projects
CAMM
Available from: 2016-12-16 Created: 2016-12-16 Last updated: 2017-11-29
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