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Ahmadzadeh, Farzaneh
Publications (9 of 9) Show all publications
Ahmadzadeh, F. & Lundberg, J. (2014). Remaining useful life estimation: Review (ed.). Paper presented at . International Journal of Systems Assurance Engineering and Management, 5(4), 461-474
Open this publication in new window or tab >>Remaining useful life estimation: Review
2014 (English)In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 4, p. 461-474Article in journal (Refereed) Published
Abstract [en]

This paper reviews the recent modelling developments in estimating the remaining useful life (RUL) of industrial systems. The RUL estimation models are categorized into experimental, data driven, physics based and hybrid approaches. The paper reviews some typical approaches and discusses their advantages and disadvantages. According to the literature, the selection of the best model depends on the level of accuracy and availability of data. In cases of quick estimations which are less accurate, the data driven method is preferred, while the physics based approach is applied when the accuracy of estimation is important.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-3684 (URN)10.1007/s13198-013-0195-0 (DOI)2-s2.0-84906985371 (Scopus ID)18262585-14db-463d-a19a-4e5ef3bb435d (Local ID)18262585-14db-463d-a19a-4e5ef3bb435d (Archive number)18262585-14db-463d-a19a-4e5ef3bb435d (OAI)
Note
Validerad; 2014; 20130708 (farahm)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Ahmadzadeh, F. & Lundberg, J. (2013). Application of multi regressive linear model and neural network for wear prediction of grinding mill liners (ed.). Paper presented at . International Journal of Advanced Computer Sciences and Applications, 4(5), 53-58
Open this publication in new window or tab >>Application of multi regressive linear model and neural network for wear prediction of grinding mill liners
2013 (English)In: International Journal of Advanced Computer Sciences and Applications, ISSN 2158-107X, E-ISSN 2156-5570, Vol. 4, no 5, p. 53-58Article in journal (Refereed) Published
Abstract [en]

The liner of an ore grinding mill is a critical component in the grinding process, necessary for both high metal recovery and shell protection. From an economic point of view, it is important to keep mill liners in operation as long as possible, minimising the downtime for maintenance or repair. Therefore, predicting their wear is crucial. This paper tests different methods of predicting wear in the context of remaining height and remaining life of the liners. The key concern is to make decisions on replacement and maintenance without stopping the mill for extra inspection as this leads to financial savings. The paper applies linear multiple regression and artificial neural networks (ANN) techniques to determine the most suitable methodology for predicting wear. The advantages of the ANN model over the traditional approach of multiple regression analysis include its high accuracy.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-4076 (URN)1f04f3d6-d8c2-46d1-9d6e-2c8187d0ec45 (Local ID)1f04f3d6-d8c2-46d1-9d6e-2c8187d0ec45 (Archive number)1f04f3d6-d8c2-46d1-9d6e-2c8187d0ec45 (OAI)
Note
Godkänd; 2013; 20130708 (farahm)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Ahmadzadeh, F., Lundberg, J. & Strömberg, T. (2013). Multivariate process parameter change identification by neural network (ed.). Paper presented at . The International Journal of Advanced Manufacturing Technology, 69(9-12), 2261-2268
Open this publication in new window or tab >>Multivariate process parameter change identification by neural network
2013 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 69, no 9-12, p. 2261-2268Article in journal (Refereed) Published
Abstract [en]

Whenever there is an out-of-control signal in process parameter control charts, maintenance engineers try to diagnose the cause near the time of the signal which is not always lead to prompt identification of the source(s) of the out-of-control condition and this in some cases yields to extremely high monetary loses for manufacture owner. This paper applies multivariate exponentially weighted moving average (MEWMA) control charts and neural networks to make the signal identification more effective. The simulation of this procedure shows that this new control chart can be very effective in detecting the actual change point for all process dimension and all shift magnitudes considered. This methodology can be used in manufacturing and process industries to predict change points and expedite the search for failure causing parameters, resulting in improved quality at reduced overall cost. This research shows development of MEWMA by usage of neural network for identifying the step change point and the variable responsible for the change in the process mean vector.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-12696 (URN)10.1007/s00170-013-5200-x (DOI)000327095900030 ()2-s2.0-84892371787 (Scopus ID)bdbcaab3-37f3-415c-9607-e6abe6dde418 (Local ID)bdbcaab3-37f3-415c-9607-e6abe6dde418 (Archive number)bdbcaab3-37f3-415c-9607-e6abe6dde418 (OAI)
Note
Validerad; 2013; 20130708 (farahm)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Ahmadzadeh, F. & Lundberg, J. (2013). Remaining useful life prediction of grinding mill liners using an artificial neural network (ed.). Paper presented at . Minerals Engineering, 53, 1-8
Open this publication in new window or tab >>Remaining useful life prediction of grinding mill liners using an artificial neural network
2013 (English)In: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 53, p. 1-8Article in journal (Refereed) Published
Abstract [en]

Knowing the remaining useful life of grinding mill liners would greatly facilitate maintenance decisions. Now, a mill must be stopped periodically so that the maintenance engineer can enter, measure the liners’ wear, and make the appropriate maintenance decision. As mill stoppage leads to heavy production losses, the main aim of this study is to develop a method which predicts the remaining useful life of the liners, without needing to stop the mill. Because of the proven ability of artificial neural networks (ANNs) to recognize complex relationships between input and output variables, as well as its adaptive and parallel information-processing structure, an ANN has been designed based on the various process parameters which influence wear of the liners. The process parameters were considered as inputs while remaining height and remaining life of the liners were outputs. The results show remarkably high degree of correlation between the input and output variables. The performance of the neural network model is very consistent for data used for training (seen) and testing (unseen).

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-7583 (URN)10.1016/j.mineng.2013.05.026 (DOI)000328522900001 ()2-s2.0-84881297898 (Scopus ID)5f78a5ae-8f42-4412-b99e-d092e5024ffa (Local ID)5f78a5ae-8f42-4412-b99e-d092e5024ffa (Archive number)5f78a5ae-8f42-4412-b99e-d092e5024ffa (OAI)
Note
Validerad; 2013; 20130708 (farahm)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Asl, A. G. & Ahmadzadeh, F. (2013). Risk prioritization based on health, safety and environmental factors by using fuzzy FMEA (ed.). Paper presented at International Journal Conference on Industrial, Mechanical and Manufacturing Engineering : 17/08/2013 - 18/08/2013. , 1(4), 233-237
Open this publication in new window or tab >>Risk prioritization based on health, safety and environmental factors by using fuzzy FMEA
2013 (English)In: Vol. 1, no 4, p. 233-237Article in journal (Refereed) Published
Abstract [en]

Failure Mode and Effects Analysis is assessing technique which relies to the rule of preventing failure, which is used to identify potential hazards. This method is used with minimum risks to predict the problems and deficits in design stage or development of the processes and services in organizations. The methods main principal is based on multiplying three main parameters: severity, occurrence, detection. This method with all the advantages still has minor disadvantages that in this paper attempts has been made to eliminate these deficiencies by fuzzification. Results show that fuzzy FMEA will enables us to evaluate situations correctly and precisely.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-29322 (URN)2c3b3c6a-10f6-42c6-87a3-29fb287a10b6 (Local ID)2c3b3c6a-10f6-42c6-87a3-29fb287a10b6 (Archive number)2c3b3c6a-10f6-42c6-87a3-29fb287a10b6 (OAI)
Conference
International Journal Conference on Industrial, Mechanical and Manufacturing Engineering : 17/08/2013 - 18/08/2013
Note
Godkänd; 2013; 20130814 (ysko); Konferensartikel i tidskriftAvailable from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Orand, S. M., Mirzazadeh, A. & Ahmadzadeh, F. (2012). Application of particle swarm optimization approach in the inflationary inventory model under stochastic conditions (ed.). In: (Ed.), Ramin Karim; Aditya Parida; Uday Kumar (Ed.), Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications. Paper presented at International Workshop and Congress on eMaintenance : 12/12/2012 - 14/12/2012 (pp. 125-130). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Application of particle swarm optimization approach in the inflationary inventory model under stochastic conditions
2012 (English)In: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet, 2012, p. 125-130Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2012
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-34861 (URN)92bd1a1d-8bd6-4ec2-8a91-6a1afbd0837b (Local ID)978-91-7439-539-6 (ISBN)92bd1a1d-8bd6-4ec2-8a91-6a1afbd0837b (Archive number)92bd1a1d-8bd6-4ec2-8a91-6a1afbd0837b (OAI)
Conference
International Workshop and Congress on eMaintenance : 12/12/2012 - 14/12/2012
Note
Godkänd; 2012; 20121214 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Ahmadzadeh, F., Ghodrati, B. & Kumar, U. (2012). Mean Residual Life Estimation Considering Operating Environment (ed.). Paper presented at International Conference on Quality, Reliability, Infocom Technology and Industrial Technology Management : 26/11/2012 - 28/11/2012. Paper presented at International Conference on Quality, Reliability, Infocom Technology and Industrial Technology Management : 26/11/2012 - 28/11/2012.
Open this publication in new window or tab >>Mean Residual Life Estimation Considering Operating Environment
2012 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

The cost of maintenance of mechanized and automated mining systems is too high necessitating efforts to enhance the effectiveness of maintenance systems and organization. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. This is essential for determining the Mean Residual Life (MRL) of systems so that maintenance tasks could be planned effectively. In this paper we used the statistical approach to estimate MRL. A Weibull proportional hazard model (PHM) with time-independent covariates was considered for modelling of the hazard function so that operating environment could be integrated in the reliability analysis. Methods are presented for calculating the conditional reliability function and computing the MRL as a function of the current conditions to guarantee the desired output. The model is verified and validated using data from the Hydraulic system of an LHD fleet from a Swedish mine. The results obtained from the analysis is useful to estimate the remaining useful life of such system which can be subsequently used for effective maintenance planning and help controlling unplanned stoppages of highly mechanized and automated systems.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-38557 (URN)cfcb9ed2-699b-4b95-b303-7997f5101125 (Local ID)cfcb9ed2-699b-4b95-b303-7997f5101125 (Archive number)cfcb9ed2-699b-4b95-b303-7997f5101125 (OAI)
Conference
International Conference on Quality, Reliability, Infocom Technology and Industrial Technology Management : 26/11/2012 - 28/11/2012
Note
Godkänd; 2012; 20130513 (behzad)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved
Safari, J. & Ahmadzadeh, F. (2012). Multi-objective reliability allocation problem (ed.). In: (Ed.), Ramin Karim; Aditya Parida; Uday Kumar (Ed.), Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications. Paper presented at International Workshop and Congress on eMaintenance : 12/12/2012 - 14/12/2012 (pp. 131-136). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Multi-objective reliability allocation problem
2012 (English)In: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet, 2012, p. 131-136Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2012
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-30628 (URN)47e44481-fcde-44b0-a895-254eb64c50ff (Local ID)978-91-7439-539-6 (ISBN)47e44481-fcde-44b0-a895-254eb64c50ff (Archive number)47e44481-fcde-44b0-a895-254eb64c50ff (OAI)
Conference
International Workshop and Congress on eMaintenance : 12/12/2012 - 14/12/2012
Note
Godkänd; 2012; 20121214 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Ghodrati, B., Kumar, U. & Ahmadzadeh, F. (2012). Remaining useful life estimation of mining equipment: A case study (ed.). In: (Ed.), (Ed.), Proceedings of MPES 2012: . Paper presented at International Symposium on Mine Planning and Equipment Selection : 28/11/2012 - 30/11/2012.
Open this publication in new window or tab >>Remaining useful life estimation of mining equipment: A case study
2012 (English)In: Proceedings of MPES 2012, 2012Conference paper, Published paper (Refereed)
Abstract [en]

To ensure the production/output and customer satisfaction in mining sector the estimation of Remaining Useful Life of mining machineries is a prime. In this paper we used the reliability analysis in order to estimate an optimal mining equipment repair/replacement policy by estimating their remaining useful life. The proportional hazard model was used in reliability analysis to be realistic and take the operational influencing factors in calculation. Methods are presented for calculating the conditional reliability function and computing the remaining useful life (RUL) as a function of the current conditions to guarantee the desired output. The model is applied in the hydraulic jack unit of LHD machine in an underground mine in Sweden. A Weibull proportional hazard model (PHM) with time-independent covariates was considered for the hazard function in an illustration of the proposed model. Presented results can be used, e.g. for developing of preventive maintenance plan or replacement intervals based on the conditional probability of failure or RUL.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-32391 (URN)6e3bce6b-c03c-4297-a97b-a488dce054c8 (Local ID)6e3bce6b-c03c-4297-a97b-a488dce054c8 (Archive number)6e3bce6b-c03c-4297-a97b-a488dce054c8 (OAI)
Conference
International Symposium on Mine Planning and Equipment Selection : 28/11/2012 - 30/11/2012
Note
Godkänd; 2012; 20130521 (ysko)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
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