| 1. |
- Al-Chalabi, Hussan, Associate Senior Lecturer, 1972-, et al.
(author)
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Time Series Forecasting using ARIMA Model : A Case Study of Mining Face Drilling Rig
- 2018
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In: ADVCOMP 2018. - : International Academy, Research and Industry Association (IARIA). ; , s. 1-3
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Conference paper (peer-reviewed)abstract
- This study implements an Autoregressive Integrated Moving Average (ARIMA) model to forecast total cost of a face drilling rig used in the Swedish mining industry. The ARIMA model shows different forecasting abilities using different values of ARIMA parameters (p, d, q). However, better estimation for the ARIMA parameters is required for accurate forecasting. Artificial intelligence, such as multi objective genetic algorithm based on the ARIMA model, could provide other possibilities for estimating the parameters. Time series forecasting is widely used for production control, production planning, optimizing industrial processes and economic planning. Therefore, the forecasted total cost data of the face drilling rig can be used for life cycle cost analysis to estimate the optimal replacement time of this rig.
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| 2. |
- Al-Douri, Yamur K., et al.
(author)
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Risk-based life cycle cost analysis using a two-level multi-objective genetic algorithm
- 2020
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In: International journal of computer integrated manufacturing (Print). - : Taylor & Francis. - 0951-192X .- 1362-3052. ; 33:10-11, s. 1076-1088
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Journal article (peer-reviewed)abstract
- The aim of this study has been to develop a two-level multi-objective genetic algorithm (MOGA) to optimize risk-based LCC analysis to find the optimal maintenance replacement time for road tunnel ventilation fans. Level 1 uses a MOGA based on a financial risk model to provide different risk percentages, while level 2 uses a MOGA based on an LCC model to estimate the optimal fan replacement time. Our method is compared with the approach of using a risk-based LCC model. The results are promising, showing that the risk-based LCC offers the possibility of significantly reducing the maintenance costs of the ventilation system by optimising the replacement schedule by considering the risk costs. The risk-based LCC can be used with repairable components, making it applicable, useful and implementable within Swedish Transport Administration (Trafikverket). In this study, MOGA operators have selected the cost of maintenance and risk data through the previous levels using different ways to provide different possible solutions. A drawback of the MOGA based on a risk-based LCC model with regard to its estimation is that a late replacement period over 20-year period might increase the maintenance cost. Therefore, the MOGA does not provide a good solution for a risk-based LCC.
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| 3. |
- Al-Douri, Yamur K., et al.
(author)
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Time Series Forecasting using Genetic Algorithm : A Case Study of Maintenance Cost Data For Tunnel Fans
- 2018
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In: ADVCOMP 2018. - : International Academy, Research and Industry Association (IARIA). ; , s. 4-9
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Conference paper (peer-reviewed)abstract
- Time series forecasting is widely used as a basis for economic planning, production planning, production control and optimizing industrial processes. The aim of this study has been to develop a novel two-level Genetic Algorithm (GA) to optimize time series forecasting in order to forecast cost data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket). The first level of the GA is responsible for the process of forecasting time series cost data, while the second level evaluates the forecasting. The first level implements GA based on the Autoregressive integrated moving average (ARIMA) model. The second level utilizes a GA based on forecasting error rate to identify a proper forecasting. The results show that GA based on the ARIMA model produces better forecasting results for the labor cost data objects. It was found that a multi-objective GA based on the ARIMA model showed an improved performance. The forecasted data can be used for Life cycle cost (LCC) analysis.
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| 4. |
- Al-Chalabi, Hussan, et al.
(author)
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Case Study: Model for Economic Lifetime of Drilling Machines in the Swedish Mining Industry
- 2015
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In: The Engineering Economist. - 0013-791X .- 1547-2701. ; 60:2, s. 138-154
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Journal article (peer-reviewed)abstract
- The purpose of this paper is to develop a practical economic replacement decision model to identify the economic lifetime of a mining drilling machine. A data driven optimisation model was developed for operating and maintenance costs, purchase price and machine resale value. Equivalent present value of these costs by using discount rate was considered. The proposed model shows that the absolute optimal replacement time (ORT) of a drilling machine used in one underground mine in Sweden is 115 months. Sensitivity and regression analysis show that the maintenance cost has the largest impact on the ORT of this machine. The proposed decision making model is applicable and useful and can be implemented within the mining industry.
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| 5. |
- Al-Chalabi, Hussan, Associate Senior Lecturer, 1972-
(author)
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Development of an economic replacement time model for mining equipment: a case study
- 2022
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In: Life Cycle Reliability and Safety Engineering. - : Springer Nature. - 2520-1352 .- 2520-1360. ; 11:2, s. 203-217
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Journal article (peer-reviewed)abstract
- In mining operation equipment replacement represents a strategic decision problem. This paper presents an economic replacement time model for mining drill rigs. A total ownership cost minimization model was developed to optimize the lifetime of a drill rig used in Tara underground mine in Ireland. The developed methodology allows an innovative practical evaluation of the replacement process by applying sensitivity and regression analysis to rank the factors affecting the replacement time of existing and new models of the production drill rig. Compared to previous studies presented in the literature, the present study represents a further development in this field as it has resulted in a practical optimization model that can be used to estimate the economic replacement time of repairable equipment used in the mining and other production industries. The proposed model shows that the absolute economic replacement time of the drill rig investigated in this case study is 81 months and the mining company operating the rig can replace it with an identical one within an optimal replacement range of 6 months (i.e. from month 79–84) when the minimum total cost can still be achieved in practice. Sensitivity and regression analyses show that the maintenance cost has the largest impact on the economic replacement time of the drill rig. The study finds that decreasing the operating and maintenance costs of the drill rig will have the positive effect of increasing the economic replacement time linearly for a new model of the drill rig. The proposed model helps decision-makers to plan the replacement of old rigs and purchase new ones from an economic view point. Thus, this new model can be extended and used for more general applications in the mining industry.
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| 6. |
- Al-Chalabi, Hussan
(author)
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Life cycle cost analysis of the ventilation system in Stockholm's road tunnels
- 2018
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In: Journal of Quality in Maintenance Engineering. - : Emerald Group Publishing Limited. - 1355-2511 .- 1758-7832. ; 24:3, s. 358-375
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Journal article (peer-reviewed)abstract
- PurposeThis study developed a practical economic replacement decision model to identify the economic lifetime of the ventilation system used by Trafikverket in its Stockholm tunnels.Design/methodology/approachThe proposed data driven optimisation model considers operating and maintenance costs, purchase price and system resale value for a ventilation system consisting of 121 fans. The study identified data quality problems in Trafikverket’s MAXIMO database.FindingsIt found the absolute economic replacement time (ERT) of the ventilation system is 108 months but for a range of 100 to 120 months, the total cost remains almost constant. Sensitivity and regression analysis showed the operating cost has the largest impact on the ERT.Originality/valueThe results are promising; the company has the possibility of significantly reducing the LCC of the ventilation system by optimising its lifetime. In addition, the proposed model can be used for other systems with repairable components, making it applicable, useful, and implementable within Trafikverket more generally.
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| 7. |
- Al-Chalabi, Hussan S., et al.
(author)
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Downtime analysis of drilling machines and suggestions for improvements
- 2014
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In: Journal of Quality in Maintenance Engineering. - 1355-2511 .- 1758-7832. ; 20:4, s. 306-332
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Journal article (peer-reviewed)abstract
- Purpose– The purpose of this paper is to analyse and compare the downtime of four drilling machines used in two underground mines in Sweden. The downtime of these machines was compared to show what problems affect downtime and which strategies should be applied to reduce it.Design/methodology/approach– The study collects failure data from a two-year period for four drilling machines and performs reliability analysis. It also performs downtime analysis utilising a log-log diagram with a confidence interval.Findings– There are notable differences in the downtime of most of the studied components for all machines. The hoses and feeder have relatively high downtime. Depending on their downtime, the significant components can be ranked in three groups. The downtime of the studied components is due to reliability problems. The study suggests the need to improve the reliability of critical components to reduce the downtime of drilling machines.Originality/value– The method of analysing the downtime, identifying dominant factors and the interval estimation for the downtime, has never been studied on drilling machines. The research proposed in this paper provides a general method to link downtime analysis with potential component improvement. To increase the statistical accuracy; four case studies was performed in two different mines with completely different working environment and ore properties. Using the above method showed which components need to be improved and suggestions for improvement was proposed and will be implemented accordingly.
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| 8. |
- Castaño Arranz, Miguel, et al.
(author)
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A generic framework for data quality analytics
- 2020
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In: International Journal of COMADEM. - : COMADEM International. - 1363-7681. ; 23:1, s. 31-38
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Journal article (peer-reviewed)abstract
- The challenge of generalizing Data Quality assessment is hindered by the fact that Data Quality requisites depend on the purpose for which the data will be used and on the subjectivity of the data consumer. The approach proposed in this paper to address this challenge is to employ a semi-automated user-guided Data Quality assessment. This paper introduces a generic framework for data quality analytics which is mainly composed by a set of software units to perform semi-automated Data Quality analytics and a set of Graphical User Interfaces to enable the user to guide the Data Quality assessment. The framework has been implemented and can be customized according to the needs of the purpose and of the consumer. The framework has been instantiated in a case study on Long-hole drill rigs, where several Data Quality issues have been discovered and their root cause investigated.
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| 9. |
- Hoseinie, Seyed Hadi, et al.
(author)
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Comparison between Simulation and Analytical Methods in Reliability Data Analysis : A Case Study on Face Drilling Rigs
- 2018
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In: Data. - Switzerland : MDPI. - 2306-5729. ; 3:2
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Journal article (peer-reviewed)abstract
- Collecting the failure data and reliability analysis in an underground mining operation is challenging due to the harsh environment and high level of production pressure. Therefore, achieving an accurate, fast, and applicable analysis in a fleet of underground equipment is usually difficult and time consuming. This paper aims to discuss the main reliability analysis challenges in mining machinery by comparing three main approaches: two analytical methods (white-box and black-box modeling), and a simulation approach. For this purpose, the maintenance data from a fleet of face drilling rigs in a Swedish underground metal mine were extracted by the MAXIMO system over a period of two years and were applied for analysis. The investigations reveal that the performance of these approaches in ranking and the reliability of the studies of the machines is different. However, all mentioned methods provide similar outputs but, in general, the simulation estimates the reliability of the studied machines at a higher level. The simulation and white-box method sometimes provide exactly the same results, which are caused by their similar structure of analysis. On average, 9% of the data are missed in the white-box analysis due to a lack of sufficient data in some of the subsystems of the studies’ rigs.
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