| 1. |
- Asbjörnsson, Gauti, 1985, et al.
(författare)
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Modelling of Discrete Downtime in Continuous Crushing Operation
- 2016
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Ingår i: Minerals Engineering. - : Elsevier BV. - 0892-6875. ; 98, s. 22-29
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Tidskriftsartikel (refereegranskat)abstract
- © 2016 Elsevier Ltd Crushing is a harsh process and production units are subjected to wear and failure over time which will reduce the overall performance of the plant. To achieve optimum process performance, both time dependant process dynamics and operating conditions should be taken into account. In this paper the aim is to simulate the process from a more operational perspective to evaluate process performance and process optimum for different operations. The objective is to model and simulate the discrete phenomena that can cause the process to alter performance and implement it with dynamic process simulations. An approach for combining discrete event simulations with time-dependent simulations for process evaluation and optimization is presented. The proposed approach demonstrates a systematic way to evaluate the process performance and locating optimum process configuration, for a given condition. The developed models can be used to optimize different aspects of the operation depending on the defined objective function and the system boundaries. Optimization of process throughput by manipulating configuration of both the grizzly and the crushers, as well as the time between calibrations has been illustrated in this paper. Adjusting the process continuously and calibrating it at the appropriate time can have major benefits when it comes to the process availability and utilization, increasing performance by 4.1–9.3% in these cases. Evaluation of process robustness and availability with regards to process specific factors and variation gave an indication of the process and unit performance under a long operating period. By combining discrete and dynamic simulation, a higher simulation fidelity can be achieved to provide a more operational perspective to the optimization and process analysis.
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| 2. |
- Asbjörnsson, Gauti, 1985, et al.
(författare)
-
Modelling of Discrete Downtime in Continuous Crushing Operation
- 2015
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Ingår i: Computational Modelling 2015, MEI conference.
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Konferensbidrag (refereegranskat)abstract
- Crushing is a harsh process and production units are subjected to wear and failure over time which will reduce the overall performance of the plant. To achieve optimum process performance, both time dependant process dynamics and operating conditions should be taken into account.In this paper the aim is to create a framework for simulating the process from a more operational perspective to evaluate process performance and process optimum for different operational scenarios. The objective is to model and simulate the discrete phenomena that can cause the process to alter performance and implement it with dynamic process simulations. A method for combining discrete probability simulations with time-continuous simulations for process evaluation and optimization is presented. The proposed framework demonstrates a systematic approach to evaluate the process performance and locating optimum process configuration, for a given condition. The developed models can be used to optimize different aspects of the operation depending on the defined objective function and the system boundaries. Optimization of process throughput by manipulating configuration of both the grizzly and the crushers, as well as the time between calibrations has been illustrated in this paper. Adjusting the process continuously and calibrating it at the appropriate time can have major benefits when it comes to the process availability and utilization, increasing performance by 4.1-9.3 % in these cases. Evaluation of process robustness with regards to different maintenance strategies and process variation gave an indication of the process and unit performance under a long operating period. By combining discrete and dynamic simulation, a higher simulation fidelity can be achieved to provide a more operational perspective to the optimization and process analysis.
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| 3. |
- Bengtsson, Lars, et al.
(författare)
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Hydrology of transport systems
- 2017
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Ingår i: Handbook of Applied Hydrology, Second Edition. - 9780071835091
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Bokkapitel (refereegranskat)
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| 4. |
- Bengtsson, Magnus, 1973, et al.
(författare)
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ADVANCED MATERIAL MODELLING IN CRUSHING PLANTS USING REAL TIME ALGORITHMS
- 2015
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Ingår i: Computational Modelling 2015, MEI conference.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In process control of crushing plants the traditional control is focused on stability control ofsingle machines and not on controlling material utilization. The reason for this is that the use ofmaterial property models is not that well known. The material models describe properties as e.g.capacity over time for a given product and this may depend on many parameters and dynamic effectsin the process. Due to this it is complicated to model and thus a methodology is needed to solve thisproblem. In this paper a novel method for modeling the current effect that the production units haveon the material presented. The paper presents a methodology how to use process data from SCADAsystem to analyze and suggest dynamic material model properties in real time.
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| 5. |
- Bengtsson, Magnus, et al.
(författare)
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An empirical model for predicting flakiness in cone crushing
- 2006
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Ingår i: International Journal of Mineral Processing. - : Elsevier BV. - 0301-7516 .- 1879-3525. ; 79:1, s. 49-60
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Tidskriftsartikel (refereegranskat)abstract
- A fundamental understanding of the factors influencing particle shape is of central importance for optimisation of the output quality from crushing plants for aggregate production. The literature reports that the wear on and setting of a cone crusher influence particle shape, The fact that wear on and the setting of a cone crusher influence particle shape is considered common knowledge and is also reported in the literature. To date, no mathematical model for predicting particle shape has been presented. A novel model capable of predicting aggregate shape is presented in this paper. The particle flakiness model has two parameters: the average particle size of the feed and the closed side setting (CSS) of the crusher. A common method used for controlling the process flow in a crushing plant is also demonstrated. Detailed process knowledge is important in order to minimize the circulating load whilst still maximizing product quality. The model shows that the flakiness of the product can be estimated with knowledge of the following two parameters: CSS and the average particle size of the feed. Additional investigations are needed to improve the precision of the model.
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| 6. |
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| 7. |
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| 8. |
- Bengtsson, Magnus, et al.
(författare)
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Comparative Study of Optimization Schemes in Mineral Processing Simulations
- 2018
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Konferensbidrag (refereegranskat)abstract
- Modelling and simulations for mineral processing plants have been successful in replicating and predicting predefined scenarios of an operating plant. However, there is a need to explore and increase the potential of such simulations to make them attractive for users. One of the tools to increase the attractiveness of the simulations is through applying optimization schemes. Optimization schemes, applied on mineral processing simulations, can identify non-intuitive solutions for a given problem. The problem definition itself is subjective in nature and is dependent on the purpose of the operating plant.The scope of this paper is to demonstrate two optimization schemes: Multi-Objective Optimization (MOO) using a Genetic Algorithm (GA) and Multi-Disciplinary Optimization (MDO) using an Individual Discipline Feasible (IDF) approach. A two stage coarse comminution plant is used as a case plant to demonstrate the applicability of the two optimization schemes. The two schemes are compared based on the problem formulations, types of result and computation time. Results show that the two optimization schemes are suitable in generating solutions to a defined problem and both schemes can be used together to produce complementary results.
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| 9. |
- Bengtsson, Magnus, 1973, et al.
(författare)
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Cost And Performance Optimization Of A Tertiary Crushing Stage
- 2015
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Ingår i: ESCC 2015 Conference. - Göteborg : Chalmers University of Technology. - 9789188041012
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Konferensbidrag (refereegranskat)abstract
- There is increasing demand to optimise performance and profit of crushing plants. Research in this area has resulted in the development of numerous optimisation tools, and resent research has shown that the quality aspects of production have great influence on the optimisation results. The quality, cost, profit and capacity of a product is influenced by several parameters, and in order to control all of these parameters it is necessary to use some sort of optimisation software. In this paper, a novel approach use the parameters cost, profit, capacity and quality in order to perform a multi objective optimization of a crushing plant is presented. As an example a tertiary crushing stage consistent of a cone crusher and a vertical shaft impact crusher (VSI) is used as base for the designed objective function. The process has a given set of constraints that represents the conditions normal in these type of crushing applications. The first step in this paper is to identify if the range of the constraints can cause undesirable production costs when reaching for a given product property. The next step in the optimization shows how a strategy for relaxing constraint can increase overall productivity and still reach certain product properties. The conclusions made in this work are that multi objective optimization is essential when optimizing crushing plant production against multiple objectives. Relaxation of constraints can increase the overall performance of the crushing plant.
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| 10. |
- Bengtsson, Magnus, 1973, et al.
(författare)
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Framework for material modelling in a processing plant
- 2015
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Ingår i: Computational Modelling ‘15.
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Konferensbidrag (refereegranskat)abstract
- Material modelling within a crushing plant is closely dependent on both manual and automatic operations as well as a close follow up on the utilization of the plant performance from a management perspective. The desire to fully be able to utilize the crushing plant with respect e.g. to material handling is limited due to the lack of possibility to fully observe actions within the process. There are large quantities of data that can be monitored in the crushing plant SCADA system. However the data collected are governed by the quantity of actual sensors in the process. The aim with this paper is to propose a method for how-to pre-process the automatically gathered SCADA data in order to fill up dynamic models for process simulations. There is a fundamental need to increase the resolution of how the crushing plant behaves. This will be structured as a framework for analysing and suggesting model improvements that will increase the utilization and decrease both manual operations and give better performance when controlling the process.
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