Optimization Framework for Crushing Plants
Licentiatavhandling, 2019
To understand the complexity and to replicate the process performance of the coarse comminution and classification processes, process simulation models have been under development for the past few decades. There are two types of process simulation models: steady-state simulation and dynamic simulation. The steady-state simulation models are based on instantaneous mass balancing while the dynamic simulation models are capable of capturing the process change over time due to non-ideal operating conditions. Both simulation types are capable of capturing the process performance, although the dynamic process simulations have been proven to have a higher fidelity for industrial applications. Both the steady-state and dynamic simulation models lack the capability of optimization methods which can potentially increase the utilization of the developed process simulation models. The optimization capabilities can further increase the functionality of the process simulation models and provide decision-making support.
The thesis presents a modular optimization framework for carrying out process optimization and process improvements in a coarse comminution and classification process using process simulation models. The thesis describes the results of explorative studies carried out for developing the application of optimization methods and key performance indicators for the coarse comminution and classification process. The application of the optimization methods can generate new insights about the process performance with respect to the operating parameters, and non-intuitive results. The application of the key performance indicators can be used to carry out process diagnostics and process improvement activities. As a conclusion, a conceptual framework for carrying out optimization procedure within the coarse comminution and classification process is presented. The development of the optimization system and performance measuring system can be useful for process optimization and process improvements for industrial applications.
Minerals Processing
Industry 4.0
Multi-Objective Optimization (MOO)
Screening
Process Optimization
Process Improvement
Modelling
Comminution
Key Performance Indicators (KPIs)
Classification
Multi-Disciplinary Optimization (MDO)
Crushing
Dynamic Simulations
Författare
Kanishk Bhadani
Chalmers, Industri- och materialvetenskap, Produktutveckling
State of the Art in Application of Optimization Theory in Minerals Processing
European Symposium on Comminution and Classification, Izmir, Turkey,;(2017)
Övrigt konferensbidrag
Application of multi-disciplinary optimization architectures in mineral processing simulations
Minerals Engineering,;Vol. 128(2018)p. 27-35
Artikel i vetenskaplig tidskrift
Comparative Study of Optimization Schemes in Mineral Processing Simulations
IMPC 2018 - 29th International Mineral Processing Congress,;Vol. 2019(2019)p. 464-473
Paper i proceeding
Ämneskategorier
Mineral- och gruvteknik
Maskinteknik
Produktionsteknik, arbetsvetenskap och ergonomi
Drivkrafter
Hållbar utveckling
Styrkeområden
Produktion
Utgivare
Chalmers
Virtual Development Laboratory (VDL), Chalmers Tvärgata 4C
Opponent: Dr. Mats Lindqvist, FLSmidth & Co. A/S