Linearization of a Coal Blending Process Control System

Kalinowski, Krzysztof; Kaula, R.

doi:10.1016/s1474-6670(17)30136-2

Cited by 1 publication

(1 citation statement)

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“…The advanced technologies of the fourth industrial revolution are also applied in blending processes: big data solutions [6], real-time image analyses and process monitoring [46], in-line monitoring using spectroscopy [47,48], digital simulation using Matlab and Simulink tools to maximize the tonnage of coal blends [9], thermogravimetry and Fourier transform infrared spectroscopy [49], automated on-line monitoring of near infrared spectroscopy [50,51], scanning electron microscopy and wide-angle X-ray scattering [52], simulation to validate the efficiency of optical image encryption [53], an adaptive sample space expansion approach for in-situ measurement in blending processes [54], NIR spectroscopy to determine the homogeneity and drug content of blends [55,56], laser-induced breakdown spectroscopy [57], control system linearization for coal blending process with one controlled component flow [58], intelligent tuning and adaptive control [4].…”

Section: Content Analysismentioning

confidence: 99%

Supply Chain Design for Blending Technologies

Bányai

Veres

2022

Sustainability

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When optimizing blending technologies, the main objective is to determine the right mixing ratio of the raw materials, depending on the different qualities and costs of the raw materials available. It can be concluded that research is mainly focused on answering technological questions, and only very few studies take into account the logistics processes related to blending technologies, their design, cost-efficiency, utilization and sustainability including energy efficiency and environmental impact. Based on this fact, within the frame of this research the authors describe a new approach, extending the basic model of blending problems by adding new supply chain efficiency-related components that makes it possible to take logistics parameters related to the raw materials supply (available stocks, batch sizes, transport and storage costs, supply chain structure) into consideration. A mathematical model of this supply chain optimization problem for blending technologies is described including routing and assignment problems in the supply chain, while technological objectives are also taken into consideration as technological objective functions and constraints. The optimization problem described in the model is a problem with non-deterministic polynomial-time hardness (NP-hard), which means that there are no known efficient analytical methods to solve the logistics-related supply chain optimization of blending technologies. As a solution algorithm, the authors have used an evolutive solver and a new metrics, which improved the efficiency of the comparison of distances between solutions of routing problems represented by permutation arrays. The scenario analysis, which focuses on the integrated optimization of technological and logistics problems validates the model and evaluates the solution algorithm and the new metrics. Using the mentioned algorithm, the supply chain processes of the blending technologies can be improved from availability, efficiency, sustainability point of view.

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