The Experts below are selected from a list of 246 Experts worldwide ranked by ideXlab platform

A. Mariajayaprakash - One of the best experts on this subject based on the ideXlab platform.

  • Optimization of Process parameters through fuzzy logic and genetic algorithm - A case study in a Process industry
    Applied Soft Computing, 2015
    Co-Authors: A. Mariajayaprakash, T. Senthilvelan, R. Gnanadass
    Abstract:

    Sugar mill industry has been taken for investigation.Failures of the boiler during the co generation Process.Failures occur in the screw conveyor, drum feeder and grate.Critical parameters are identified by FMEA and fuzzy FMEA.Parameters are optimized by Taguchi method. Failures are minimized.Further optimized by Genetic algorithm. Failure free system has been obtained. The simultaneous generation of steam and power, which is commonly referred to as Cogeneration, has been adopted by many sugar mills in India to overcome the power shortage. It becomes an increasingly important source of income for sugar factories. The problems faced by the sugar mill industry arise mainly due to failures of either the complete system or some specific components during the Cogeneration Process. This paper presents the failure analysis of the boiler during the Cogeneration Process and provides solution to overcome these failures. The failures frequently occur in the screw conveyor and in the drum feeder of fuel feeding system and the grate of the boiler. In this research work, the statistical tools viz., Failure Mode and Effect Analysis (FMEA) and the Taguchi method have been applied to investigate and alleviate these failures. Since conventional FMEA has some limitations and Taguchi method does not give better solution, fuzzy FMEA has been employed to overcome the limitations and genetic algorithm technique has been applied to obtain failure - free system during the Cogeneration Process.

  • Optimizing Process Parameters of Screw Conveyor (Sugar Mill Boiler) Through Failure Mode and Effect Analysis (FMEA) and Taguchi Method
    Journal of Failure Analysis and Prevention, 2014
    Co-Authors: A. Mariajayaprakash, T. Senthilvelan
    Abstract:

    This paper exhibits the failures of the boiler during the Cogeneration Process and provides solution to overcome the failures. The failures are frequently occurring in the screw conveyor of fuel-feeding system of the boiler and rarely occurring in the grate of the boiler. In this research work, three important statistical tools are employed to identify and further rectify the failures of the screw conveyor. The different techniques, viz., cause-and-effect diagram, failure mode and effect analysis (FMEA), and the Taguchi method have been applied. The cause-and-effect diagram, is the primary tool used to sort out all the possible root causes of the failures. The Process parameters that cause the failures in the screw conveyor are identified by FMEA. Since the conventional FMEA has some limitations, fuzzy FMEA is employed. The most critical parameters selected by conventional FMEA and fuzzy FMEA are fuel type, fuel moisture, drum speed, and air flow. Finally, the selected Process parameters are optimized by the Taguchi method to prevent the failures occurring in the screw conveyor. Among the various Process parameters, the parameter, fuel type, significantly affects the performance of the screw conveyor.

  • failure detection and optimization of sugar mill boiler using fmea and taguchi method
    Engineering Failure Analysis, 2013
    Co-Authors: A. Mariajayaprakash, T. Senthilvelan
    Abstract:

    Abstract Sugar industry plays an important role in economic development of country. Cogeneration is an important source of income for sugar industries. Boiler is one of the essential components used in Cogeneration Process. Unscheduled boiler outages in sugar mills are major problem resulting loss of production. The boiler may be failed due to number of reasons; some of the reasons such as mechanical failure, electrical failure and temperature sensors failure. This paper describes the failures of the fuel feeding system frequently occurred in the Cogeneration boiler and gives the solution to rectify these failures by using three important tools, namely, cause and effect diagram, Failure Mode and Effect Analysis and Taguchi method.

T. Senthilvelan - One of the best experts on this subject based on the ideXlab platform.

  • Optimization of Process parameters through fuzzy logic and genetic algorithm - A case study in a Process industry
    Applied Soft Computing, 2015
    Co-Authors: A. Mariajayaprakash, T. Senthilvelan, R. Gnanadass
    Abstract:

    Sugar mill industry has been taken for investigation.Failures of the boiler during the co generation Process.Failures occur in the screw conveyor, drum feeder and grate.Critical parameters are identified by FMEA and fuzzy FMEA.Parameters are optimized by Taguchi method. Failures are minimized.Further optimized by Genetic algorithm. Failure free system has been obtained. The simultaneous generation of steam and power, which is commonly referred to as Cogeneration, has been adopted by many sugar mills in India to overcome the power shortage. It becomes an increasingly important source of income for sugar factories. The problems faced by the sugar mill industry arise mainly due to failures of either the complete system or some specific components during the Cogeneration Process. This paper presents the failure analysis of the boiler during the Cogeneration Process and provides solution to overcome these failures. The failures frequently occur in the screw conveyor and in the drum feeder of fuel feeding system and the grate of the boiler. In this research work, the statistical tools viz., Failure Mode and Effect Analysis (FMEA) and the Taguchi method have been applied to investigate and alleviate these failures. Since conventional FMEA has some limitations and Taguchi method does not give better solution, fuzzy FMEA has been employed to overcome the limitations and genetic algorithm technique has been applied to obtain failure - free system during the Cogeneration Process.

  • Optimizing Process Parameters of Screw Conveyor (Sugar Mill Boiler) Through Failure Mode and Effect Analysis (FMEA) and Taguchi Method
    Journal of Failure Analysis and Prevention, 2014
    Co-Authors: A. Mariajayaprakash, T. Senthilvelan
    Abstract:

    This paper exhibits the failures of the boiler during the Cogeneration Process and provides solution to overcome the failures. The failures are frequently occurring in the screw conveyor of fuel-feeding system of the boiler and rarely occurring in the grate of the boiler. In this research work, three important statistical tools are employed to identify and further rectify the failures of the screw conveyor. The different techniques, viz., cause-and-effect diagram, failure mode and effect analysis (FMEA), and the Taguchi method have been applied. The cause-and-effect diagram, is the primary tool used to sort out all the possible root causes of the failures. The Process parameters that cause the failures in the screw conveyor are identified by FMEA. Since the conventional FMEA has some limitations, fuzzy FMEA is employed. The most critical parameters selected by conventional FMEA and fuzzy FMEA are fuel type, fuel moisture, drum speed, and air flow. Finally, the selected Process parameters are optimized by the Taguchi method to prevent the failures occurring in the screw conveyor. Among the various Process parameters, the parameter, fuel type, significantly affects the performance of the screw conveyor.

  • failure detection and optimization of sugar mill boiler using fmea and taguchi method
    Engineering Failure Analysis, 2013
    Co-Authors: A. Mariajayaprakash, T. Senthilvelan
    Abstract:

    Abstract Sugar industry plays an important role in economic development of country. Cogeneration is an important source of income for sugar industries. Boiler is one of the essential components used in Cogeneration Process. Unscheduled boiler outages in sugar mills are major problem resulting loss of production. The boiler may be failed due to number of reasons; some of the reasons such as mechanical failure, electrical failure and temperature sensors failure. This paper describes the failures of the fuel feeding system frequently occurred in the Cogeneration boiler and gives the solution to rectify these failures by using three important tools, namely, cause and effect diagram, Failure Mode and Effect Analysis and Taguchi method.

Mahmoud M. El-halwagi - One of the best experts on this subject based on the ideXlab platform.

  • An Integrated Approach to Water-Energy Nexus in Shale-Gas Production
    Processes, 2018
    Co-Authors: Fadhil Y. Al-aboosi, Mahmoud M. El-halwagi
    Abstract:

    Shale gas production is associated with significant usage of fresh water and discharge of wastewater. Consequently, there is a necessity to create proper management strategies for water resources in shale gas production and to integrate conventional energy sources (e.g., shale gas) with renewables (e.g., solar energy). The objective of this study is to develop a design framework for integrating water and energy systems including multiple energy sources, the Cogeneration Process and desalination technologies in treating wastewater and providing fresh water for shale gas production. Solar energy is included to provide thermal power directly to a multi-effect distillation plant (MED) exclusively (to be more feasible economically) or indirect supply through a thermal energy storage system. Thus, MED is driven by direct or indirect solar energy and excess or direct Cogeneration Process heat. The proposed thermal energy storage along with the fossil fuel boiler will allow for the dual-purpose system to operate at steady-state by managing the dynamic variability of solar energy. Additionally, electric production is considered to supply a reverse osmosis plant (RO) without connecting to the local electric grid. A multi-period mixed integer nonlinear program (MINLP) is developed and applied to discretize the operation period to track the diurnal fluctuations of solar energy. The solution of the optimization program determines the optimal mix of solar energy, thermal storage and fossil fuel to attain the maximum annual profit of the entire system. A case study is solved for water treatment and energy management for Eagle Ford Basin in Texas.

  • An Integrated Approach to Water-Energy Nexus in Shale-Gas Production
    2018
    Co-Authors: Fadhil Y. Al-aboosi, Mahmoud M. El-halwagi
    Abstract:

    Shale gas production is associated with significant usage of fresh water and discharge of wastewater. Consequently, there is a necessity to create the proper management strategies for water resources in shale gas production and to integrate conventional energy sources (e.g., shale gas) with renewables (e.g., solar energy). The objective of this study is to develop a design framework for integrating water and energy systems including multiple energy sources, Cogeneration Process, and desalination technologies in treating wastewater and providing fresh water for shale gas production. Solar energy is included to provide thermal power directly to a multi-effect distillation plant (MED) exclusively (to be more feasible economically) or indirect supply through a thermal energy storage system. Thus, MED is driven by direct or indirect solar energy, and excess or direct Cogeneration Process heat. The proposed thermal energy storage along with the fossil fuel boiler will allow for the dual-purpose system to operate at steady-state by managing the dynamic variability of solar energy. Additionally, electric production is considered to supply a reverse osmosis plant (RO) without connecting to the local electric grid. A multi-period mixed integer nonlinear program (MINLP) is developed and applied to discretize operation period to track the diurnal fluctuations of solar energy. The solution of the optimization program determines the optimal mix of solar energy, thermal storage, and fossil fuel to attain the maximum annual profit of the entire system. A case study is solved for water treatment and energy management for Eagle Ford Basin in Texas.

E. Arbizu - One of the best experts on this subject based on the ideXlab platform.

  • Computational Intelligence techniques for maximum energy efficiency of an internal combustion engine and a steam turbine of a Cogeneration Process
    International Journal of Energy and Environmental Engineering, 2014
    Co-Authors: Sandra Seijo Fernández, I. Campo, J. Echanobe, J. García-sedano, E. Suso, E. Arbizu
    Abstract:

    This paper discusses the development of a model of a real Cogeneration plant based on Computational Intelligence (CI) algorithms. In particular, two CI strategies are used: one based on artificial neural network and the other one based on a neuro-fuzzy system. Both systems are trained with a data collection from the Cogeneration plant. Data mining techniques are applied to remove erroneous and redundant data, and also to obtain information about the variables and its behaviour. This task allows to select only the relevant information and is also a way to decrease the complexity of the model. In this first approach on the work, two separate subsystems of the Cogeneration Process are considered: an engine and a steam turbine. The obtained models are used to analyze the role of each involved variable and to derive a set of recommendations (i.e., changes in some of the input variables) to optimize the performance of the system. The recommendations applied to the models improve the behaviour of the plant providing higher energy production with a lower cost.

Siyu Yang - One of the best experts on this subject based on the ideXlab platform.

  • Conceptual Design and Techno-economic Analysis of a Coal to Methanol and Ethylene Glycol Cogeneration Process with Low Carbon Emission and High Efficiency
    ACS Sustainable Chemistry & Engineering, 2020
    Co-Authors: Chen Jianjun, Yu Qian, Siyu Yang
    Abstract:

    Coal gasification and coking to methanol (GCtM) is a newly developed and industrialized Process in China. However, in the early stages, the idea of integration hardly applied to this Process. To improve the degree of integration, this paper developed a coupling Process of coproducing methanol and ethylene glycol. The key idea was to find an appropriate distribution of carbon and hydrogen components for maximal resource utilization. The new Process introduced additional hydrogen and carbon sinks by adding a new ethylene glycol synthesis unit. It separated excessive H₂ or CO from different syngas streams depending on their composition. This brought more hydrogen and carbon sources. The new Process conducted integration by matching sinks and sources. A detailed Process modeling and simulation were conducted in Aspen Plus. The simulation results were verified with reference and industrial data. The techno-economic performance was analyzed and compared with the conventional Process to find the advantages of the new Process. The results showed that the new Process had a much higher carbon utilization efficiency of 54% than that of the GCtM Process, 40%. The total greenhouse gas emissions of the new Process are 1.58 t CO₂ equiv t–¹, which is 26.2% lower than that of the GCtM. It was also found that the exergy efficiency was improved from 56.7% to 68.1%. As for economic benefits, the new Process decreased total product cost by 35.2% and increased internal rate of return by 4.5%.