Browsing by Author "Moongo, Thomas E."

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    DESIGNING A CONTINUOUS QUALITY IMPROVEMENT FRAMEWORK FOR IMPROVING ELECTROWINNING CURRENT EFFICIENCY
    (2020) Moongo, Thomas E.; Sony, MIchael
    In general, the electrowinning process consumes substantial electrical energy. Considering the ever-increasing unit cost of electrical power there is a need to improve current efficiency so that electrical energy is utilised efficiently. In light of the research/knowledge gap identified, this research aims to design a continuous quality improvement framework for improving electrowinning current efficiency. The objectives of this research are as follow: (i) To explore factors that influence current efficiency; (ii) To evaluate the factor that has the most significant effect on current efficiency, by applying statistical process control; and finally (iii) To design a continuous quality improvement framework for improving electrowinning current efficiency, by applying statistical process control. The scope of work for this research focused on applying statistical process control on an online industrial copper electrowinning process instead of doing laboratory experiments. In this case, a sequential mixed research methodology was applied and Minitab statistical software package was utilized for analysing data by creating control charts. The factors that influence current efficiency were explored and the main factors are as follow: metallurgical short-circuits, impurities, electrode condition, electrode alignment, contacts condition, electrolyte temperature, reagent addition, electrolyte acid concentration, current density, rectifier current, electrode insulators, cathode nodules, electrolyte copper content, and electrolyte flow rate. After analysing constructed control charts and implementing an out of control action plan, it was concluded that metallurgical short-circuits (hotspots) have the most significant effect on current efficiency than all the other factors. Bringing hotspots under statistical control resulted in improved current efficiency by 5.40 % which is equivalent to approximately 74 MT of 99.999 % pure grade A copper cathode production over a period of 1.5 months. Finally, a continuous quality improvement framework for improving electrowinning current efficiency was designed. This was done by considering the following: Anderson Darlington normality test, non-normal data transformation (using Johnson and Box-Cox transformation), constructing control charts, and then analysing control charts which include Pearson correlation analysis, out of control points alignment analysis, root cause analysis, process capability analysis, and implementing an out of control action plan.
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    DESIGNING A CONTINUOUS QUALITY IMPROVEMENT FRAMEWORK FOR IMPROVING ELECTROWINNING CURRENT EFFICIENCY
    (2020) Moongo, Thomas E.
    In general, the electrowinning process consumes substantial electrical energy. Considering the ever-increasing unit cost of electrical power there is a need to improve current efficiency so that electrical energy is utilised efficiently. In light of the research/knowledge gap identified, this research aims to design a continuous quality improvement framework for improving electrowinning current efficiency. The objectives of this research are as follow: (i) To explore factors that influence current efficiency; (ii) To evaluate the factor that has the most significant effect on current efficiency, by applying statistical process control; and finally (iii) To design a continuous quality improvement framework for improving electrowinning current efficiency, by applying statistical process control. The scope of work for this research focused on applying statistical process control on an online industrial copper electrowinning process instead of doing laboratory experiments. In this case, a sequential mixed research methodology was applied and Minitab statistical software package was utilized for analysing data by creating control charts. The factors that influence current efficiency were explored and the main factors are as follow: metallurgical short-circuits, impurities, electrode condition, electrode alignment, contacts condition, electrolyte temperature, reagent addition, electrolyte acid concentration, current density, rectifier current, electrode insulators, cathode nodules, electrolyte copper content, and electrolyte flow rate. After analysing constructed control charts and implementing an out of control action plan, it was concluded that metallurgical short-circuits (hotspots) have the most significant effect on current efficiency than all the other factors. Bringing hotspots under statistical control resulted in improved current efficiency by 5.40 % which is equivalent to approximately 74 MT of 99.999 % pure grade A copper cathode production over a period of 1.5 months. Finally, a continuous quality improvement framework for improving electrowinning current efficiency was designed. This was done by considering the following: Anderson Darlington normality test, non-normal data transformation (using Johnson and Box-Cox transformation), constructing control charts, and then analysing control charts which include Pearson correlation analysis, out of control points alignment analysis, root cause analysis, process capability analysis, and implementing an out of control action plan.
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    DESIGNING A CONTINUOUS QUALITY IMPROVEMENT FRAMEWORK FOR IMPROVING ELECTROWINNING CURRENT EFFICIENCY
    (2020-04) Moongo, Thomas E.
    Continuous quality improvement by applying statistical process control has been long recognized in the processing industry. Effectively monitoring and controlling of process variability can result in sustained process stability and maximized process efficiencies. The electrowinning process is an energy-intensive process, and the cost of electrical energy is ever increasing. The effectiveness of utilizing electrical energy in the electrowinning process is best measured by current efficiency. Although substantial research has been done to improve current efficiency, no evidence on improving current efficiency from a quality perspective or by applying statistical process control has been found in the reviewed literature. This identified knowledge/research gap needs to be filled. This research project intends to contribute to the existing knowledge by filling the identified knowledge/research gap. The research aims to design a continuous quality improvement framework for improving electrowinning current efficiency. The objectives of the research are as follow: (i) to explore factors that influence current efficiency, (ii) to evaluate the factor that has the most significant effect on current efficiency, by applying statistical process control, and (iii) to develop a continuous quality improvement framework for improving current efficiency, by applying statistical process control. A sequential mixed research methodology was applied in this research. In this case, a qualitative research approach was followed by a quantitative research approach. Questionnaires were utilized to establish factors influencing current efficiency and best practices for improving current efficiency. The quantitative research approach was accomplished by collecting and analyzing electrolyte samples and instrument data. This is in addition to gathering historical data from an instrument database and analytical laboratory database. The established research strategy includes exploring current efficiency factors, analyzing historical data, establishing current efficiency improvement best practice and finally designing a continuous quality improvement framework for improving electrowinning current efficiency.