What is he best known for?
The fields of study he is best known for:
- Mechanical engineering
- Artificial intelligence
- Electrical engineering
His scientific interests lie mostly in Computer-integrated manufacturing, Manufacturing engineering, Environmental impact assessment, Quality and Risk analysis.
Hong-Chao Zhang interconnects Computer-aided manufacturing, Computer-aided process planning, Group technology, Artificial neural network and Scheduling in the investigation of issues within Computer-integrated manufacturing.
The Manufacturing engineering study combines topics in areas such as Waste management, State and CAD.
His Environmental impact assessment study overlaps with Natural resource, Environmental engineering, Energy consumption, Life-cycle assessment and Environmental degradation.
His Risk analysis study also includes
- Systems engineering, which have a strong connection to Material flow analysis,
- Auto industry, which have a strong connection to Remanufacturing.
Remanufacturing is closely attributed to Decision support system in his study.
His most cited work include:
- Computer Aided Process Planning: the state-of-the-art survey (353 citations)
- Printed circuit board recycling: a state-of-the-art survey (149 citations)
- Applications of neural networks in manufacturing: a state-of-the-art survey (147 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Remanufacturing, Life-cycle assessment, Environmental impact assessment, Manufacturing engineering and Energy consumption.
His biological study spans a wide range of topics, including Waste management, Automotive engineering and Supercritical carbon dioxide.
His study focuses on the intersection of Waste management and fields such as Supercritical fluid with connections in the field of Process engineering.
His Life-cycle assessment research incorporates Diesel engine, Environmental engineering, Primary energy, Ozone depletion potential and Reliability engineering.
Hong-Chao Zhang works mostly in the field of Manufacturing engineering, limiting it down to topics relating to Process and, in certain cases, Quality.
His research investigates the connection between Energy consumption and topics such as Efficient energy use that intersect with issues in Scheduling and Mathematical optimization.
He most often published in these fields:
- Remanufacturing (43.81%)
- Life-cycle assessment (33.19%)
- Environmental impact assessment (23.01%)
What were the highlights of his more recent work (between 2018-2021)?
- Remanufacturing (43.81%)
- Deposition (7.96%)
- Energy (7.52%)
In recent papers he was focusing on the following fields of study:
Hong-Chao Zhang mainly investigates Remanufacturing, Deposition, Energy, Efficient energy use and Composite material.
His Remanufacturing research includes elements of Hidden Markov model, Condition-based maintenance and State-space representation.
He has researched Deposition in several fields, including Particle size, Volumetric flow rate and Laser power scaling.
Hong-Chao Zhang combines subjects such as Energy consumption, Scheduling, Mathematical optimization and Industrial organization with his study of Efficient energy use.
The study incorporates disciplines such as Manufacturing engineering and Process in addition to Quality.
In his works, Hong-Chao Zhang conducts interdisciplinary research on Manufacturing engineering and Life-cycle assessment.
Between 2018 and 2021, his most popular works were:
- Effects of deposition variables on molten pool temperature during laser engineered net shaping of Inconel 718 superalloy (14 citations)
- Effects of deposition variables on molten pool temperature during laser engineered net shaping of Inconel 718 superalloy (14 citations)
- An integrated decision model of restoring technologies selection for engine remanufacturing practice (14 citations)
In his most recent research, the most cited papers focused on:
- Mechanical engineering
- Electrical engineering
- Artificial intelligence
Hong-Chao Zhang focuses on Laser power scaling, Remanufacturing, Process, Deposition and Energy.
His study in Laser power scaling is interdisciplinary in nature, drawing from both Thermocouple and Thermal, Thermal distortion.
His Remanufacturing study is associated with Manufacturing engineering.
His work deals with themes such as Key, Metal, Ranking, Reliability and Electronic engineering, which intersect with Process.
His Deposition study combines topics in areas such as Laser engineered net shaping, Inconel, Dendrite and Superalloy.
His Energy research incorporates themes from Process modeling, Tabu search, Root-mean-square deviation, Genetic algorithm and Response surface methodology.
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