Many ports and terminals endeavor to enhance energy efficiency as energy prices have increased through years and climate change mitigation is a key target for the port industry. Stricter environmental regulations are adopted by authorities to limit pollutants and GHG emissions arising from energy consumption. Increasingly, port operational strategies and energy usage patterns are under scrutiny. To ingrain sustainability and environmental protection of ports, the use of innovative technology appears as a critical conduit in achieving a transition from a carbon-intensive port industry (dependent on fossil fuels) to a low-carbon port model by harnessing renewable energy, alternative fuels (e.g. LNG, hydrogen, biofuel), smarter power distribution systems, energy consumption measurement systems. In this context, this paper conducts a systematic literature review to analyze operational strategies (e.g. peak shaving, operations optimization), technology usage (e.g. electrification of equipment, cold-ironing, energy storage systems), renewable energy, alternative fuels and energy management systems (e.g. smart grid with renewable energy) for improving the energy efficiency and environmental performance of ports and terminals. Research gaps and future research directions are identified. Analysis shows that there is a great potential for ports to achieve further energy efficiency and researchers have many impactful research opportunities.

A review of energy efficiency in ports: Operational strategies, technologies and energy management systems

Energy Management in Manufacturing: From Literature Review to a Conceptual Framework

Energy consumption in machining: Classification, prediction, and reduction strategy

Multi-objective optimization and life cycle assessment of eco-friendly cryogenic N2 assisted turning of Ti-6Al-4V

Systematic literature review of decision support models for energy-efficient production planning

Energy consumption model and energy efficiency of machine tools: a comprehensive literature review

Establishing a rapid, accurate, and practical energy consumption evaluation model for machine tools is essential to save energy and increase profits in the manufacturing industry. Relationships between spindle rotation speed, cutting parameters, material removal rate, specific energy consumption, cutting power, and material removal power were experimentally analyzed, and the limitation and the limitation and differences between several machine tools’ cutting power evaluation models were discussed. Cutting parameters or material removal rate were regarded as independent variable in those models. By comparing the models’ fitting and predicted results, it draw a conclusion that the model treating cutting parameters as independent variable had greater accuracy but depends on a large quantity of experimental data. The model treating material removal rate as independent variable can also obtain a good fit and reduce the number of necessary experiments. Therefore, it is a rapid method to estimate the cutting energy consumption of machine tools for the latter model. In addition, the paper puts forward an improved cutting power model, which considers the influence of the spindle rotation speed on the material removal power during the milling process. The proposed model can predict a milling machine’s cutting power more accurately.

An improved cutting power model of machine tools in milling process

Optimization Parameters for Energy Efficiency in End milling

Manufacturing processes, such as machining, transform raw materials into finished goods, and these processes consume significant energy. There is an increasing concern about the energy required for such processes and the environmental consequences attributable to the generation of the energy. Reducing the energy required to perform machining operations will not only reduce the environmental footprint, but also provide economic benefits. To that end, the effects of cutting conditions (e.g., feed and speed) and tool geometry (diameter and number of teeth) on the power required for an end milling operation are investigated experimentally. Experimental results are presented from a cutting mechanism perspective with the goal of understanding the role of the process variables. The specific cutting energy (SCE) is found decreasing when material removal rate increases, but there is substantial variation about the general trend. In essence, the cutting parameters and the tool geometry influenced the changes of average chip thickness and cutting speed, which cause the shear deformation energy changes and eventually collectively influence the SCE’s change. Based on the experiments, suggestions on selecting process parameters are provided to improve milling energy efficiency.

Characterizing the effect of process variables on energy consumption in end milling

A Rapid Life Cycle Assessment (RLCA) method based on Green features is proposed in order to solve the inherent limitations of conventional Life Cycle Assessment (LCA), such as long period, massive data requirement, which result in difficulties in supporting product conceptual design. Firstly, Green Feature is proposed in supporting the LCA in conceptual design, where a mapping relationship is established between green feature and design information to achieve the transformation from the design information to green features. Secondly, product conceptual design model is proposed based on modular configuration. The approximate products program will be obtained through retrieval and matching of each module of product using the knowledge base and case base. Thirdly, Intuitionistic Fuzzy theory and Monte Carlo method are respectively used to process the qualitative and quantitative uncertain information of green features in order to ensure the accuracy of the evaluation results. Besides, the appropriate life cycle impact assessment method is selected to complete the life cycle impact assessment and obtain the LCA results. Consequently, the RLCA of product design program is completed to support product green design. Finally, a fan of a ventilation system is studied as an example to verify the proposed RLCA theory.

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Lirong Zhou

Papers

Energy consumption model and energy efficiency of machine tools: a comprehensive literature review

An improved cutting power model of machine tools in milling process

Optimization Parameters for Energy Efficiency in End milling

Characterizing the effect of process variables on energy consumption in end milling

A rapid life cycle assessment method based on green features in supporting conceptual design