International Journal of Precision Engineering and Manufacturing-Green Technology最新文献

On a metal manufacturing shop floor, hazardous metal emissions are released from machines. These emissions remain suspended in the proximity of the working environment for an extended period despite the presence of a ventilation system and pose health risks to the workers. The present work discussed the need and demand for control and mitigation of emissions from the most demanding industrial shop floor electrical discharge machine (EDM) process for pollution-free manufacturing. The emissions of metal aerosols from the EDM process impose significant concerns for occupational safety. Health risk assessment of EDM emission reveals the presence of carcinogenic and non-carcinogenic elements in substantially high concentrations, causing several pulmonary and life-threatening diseases. The developed nanofiber-based multi-layer auxiliary filtration system reduces the PM1 particles of 170 × 10⁵ per litre of air concentration using the non-coated and nano-coated composite nanofiber-based multi-layer filters with filtration efficiency of ~ 87% and 97.27%, respectively. Moreover, the filtration efficiency of varying sizes of PM particles (average diameter of > 0.35 µm) is estimated to be ~ 99% using the above-mentioned in-house developed filtration systems with less pressure drop comparable with commercial filters. A comparative assessment of in-house developed filtration systems reveals nearly equal filtration efficiency with low flow resistance, reusable and cost-effectiveness than the high-efficiency particulate air (HEPA) filters. The presented study examines hazardous emissions from shopfloor machines and proposes a control mitigation approach through technological innovation to promote green manufacturing.

The microdrill serves as precision cutting tool employed in the drilling of printed circuit boards (PCBs). The edge defects, such as grinding marks and burrs resulting from the grinding process, significantly impairs both the drilling quality and service life. Hence, it is imperative to meticulously prepare the cutting edge to ensure optimal cutting performance. In this paper, the cutting edge of cemented carbide microdrill was prepared by shear thickening polishing (STP) method. To achieve efficient cutting edge preparation of microdrill, STP experiment was carried out to evaluate the polishing force and determine the suitable processing parameters. Furthermore, the electrolysis combined shear thickening polishing (E-STP) method was employed in microdrill edge preparation, and the influence of different electrolytic voltage on the edge preparation effect was studied. The experimental results indicate that cutting edge preparation efficiency of microdrill in the STP process can be successfully increased by increasing the polishing speed, the main cutting edge radius increases from the initial 2.77 ± 0.4 μm to the highest 3.9 ± 0.3 μm after 2 min processing (polishing speed v = 85 rpm). The E-STP method is proven as an effective way in removing microdrill edge defects with a smaller polishing speed (v = 55 rpm). But, drilling experiments show that the wear resistance and drilling accuracy of the E-STP prepared microdrill (r average 3.6 μm) is significantly worse than that of the STP prepared microdrill (r average 3.5 μm) due to the Co loss. Overall, our research provides a new idea for realizing efficient cutting edge preparation of microdrill.

Evolving demands for compact, light-weight, and versatile optical systems across various industries require the facile integration of planar diffractive optics. For the manufacturing of diffractive optics, green manufacturing becomes the prerequisite with timely considerations of Environmental, Social, and Governance (ESG). Conventional manufacturing processes such as semiconductor lithography or nano /micro imprinting utilize a large amount of harmful chemicals. Meanwhile, direct laser writing emerges as one of the key solution candidates, offering clear advantages over others, especially in terms of eco-friendliness due to the simple manufacturing process with less chemical usage. In this comprehensive review, we present recent advances in the analytical design, green manufacturing of electrically tunable smart light-weight planar optics, and their promising applications in space optics, photovoltaics, and optical imaging, highlighting the necessity for tunability in focal length, aberration, transparency, and beam propagation direction. Various types of electrically tunable diffractive optical elements utilizing active modulation of refractive index, geometrical shape, and bandgap have been discussed. Finally, this review concludes by proposing the integration of ultra-thin and light-weight diffractive optics presenting potential applications in micro-electronics, biomedical imaging, space exploration, and extended reality.

Friction Stir Welding (FSW) and Friction Stir Processing (FSP) are solid-state joining and material processing techniques that have garnered considerable attention for their versatility and industrial applicability. In the present work, FSP was performed on AA 6056 T4, dealing with the issue of monitoring tool wear and assessing its impact on the process. The impact of tool wear on power requirements was analyzed, and it was expanded the understanding of tool behavior and its implications for the overall process performance. Specifically, variations in energy consumption, temperatures, and vibrations are observed with changing tool conditions. Further insights are provided by analyzing the microhardness and the pin volume ratio, which show distinct trends as the tool wears. Two tool maintenance ways are proposed, that are cleaning the tool with a sodium hydroxide solution and increasing the tool’s rotational speed. Both the strategies exhibit the potential to partially restore the tool’s initial characteristics. This study highlights the critical importance of assessing tool condition, energy consumption, and process sustainability, particularly in industrial settings where material processing requires efficiency and quality assurance.

The development and manufacturing of sensors are of great importance to modern engineering, as sensors are essential for detecting environmental changes and for the monitoring of various systems. While conventional manufacturing is the most common method for fabricating sensors, additive manufacturing (commonly known as 3D printing) has gained popularity as an efficient alternative. Although additively manufactured sensors are applicable in many engineering fields, building an entire sensor (including the housing structure and sensing components) by additive manufacturing remains challenging. This work presents a comprehensive analysis of the additive manufacturing processes, materials, and applications for sensors that are either fully or partially produced by additive manufacturing. Key issues in material development and processes that limit the development of fully 3D-printed sensors are highlighted. Additionally, the role of additively manufactured sensors plays in green technology has been explored. This review is expected to provide the researchers with a comprehensive understanding of the processes and materials used to produce sensors for various applications.

Binderless tungsten carbide (WC) is preferred for manufacturing tools, mould, and wear-resistant components. However, due to its high brittleness and hardness, the machined binderless WC surface is prone to generate microcracks and the machining efficiency is extremely low. Aiming at this difficulty, a clean and eco-friendly dry electrical discharge assisted grinding (DEDAG) method without any liquid medium was proposed for the processing of binderless WC. DEDAG principle was revealed and the DEDAG platform was first developed. A series of DEDAG, conventional dry grinding (CDG), and conventional wet grinding (CWG) experiments were conducted on binderless WC under different processing parameters. The current and voltage waveforms during the DEDAG process were observed, and the discharge properties were analyzed. The chip morphologies, surface hardness, residual stress, as well as surface and subsurface morphologies were analyzed. The results show that the surface hardness and roughness obtained by DEDAG are smaller than that by CDG or CWG. The measured residual tensile stress after CDG is larger against DEDAG. The ground surface by DEDAG has better crystal integrity than that by CDG. DEDAG can soften/melt workpiece material and diminish grinding chips, thereby promoting plastic removal and increasing processing efficiency. The influences of DEDAG parameters on the ground surface quality are also investigated, and the optimal DEDAG parameters are determined. With the increase of open-circuit voltage or grinding depth, the surface quality improves first and then worsens. The optimal open-circuit voltage is 40 V and the grinding depth ranges from 10 µm to 15 µm. This research provides a new idea for promoting the efficient and low-damage processing of binderless WC.

Enhancing energy efficiency in buildings is a pivotal strategy for reducing energy consumption and mitigating greenhouse gas emissions. As part of global efforts to achieve carbon neutrality by 2050, there is a heightened focus on improving window insulation because windows are a significant source of thermal loss, representing nearly 40% of a building's heat dissipation. This study explores the development and application of vacuum insulation glazing (VIG), a cutting-edge insulation technology, to substantially reduce heat transfer through windows, thereby contributing to building energy savings. With its superior insulation performance, achieving thermal transmittance levels around 0.5W/m²·K, VIG technology presents a promising advancement over traditional double-glazed or gas-filled insulating glass units (IGUs). However, the adoption of VIG is challenged by economic factors, with costs significantly higher than standard IGUs and triple-glazed windows meeting passive house standards. The production of VIG, characterized by lengthy evacuation times and high processing temperatures, contributes to its elevated price. This research identifies the potential for cost reduction through optimizing manufacturing processes, including using low-melting-point solders for hermetic sealing and localized heating techniques to shorten production times. Despite the high initial cost, the potential for integrating VIG with other smart technologies suggests a promising future for achieving carbon neutrality in buildings. The study calls for further research and standardization in VIG production to overcome current technical and economic barriers, paving the way for its wider adoption and realizing next-generation energy-efficient building materials.

This study focuses on the challenges with butt joining of 25 mm thick aluminum alloy 7175-T79. High-speed (150 mm/min) single-pass friction stir welding was employed as an effective technique for this purpose. The influence of quenching and cooling rate on critical performance level indicators such as joint strength and microstructure was investigated. A series of friction stir welding (FSW) trials, conducted both in air and with a trailing water spray using steel and composite backing plates (BP) revealed distinct hardness distribution in the nugget, heat-affected zone (HAZ), and HAZ minimum hardness. The influence of trailing water spray (TWS) on joint efficiency proves more significant than the impact of BP combinations, owing to their markedly different contributions to the quenching process. The ultimate tensile strength of TWS welds exhibited a notable 14% increase compared to the air welds. TWS also introduces multifaceted effects on FSW, including a reduction in processing temperature, an increase in X and Z forces, and decrease in Y force, and a narrowing of the HAZ. Lastly, the study employs digital image correlation (DIC)-based fracture mode analysis and grain size measurements, establishing correlations with the observed micro-hardness distribution.

Sustainability has become a prominent theme in the manufacturing industry, with an emphasis on optimal process configurations that enable environmentally friendly and economically viable operations. Particularly, the textile dyeing and finishing industry has garnered special attention due to its substantial water consumption and consequential wastewater generation. Moreover, dye residues in textile wastewater contain a multitude of chemical substances, posing a serious threat to environmental pollution. Therefore, there is a pressing need for effective decision-making tools to reduce dye residues. In this study, we introduce a reinforcement learning-based model to predict waste discharge in the textile dyeing and finishing industry and recommend dyeing process variables to minimize such waste. Leveraging manufacturing data collected from real production facilities, we constructed a Gradient Boosting model for waste prediction and developed a Q-learning-based process variables recommendation model for dye residue reduction. The recommendation model demonstrated high predictive performance with an R-value of 0.96, and through process configuration recommendations, achieved an average reduction of 66.58% in dye residue. These results have been validated through the collection of on-site information and experiments. This study proposes an innovative approach to effectively predict and reduce residual dyes generated in the dyeing and processing industry. However, a limitation of the developed dyeing process recommendation model is that it was tested on only two out of 124 formulations, making it challenging to generalize the model's performance. More extensive training data is necessary. These facts suggest that, if addressed in future research, improvements can overcome practical constraints and contribute to enhancing the prospects for future decision-making. It is anticipated that such advancements will strengthen the sustainability of the dyeing and processing industry, fostering environmentally friendly operations and contributing to a sustainable future.

Directed energy deposition (DED) is widely employed in the automotive, aerospace, and defense industries for defect repair and remanufacturing. Stable powder feeding through nozzles for the quality of parts is crucial in the DED process. Detecting changes in the powder flow caused by nozzle defects is visually challenging, and identifying defects in additively manufactured components is equally difficult unless significant distortion occurs. Therefore, prior understanding regarding the quality degradation and development mechanism of process defects associated with abnormal powder feeding is necessary, and product defects must be observed. This research focuses on analyzing the effect of nozzle failure on the shape and mechanical properties of parts. Computational fluid dynamics analysis is performed to examine physical phenomena resulting from an abnormal powder supply. Based on the results, an obstructed nozzle causes an abnormal powder supply, thus resulting in defects in additively manufactured components owing to distortions in the melting-pool flow and temperature distribution.