Intelligent and Sustainable Manufacturing

Guide for Authors Submit to ISM

Sustainable Machining and Green Products

Deadline for manuscript submissions: 28 February 2025.

Guest Editor (1)

Sujan Debnath
Prof. Dr. Sujan Debnath 
Department of Mechanical Engineering, Curtin University Malaysia, Miri, Sarawak, Malaysia
Interests: Elastomer and Polymer Recycling; Green Composite Materials using Bio-Waste; Nano Polymer Composite; Advanced/Sustainable/Nano-enhanced Machining; Thermal Management in Electronic Packaging; Origami-inspired Folding Technique and Folding Design
Website: https://engsci.curtin.edu.my/departments/mechanical-engineering/staff/sujan-debnath/

Co-Guest Editors (3)

Iqbal U. Mohammed
Prof. Dr. Iqbal U. Mohammed 
Department of Mechanical Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India
Interests: Metal Forming; Nano Machining; Tool path Machining; Metal Joining; Composite and Nano Materials; Severe Plastic Deformation; Optimization Techniques
Website: https://www.srmist.edu.in/faculty/dr-u-mohammed-iqbal/
Alokesh Pramanik
Dr. Alokesh Pramanik 
Department of Mechanical Engineering, Curtin University, GPO Box U1987, Perth WA6845, Australia
Interests: Machining Processes; Composite Materials; 3D Printing; Finite Element Analysis
Website: https://staffportal.curtin.edu.au/staff/profile/view/alokesh-pramanik-dd8e9a16/
N Senthilkumar
Prof. Dr. N Senthilkumar 
Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India
Interests: Composite Materials; Machining; Optimization; Corrosion and Wear Studies
Website: https://publons.com/researcher/1300709/n-senthilkumar/

Topic Collection Information

In today’s manufacturing industries, increased productivity, better surface quality, and cost reductions are essential. The machining process can be sustainable if raw materials are reduced and recycled, energy sources are green and efficient, and tools and cutting atmospheres are environmentally friendly. Moreover, an environment impact assessment plan including recovering waste and waste disposal strategy is crucial to achieving sustainability in industrial machining. In addition, sustainable machining should account for economic, ecological, and technological aspects promoting a circular economy.

We invite articles related to sustainable machining and green products in this special issue with an emphasis on achieving sustainability in industrial machining and product development. The articles are expected to address novel and effective strategies for sustainable machining and green product development. We hope that this issue will inspire further research and innovation in this area and contribute to global efforts toward a more sustainable industry future.

Keywords:
MQL machining
Eco-efficiency Analysis/Environmental Impact Assessment
Green Design and Recycling
Sustainable Manufacturing
Waste-to-Energy/Sustainable Waste Management
Nano and Hybrid Lubrication
Energy Efficient Machining
Sustainable CNC machining
Supply Chain Sustainability
Sustainable Machining and Circular Economy
Sustainable Cooling and Lubrication Strategies
Machine Tool Energy Consumption
Green Machine Tools
Optimization of Sustainable Machining
Difficult-to-Machine Materials Machining
Machine Vision Inspection with IoT Environmental
Cryogenic Machining
Digital Twin-enabled Machining Process
Machine Learning and Artificial Intelligence
Sustainable Turning and Milling
Sustainable Machining and Machinability
Advanced Image Processing
Industry 4.0 in Machining
Ecological, Economic and Technological Aspects of Machining
Hybrid Cooling and Lubrication Strategies
Vegetable-oil Based Cutting Fluids for Sustainable Machining
Virtual High-Performance Machining
Incremental Sheet Forming
Biodegradable and eco-friendly cutting fluids
Ionic fluids
Sustainable Polishing
Sustainable Metal forming operations

Published Papers (2 papers)

Article

02 September 2024

Lithium-Rich Spinel Cathode with Higher Energy Density for Sustainable Li-Ion Batteries Operating in Extended Potential Range

Lithium batteries pave way for rapidly reducing greenhouse gas emissions. Still there are concerns associated with battery sustainability, such as the supply of key battery materials like cobalt, nickel and carbon emissions related to their manufacture. While LiMn2O4 spinel is a common cathode material for Li-ion batteries that remove Co and Ni, studies on over-stoichiometric variants and their behavior across a broad potential range may be limited. Research in this area could provide valuable insights into the performance, stability and electrochemical characteristics of such cathodes, offering potential benefits for the development and optimization of Li-ion battery technologies. This study investigates the electrochemical behavior of Li-rich Li1+yMn2−yO4−δ (LMO, y ≈ 0.03, δ ≈ 0.01) spinel as a cathode in Li-ion batteries, focusing on the phenomenon of extra capacity under the extended operating voltage 1.5–4.8 V vs. Li+/Li. The nanostructured LMO sample synthesized by sol-gel method and calcined at 900 °C is characterized by X-ray diffraction, scanning and transmission electron microscopy and surface area measurements. The Li-rich spinel electrode delivers a specific discharge capacity of 172 mAh g−1 at 1st cycle. It retains 123 mAh g−1 at the 100th cycle (71.5% capacity retention) at current density of 100 mA g−1 current density (i.e., ~0.7 C rate). An excellent stability is obtained in the 1.5–4.8 V potential window, with a discharge capacity of 77 mAh g−1 after 500 cycles at the same current density, owing to the reduction of the Jahn-Teller effect by Li doping. These results contrast with the specific capacity of 85 mAh g−1 (1st cycle) and the capacity retention of 54.3% after 100 cycles, obtained when the cell operates in the narrow potential range of 3.0–4.5 V.

Somia M.Abbas
Motaz G.Fayed
Rasha S.El-Tawil
Saad G.Mohamed
Ashraf E.Abdel-Ghany
Ahmed M.Hashem
Alain Mauger
Christian M.Julien*

Article

26 November 2024

Identification of Cutting Workpiece Surface Defects Based on an Improved Single Shot Multibox Detector

In the mechanical cutting process, the surface defects of the workpiece are an important indicator of cutting quality and also reflect the condition of both the machine tool and the cutting tool. Effective detection of defects on the surface of the workpiece plays an important role in adjusting the processing conditions promptly, reducing losses, improving the utilization rate of the workpiece, and maintaining the normal operation of the equipment. To address the challenge of detecting surface defects on workpieces, an inspection method based on an improved Single Shot Multibox Detector (SSD) model is proposed. The method simplifies the detection model and reduces the computation by proposing a DH-MobileNet network instead of a VGG16 network in the SSD structure. The inverse residual structure is also used for position prediction, and null convolution is used instead of a down-sampling operation to avoid information loss. A scanning electron microscope was used to obtain the surface image of the workpiece. A dataset of workpiece surface defects was constructed and expanded, then used to train and test the model for detecting three common types of high-frequency defects: peel-off, chip adhesion, and scratches. The effect was compared with YOLO, Faster R-CNN, and the original SSD model. The detection results show that the method can detect the defects on the surface of the workpiece more accurately and quickly, which provides a new idea for defect detection in real industrial scenarios.

Zhenjing Duan
Shushu Xi
Shuaishuai Wang
Ziheng Wang
Peng Bian
Changhe Li
Jinlong Song
Xin Liu*
TOP