Volume 1, Issue 1 (September 2024) – 8 articles

Editorial

08 November 2023

Review

29 December 2023

A State-of-the-art Review on the Intelligent Tool Holders in Machining

In the manufacturing process, in addition to the properties of material itself, the quality of a product is directly related to the cutting process. Cutting force and cutting heat are two crucial factors in cutting processing. Researchers can analyze various signals during cutting process, such as cutting force signal, vibration signal, temperature signal, etc., which can regulate force and temperature, optimize the cutting process, and improve product quality. Therefore, it is very important to pay attention to various signals in cutting process. Meanwhile, good-quality signal data sets will greatly reduce time, resource and labor costs for subsequent use or analysis of researchers. Therefore, how to collect high-quality signals effectively and accurately is the first step. At present, researchers prefer to use various sensors to collect signals. With the advancement of science and technology, intelligent tool holder appears in researchers’ vision. It integrates multiple systems such as sensors, data collection, data transmission, and power supply on the tool holder. It replaces traditional wired sensors, and it is highly interactive with CNC machine tools. This paper will carry out a systematic review and prospect from three aspects: the structural design of the intelligent tool holder, the signal monitoring technology of the intelligent tool holder, and the tool condition monitoring of the intelligent tool holder.

Article

31 January 2024

Design of Intelligent and Sustainable Manufacturing Production Line for Automobile Wheel Hub

The wheel hub is an important part of the automobile, and machining affects its service life and driving safety. With the increasing demand for wheel productivity and machining accuracy in the automotive transport sector, automotive wheel production lines are gradually replacing human production. However, the technical difficulties of conventional automotive wheel production lines include insufficient intelligence, low machining precision, and large use of cutting fluid. This paper aims to address these research constraints. The intelligent, sustainable manufacturing production line for automobile wheel hub is designed. First, the machining of automotive wheel hubs is analyzed, and the overall layout of the production line is designed. Next, the process equipment system including the fixture and the minimum quantity lubrication (MQL) system are designed. The fixture achieves self-positioning and clamping functions through a linkage mechanism and a crank–slider mechanism, respectively, and the reliability of the mechanism is analyzed. Finally, the trajectory planning of the robot with dual clamping stations is performed by RobotStodio. Results show the machining parameters for a machining a wheel hub with a diameter of 580 mm are rotational speed of 2500 rpm, cutting depth of 4 mm, feed rate of 0.5 mm/r, and minimum clamping force of 10881.75 N. The average time to move the wheel hub between the roller table and each machine tool is 27 s, a reduction of 6 s compared with the manual handling time. The MQL system effectively reduces the use of cutting fluid. This production line can provide a basis and reference for actual production by reasonably planning the wheel hub production line.

Review

13 February 2024

3D Printing Technology for Rapid Response to Climate Change: Challenges and Emergency Needs

Providing rapid, efficient, inexpensive, and resilient solutions is an eminent and urgent need for emergency relief conditions, mainly and increasingly driven by the impacts of climate change. Under such disastrous circumstances, the current practice involves preparation, dispatching and managing significant amounts of materials, resources, manpower, and transportation of basic needs, which can be hindered remarkably by infrastructure damage and massive loss of lives. However, an emerging technology known as 3D printing (3DP) can play a significant role and rapidly bring unlimited innovative solutions in such conditions with much lesser resources to meet the necessities of large populations affected. Considering the recent progress of 3DP technology and applications in different industrial and consumer sectors, this study aims to provide an analysis of the status and current progress of 3DP technology in various fields to understand and present its potential for readiness and response to disasters, emergency and relief need driven by climate change. Secondly, this study also presents a sustainability assessment of 3DP technology for such cases to evaluate economic, environmental, and social impacts. Finally, policies and strategies are suggested to adapt 3DP technology in different sectors to prepare for large-scale emergencies.

Article

23 February 2024

Influence of Separation Gap on the Performance of Savonius Hydrokinetic Turbine

Despite that ocean current energy is one of the promising sources of electricity produced in the ocean, the development of ocean current energy is far behind compared to other ocean energy due to the low efficiency and high cost of installation and maintenance. Among many converting devices, the Savonius turbine has been proven to be effective and competitive in harnessing ocean current energy. The primary purpose of the present study is to search for the optimum shape of a Savonius rotor based on CFD simulation (Star-CCM+). A Savonius turbine composed of two rotating cup-shaped rotors is selected as a numerical model. We focus on the effect of two geometry parameters such as the overlap and gap ratio on the power coefficient. Throughout the parametric study, the shape of a Savonius rotor affects the power performance, and two geometry parameters with an overlap ratio of 0.15 and a gap ratio of −0.03 are found to be the optimum design. It demonstrates stable performance within the wide TSR (Tip Speed Ratio) range of 0.6 to 1.6, with the maximum power coefficient Cp of 0.34 achieved at a TSR of 0.8. According to the numerical results based on the new CFD model, the presence of a bottom wall does not significantly affect the performance of a Savonius turbine. It means that the present unbounded CFD model can be acceptable in the initial design stage for the determination of the geometry parameters of a Savonius turbine.

Review

23 February 2024

Research Status and Prospect of Ultrasonic Vibration and Minimum Quantity Lubrication Processing of Nickel-based Alloys

Nickel-based alloys has important application value in modern industrial field, but there are a lot of problems that are difficult to solve in traditional processing, and it is a typical difficult-to-process material. In order to improve the machinability of nickel-based alloys, scholars try to use a variety of non-traditional processing methods to explore and study the processing of nickel-based alloys. In these studies, ultrasonic vibration assisted processing technology and minimum quantity lubrication (MQL) processing technology can achieve remarkable results. The intermittent separation cutting characteristics of ultrasonic vibration assisted processing technology can improve the processing quality by changing the tool path, while minimum quantity lubrication processing technology can improve the lubrication effect of cutting, combining ultrasonic vibration assisted MQL processing leverages the benefits of both methods, resulting in improved machinability and expanded application of nickel-based alloys. Summarize the current research status on the machining mechanism of nickel-based alloys assisted by ultrasonic vibration and micro lubrication, and anticipate its developmental trends. This provides a reference for future research on the efficient machining mechanisms and practical applications of nickel-based alloys.

Review

28 March 2024

Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application

Digital twin technology develops virtual models of objects digitally, simulating their real-world behavior based on data. It aims to reduce product development cycles and costs through feedback between the virtual and real worlds, data fusion analysis, and iterative decision-making optimization. Traditional manufacturing processes often face challenges such as poor real-time monitoring and interaction during machining, difficulties in diagnosing equipment failures, and significant errors in machining. Digital twin technology offers a powerful solution to these issues. Initially, a comprehensive review of the research literature was conducted to assess the current research scope and trends. This was followed by an explanation of the basic concepts of digital twins and the technical pathway for integrating digital twins into intelligent manufacturing including outlining the essential technologies for creating a system of interaction between the virtual and real worlds, enabling multimodel fusion, data sensing, algorithm-based prediction, and intelligent decision-making. Moreover, the application of digital twins in intelligent manufacturing throughout the product life cycle was detailed, covering product design, manufacturing, and service stages. Specifically, in the manufacturing phase, a model based on heat conduction theory and visualization was used to construct a time-varying error model for the motion axis, leading to experiments predicting the time-varying error in the hole spacing of a workpiece. These experiments achieved a minimum prediction error of only 0.2 μm compared to the actual error. By compensating for time-varying errors in real time, the variability in the hole spacing error decreased by 69.19%. This paper concludes by summarizing the current state of digital twins in intelligent manufacturing and projecting future trends in key technologies, application areas, and data use, providing a basis for further research.

Article

01 April 2024

Cost Effectiveness of the Industrial Internet of Things Adoption in the U.S. Manufacturing SMEs

This research paper explores the financial adoption challenges of the Industrial Internet of Things (IIoT) in industry. Previous studies have mainly concentrated on designing affordable IIoT devices, reducing operational costs, and creating conceptual frameworks to assess the financial impact of IIoT adoption. The objective of this paper is to investigate whether IIoT adoption’s financial benefits outweigh the initial costs in small and medium-sized enterprises (SMEs). The data from the Industrial Assessment Centers (IAC) database were analyzed, focusing on 62 U.S. manufacturing SMEs across 10 states and 25 Standard Industrial Classifications (SICs), evaluating projected IIoT implementation costs and anticipated cost savings. Results from the analyses reveal that statistically, the difference between implementation costs and savings is significant at a 95% confidence level. Practically, this indicates that SMEs, despite facing high initial costs, can expect these investments to be counterbalanced by substantial savings. From an engineering perspective, this finding raises awareness among SMEs that, beyond overcoming financial barriers, IIoT technologies serve as a strategic enhancement to operational efficiency and competitive positioning. This study acknowledges the limitations including reliance on estimated projections and a narrow industry focus. Future research should broaden the sample and explore the lifecycle costs of IIoT.

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