Cirp Annals-Manufacturing Technology最新文献

Non-isothermal hot forming processes are of great scientific and industrial interest to produce e.g. high-strength aluminum components for lightweight applications. The interfacial heat transfer coefficient (IHTC) is a key factor in the design of these forming processes. However, the IHTC values reported in the literature vary significantly, even for the same material combinations and load conditions. The present work reveals the causes of these variations by a combined experimental and model-based approach. It is shown that the measurement of dynamically changing blank temperatures and the determination of the die surface temperature are two core aspects of non-isothermal experimental IHTC analysis.

Electro-active scaffolds play an important role in bone tissue engineering applications, serving as physical substrates for cell proliferation and osteogenic differentiation, ultimately realizing new bone regeneration. This paper discusses a novel strategy to synthesize graphene through laser-induced surface doping, using bone collagen as the carbon source, serving as a key functional filler to be combined with biocompatible, biodegradable poly(ε-caprolactone) (PCL), for the fabrication of the next generation electro-active bone tissue engineering scaffolds. Scaffolds are fabricated through material-extrusion additive manufacturing. The developed graphene is proven to present a significant enhancement effect on surface and mechanical properties over the conventional graphene material.

A predictive digital twin (DT)-driven dynamic error control approach is presented for accuracy control in high-frequency slow-tool-servo ultraprecision diamond turning processes. An explainable artificial intelligence-enabled real-time DT of the total dynamic error (inside and outside the servo loop) was established using in-line acceleration input data near the tool. A feedforward controller was used to mitigate the total dynamic errors before they came into effect. The machining trials using this approach showed that significant improvement in machining accuracy (87%, surface form accuracy; 95%, phase accuracy with precisions of 0.06 µm and 0.05°), and efficiency (8 times the state-of-the-art) were successfully achieved.

Modern medical implants are characterized by non-circular shapes, which is often challenging for economic production. Non-Circular-Rotary-Turning (NCRT) is a newly developed process for manufacturing non-circular cross-sections at high productivity and a high degree of geometric freedom. In this work, the basic process kinematics of NCRT are presented. A process design method is proposed and validated. The fundamental cutting conditions are examined using simulation and the cutting forces are studied experimentally. In an example of application, NCRT enables to reduce machining time by a factor of more than ten compared to a conventional process chain, resulting even in better surface quality.

A novel aerosol evaluation cell was employed to measure particle number and mass concentration, with a size distribution from nano to micro scale. Different cooling/lubrication and airflow extraction scenarios were tested on a CFRP/Ti6Al4V case study, and the particle concentrations were measured to evaluate their effect on productivity and cost per hole, if current occupational exposure limits are respected. Aspects to achieve sustainable machining like tool life, consumption of coolant and energy, and standby time required to safely open the machine-tool doors were considered. LCO₂ delivered the best productivity and cost results as it improved the tool life by 40 % compared to MQL, while eliminating the need for standby time to evacuate particles.

Additively manufactured cutting tools have thus far proven unsuccessful in machining difficult-to-cut materials like titanium. To the knowledge of the authors, this paper demonstrates, for the first time, the form turning of Ti6Al4V with WC-Co tools printed using laser powder bed fusion (LPBF), without any material-related post-processing. Following an investigation into LPBF parameters to optimize WC-Co properties, numerical modelling was utilized to design and analyse said tools, which were then printed, finish-ground, and tested. This advance was facilitated by the enabling capabilities of LPBF, which elevated tool performance by incorporating features that are critical to machining titanium, such as cooling fins and streamlined internal coolant channels.

This work introduces a fast ED-milling approach for machining of complex and precise geometries on high vol.% Al/SiC MMCs. It aims to overcome the issues of severe tool wear and low overall machining efficiency while conducting conventional milling. The material removal mechanism of this specific machining scheme is investigated through discharge phenomena observation and metallurgical analyzation, thereby, discharge current regulation methods for finishing and roughing were developed accordingly to further promote the material removal. Machining tests verify that, as compared to die-sinking EDM, the proposed method guarantees rather higher machining efficiency and satisfactory surface quality in machining of various cavities.

In manufacturing, the essential product characteristics are often created through multiple stages. Coupling product data obtained through inspection and controllers based on decision models with prediction capabilities enables quality control loops, enhancing both feedback and feedforward mechanisms. This paper proposes a methodology to merge the formulation of feedback and feedforward quality control loops into a performance evaluation model for multi-stage manufacturing systems. This approach evaluates quality control loop impacts system-wide, aiding in configuring and reconfiguring quality gates. A case study illustrates how allocating inspection technologies and efficient decision models improves overall system performance through effective feedback and feedforward control loops.

Cutting force simulations are effective tools to predict the quality of the cutting process and to reduce the process development times. Such simulations must generally be verified by measurements to ensure the required prediction accuracy. Table and tool holder dynamometers are typically used equipment for cutting force measurement by basic cutting processes like milling and turning. However, the use of this equipment by advanced processes like gear skiving is limited. This paper presents an approach for a sensory, spindle-integrated force measurement system for mill-turn machines and its use for the verification of a cutting force simulation in gear skiving.

Inspired by the natural intelligence of humans and bio-evolution, Artificial Intelligence (AI) has seen accelerated growth since the beginning of the 21st century. Successful AI applications have been broadly reported, with Industry 4.0 providing a thematic platform for AI-related research and development in manufacturing. This paper highlights applications of AI in manufacturing, ranging from production system design and planning to process modeling, optimization, quality assurance, maintenance, automated assembly and disassembly. In addition, the paper presents an overview of representative manufacturing problems and matching AI solutions, and a perspective of future research to leverage AI towards the realization of smart manufacturing.