The editorial, authored by Chitaranjan Pany of the Vikram Sarabhai Space Centre in India, Dawood Desai of Tshwane University of Technology in South Africa, and Wagner de Rossi of the Institute of Energy and Nuclear Research in Brazil, frames manufacturing as a domain dominated by brutal physical phenomena: burr creation, plastic deformation, frictional contact, and thermo-mechanical coupling. Since at least the 1980s, FEM has been the most prevalent method for simulating these processes, and its continuous development has allowed it to replicate experimental techniques even when intricate characteristics are involved, such as complex process parameters, non-linearity, composite and multi-layered materials, shape memory alloys, and varied tool geometries. The appeal is straightforward: experiments near the cutting tool are laborious and costly, yet quantities like strain, strain rate, cutting force, and temperature are precisely the ones engineers need to understand metal cutting mechanisms. Simulation fills that measurement gap.

But FEM is only as good as its inputs, and the editorial is candid about which inputs matter most. The material constitutive law describing flow stresses, the type of friction at the tool-chip interface, and fracture control are all highly significant to the finite element analysis of machining problems. When these constitutive models are paired with experimental data to calibrate a simulation, researchers can predict characteristics that determine surface integrity: surface roughness, residual stresses, micro-hardness, plastic deformation, phase transitions, elastic recovery, and thermal behavior. Both academia and industry are paying increasing attention to this coupling of models and measurements, because surface integrity ultimately dictates the fatigue life and reliability of manufactured components, from orthopedic implants to jet engine parts.

One of the standout contributions highlighted in the editorial tackles a biomedical challenge head-on. Titanium alloy Ti6Al4V is a favorite of the biomedical field thanks to its remarkable biocompatibility, corrosion resistance, and mechanical properties, and the design of surface textures for dental implants has evolved over time to address oral rehabilitation in both healthy and compromised bone. A research team led by Lebea and colleagues explored laser shock peening, or LSP, as a surface modification technique to enhance the mechanical characteristics of implants, examining how material orientation, loading angle, and single-shot repetition of the peening process affect surface roughness. Because implant durability depends considerably on surface roughness, and because no prior computational studies had established roughness parameters for this process, the team built a numerical model in the commercial finite element software ABAQUS/Explicit to replicate the dynamic conditions of LSP, effectively using simulation to predict what experiments had not yet measured.

A second study, by Baloyi and colleagues, dives into the powder that feeds the additive manufacturing revolution. Spherical particles are essential in powder-based additive manufacturing because their enhanced flowability, packing density, and mechanical properties improve printing accuracy and the quality of final products. Traditional routes to spherical powder, such as gas atomization and plasma spheroidization, have been thoroughly examined, but laser spheroidization remains inadequately investigated. To close that gap, the researchers performed comprehensive numerical analyses using models built in Abaqus and OpenFOAM, simulating heat transfer from the laser to titanium Ti-6Al-4V powder particles with a transient uncoupled heat transfer approach that accounts for latent heat, while particle deformation was modeled with a phase-fraction-based interface-capturing technique combined with the Navier-Stokes equations. The payoff is striking: laser spheroidization of Ti-6Al-4V powder may enhance powder yield by 10 percent compared with plasma processing, delivering greater power density and reduced melting durations, and offering a more effective route to spherical particles of specific dimensions.

The third highlighted study shifts from the factory floor to the power generation sector, where steam turbine blades endure one of the harshest mechanical environments in engineering. Mashiachidi and Desai examined the complex factors impacting the fatigue life of these blades, including steam flow-induced bending, centrifugal forces, vibration response, structural mistuning, and temperature-dependent influences. The concept of mistuning is critical: manufacturing tolerances mean that nominally identical blades in a bladed disk actually vary slightly in shape, and those small deviations can dramatically alter vibration behavior and fatigue life. Using finite element analysis software, the researchers created a basic, mistuned, scaled-down model of a steam turbine bladed disk that accounts for temperature-dependent material characteristics, providing the power generation industry with a computational window into failure modes that are nearly impossible to probe directly in a running turbine.

Not every application of FEM is glamorous, and the editorial makes a point of celebrating that. A study by Gobi and Guo focused on the modeling, internal structure examination, and automation of a cassava grinding machine used in starch production. The researchers selected a single-cylinder grinder for its simplicity and versatility, then implemented automation using a GRAFCET model, a graphical sequential function chart standard in industrial control, together with an advanced human-machine interface. The HMI added an extra safety feature and allowed operators to oversee the operation through an easy graphical interface, enabling continuous operation with minimal human involvement. The result is a modest but meaningful demonstration that finite element analysis and control automation can enhance the efficiency and safety of food processing equipment in agricultural economies.

Beyond these four research articles, contributed by ten authors, the editorial sketches a sweeping landscape of where FEM is being applied across precision manufacturing. Ideal cutting parameters in machining, rolling, turning, milling, and high-speed machining are being mapped numerically. Laser applications in sheet metal forming, tube end-forming processes, micro-manufacturing, and ball-burnishing processes are being examined through combined numerical and experimental simulations. Welding and electron beam welding of high-strength steels, aluminum, titanium, and nickel-base alloys for aerospace applications are being modeled to predict joining quality. Additive manufacturing, particularly metallic powder bed processes, is being optimized with the help of artificial intelligence and machine learning algorithms trained on simulation and experimental data. Even the fabrication of blazed grating structures, which are essential for optical communication, structural coloration, precision measurement, and digital display, is being advanced through techniques such as ultrasonic-assisted ultraprecision planing, with FEM providing the predictive backbone.

The editorial’s authors, who have themselves published extensively on periodic structure theory and wave propagation in curved panels using finite element approaches, see a future where robust and reliable FE techniques for diverse manufacturing processes are integrated into AI and machine learning algorithms and digital production chains. Acoustic metamaterials and phononic crystals aimed at vibration reduction, spacecraft and antenna structures produced via 3D printing, and composite multi-layered products all feature in their vision of new potential applications. Laser processes receive special attention as a particularly intriguing and challenging domain for FEM: the intricacy and temporal sequence of phenomena that occur when a laser beam interacts with matter, combined with the speed of the processes, the complex parameter interactions, and the small regions affected, render experimental measurements incredibly difficult. In these situations, simulation is not merely a convenience but the primary means of comprehending the physics and improving outcomes.

What emerges from this collection is a portrait of a field at an inflection point. The finite element method, once a specialist tool for structural analysts, has become the connective tissue linking machining, additive manufacturing, laser processing, biomedical engineering, and industrial automation. As experimental data increasingly feeds the calibration of numerical models, and as those models in turn feed machine learning systems that optimize entire production chains, the boundary between virtual and physical manufacturing continues to blur. For researchers and engineers, the message of this Research Topic is clear: the reported advances may help the community study and better understand precision manufacturing processes, and the rapid development of manufacturing approaches and methods suggests that the most interesting applications of FEM are still ahead.

Subject of Research: Applications of finite element methods in precision manufacturing processes including machining, laser processing, additive manufacturing, and industrial automation

Article Title: Editorial: Advances of finite element methods in the precision manufacturing processes

Article References: Editorial: Advances of finite element methods in the precision manufacturing processes. (n.d.). https://doi.org/10.3389/fmtec.2025.1608699

Image Credits: AI Generated

DOI: 10.3389/fmtec.2025.1608699

Keywords: finite element method, precision manufacturing, laser shock peening, additive manufacturing, titanium alloy Ti6Al4V, powder spheroidization, steam turbine blades, fatigue life prediction, surface integrity, machine learning, machining simulation, cassava grinding automation