Mechanical Engineering Research Articles

Development and verification of material models in modeling of wave strain hardening and additive synthesis processes

BACKGROUND: The creation of competitive machine parts capable of withstanding standard and increased operational loads is an urgent task in mechanical engineering. Developing additive synthesis technologies together with strengthening technologies make it possible to create such products with high load-bearing capacity. However, to improve the efficiency of these technologies, it is necessary to create theoretical models of the processes taking place. The article presents the results of the first stage of creating complex theoretical models of the combined 3DMP process and wave strain hardening (WSH) required for designing technological processes for manufacturing engine parts and brake systems of automotive equipment. . AIMS: Creation and assessment of the adequacy of material models used in finite element modeling of additive synthesis processes with subsequent hardening. MATERIALS AND METHODS: Theoretical models of the material were created in the ANSYS software package, which allows for multidisciplinary calculations. The experimental data required for preparing the models were obtained by testing tensile samples manufactured using standardized methods. The hardness of materials was studied using a KB 30S automatic hardness tester. The adequacy of additive synthesis modeling was assessed based on the distribution of temperature fields. The adequacy of material models for the VDU process was assessed based on the sizes of individual plastic indentations and the distribution diagrams of the depth and degree of hardening in the surface layer. RESULTS: Theoretical models of the following materials were developed: steel, stainless steel, bronze alloy, titanium alloy, aluminum alloy. The theoretical data obtained from the modeling results have a high level of significance. The studies were conducted for various thermal (in the range from +20ºС to +800ºС) and deformation modes. Graphical results of theoretical and experimental studies allow us to obtain a qualitative assessment of the processes under study with the required accuracy. CONCLUSIONS: As a result of the assessment of the adequacy of the developed models, it was established that the discrepancy between the empirical and theoretical data does not exceed 7.4%. The obtained models of materials are statistically significant and can be correctly applied in further studies.

Utilising Artificial Intelligence to Bolster and Refine the Production of Formal Letters in English Tailored for Students of Mechanical Engineering

Over the past decade, advancements in technology, notably Artificial Intelligence (AI), have significantly transformed educational methodologies and shifted the existing educational framework. Innovations like OpenAI’s ChatGPT and Gemini have garnered considerable attention, with their groundbreaking features potentially revolutionizing the realm of education, prompting concerns among educators and researchers (Grassini, 2023; Halaweh, 2023). This research endeavours to utilise AI, specifically ChatGPT and Gemini, to bolster and refine formal letter writing and email composition skills among first-cycle undergraduate students enrolled in the English for Engineering module at a Spanish university. Initially, students underwent a pre-test assessing their English proficiency and confidence levels, along with their familiarity with ChatGPT and other AI tools utilised for educational and writing purposes. Subsequently, students engaged in collaborative group tasks using Google Docs within Google Drive. Finally, a post-test was administered to gauge students' perceptions regarding their experience with English for Specific Purposes, particularly English for Mechanical Engineering, and their utilisation of ChatGPT and other AI tools for educational and writing purposes. Findings indicate that integrating AI can enhance students' grasp of written language accuracy in formal letter writing, particularly in inquiries, quotations, and complaint letters, facilitating better organisation and structure in their written correspondence in terms of style, accuracy, and communicative efficacy. This study suggests that investigations like the one presented here enable educators to explore the incorporation of AI, specifically ChatGPT and Gemini, to enrich students' writing proficiency, foster creativity, and cultivate technological aptitude within the classroom setting.

On the Quasi-diagonalization and Uncoupling of Gyroscopic Circulatory Multi-degree-of-freedom Systems

Abstract A new central result that gives the necessary and sufficient conditions for two n by n skew-symmetric matrices and one symmetric matrix to be simultaneously quasi-diagonalized by a real orthogonal congruence is proved. Based on this result, the decomposition of linear multi-degree-of-freedom dynamical systems with gyroscopic, circulatory, and potential forces is investigated through a real linear coordinate transformation generated by an orthogonal matrix. Several sets of conditions, applicable to real-life structural and mechanical systems arising in aerospace, civil, and mechanical engineering, under which such a coordinate transformation exists are found, thereby allowing these systems to be decomposed into independent, uncoupled subsystems, each with a maximum of two degrees of freedom. The conditions are expressed in terms of the coefficient matrices of the system. A specific form for the circulatory (gyroscopic) matrix is posited, and when the gyroscopic (circulatory) matrix is simple—a situation that commonly appears in real-life applications—it is shown that just a single necessary and sufficient condition is required for the decomposition of the multi-degree-of-freedom system. Numerical examples are provided throughout to demonstrate the analytical results.

Editorial: Mechanical Properties and Engineering Applications of Special Soils

Special soils refer to the soils with unique physical, mechanical, and engineering properties that are developed under specific geological environments and weathering conditions [...]

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

Persepsi Pihak Industri Terhadap Kompetensi Mahasiswa PTM pada Program Magang Industri

<p><em>The purpose of this study was to determine the assessment of the industry, especially field supervisors regarding the competence of students who participated in the industrial internship program majoring in Mechanical Engineering Education FKIP UNS with a concentration in Production for the 2022 period. This study uses a descriptive method, which aims to collect, analyze, and present data that has a relationship with the problem under study. Data collection techniques using questionnaires and interviews. The results showed that the industry's perception of the competence of PTM students was in the very good category and was considered quite in accordance with industry needs, with work attitude as the most prominent aspect (82.5%). However, there is still room for improvement, especially in the aspects of practical skills (74.2%) and knowledge application (76.5%) in order to produce graduates who are better prepared to face the demands of the dynamic world of work. With good assessments, especially in the work attitude aspect, PTM graduates have good competitiveness potential in the job market, but need to continue to improve their practical skills and knowledge application abilities to maximize employment opportunities. Conducting Conduct an in-depth analysis of the gap between the competencies expected by industry and those possessed by students so that it can be the basis for recommendations for curriculum improvements that are more specific to the demands of the labor market and improve the work readiness of PTM graduates.</em></p>

3D PRINTING OF THIN-WALLED MODELS - STATE-OF-ART

The paper presents an analysis of the state of the art regarding the production of thin-walled models using 3D printing technology. Data based on the Web of Science database was presented in quantitative terms and divided into individual areas of science. 189 publications were found in the years from 2013 to 2024, of which the most, i.e. 82 in the area of Mechanical Engineering. It was observed that some of the publications are grouped around issues related to the study of mainly mechanical properties of both samples and thin-walled cellular structures. Another group of works concerns methods of obtaining thin-walled models using 3D printing technologies. The article characterizes selected exemplary works representing individual areas of science. The need to perform tests of the mechanical properties of thin-walled elements, especially those with a thickness of less than 2 mm, was indicated. Appropriate examples were provided to demonstrate the lower mechanical properties of thin-walled elements compared to solid-type parts manufactured by 3D printing.

CREATION, MANAGEMENT, AND USE OF A DATABASE FOR THE MAINTENANCE PROCESS OF PRODUCTION EQUIPMENT IN AN INDUSTRIAL COMPANY

The paper presents the creation of a database of motion norms to support the maintenance management system in an industrial production company, implemented by a team from the Faculty of Mechanical Engineering, VSB - Technical University of Ostrava. This database is intended for filling and optimal use of maintenance modules of ERP systems and for use in the processes of preparation of maintenance and service orders. The article focuses on the methodology of creation, characteristics, use and availability of this database and its application in industrial practice.

Effect of various notch shape on Lamb wave scattering behaviour in a bent plate

Abstract The application of guided waves to investigate commonly used plate shapes in the aerospace, mechanical and civil industries are plates with bend shapes. This paper investigates the interaction of fundamental Lamb waves with notches in bent plates, commonly found in aerospace, mechanical, and civil engineering applications. These areas are particularly susceptible to failure due to defects such as cracks and notches, which often manifest as semi-circular corrosion patches or 900 notches. The presence of notches affects stress distribution, necessitating thorough analysis to prevent accidents. Accordingly, this paper focus on the interaction of fundamental Lamb waves through two types of notches that could be present inside a bent metal plate section. To explore this, a hybrid numerical framework is employed which combines Semi-Analytical Finite Elements (SAFE) with the Finite Element Method (FEM). A bent plate sections with various notch types is simulated using FEM, while SAFEs facilitate the definition of wave propagation through healthy regions of the plate. The study analyses the scattering behaviour of Lamb waves for different notch configurations and examines both fundamental modes over a specified frequency range. With a change in the interrogation signal parameters, there is a noticeable difference in the sensitivity of scattered waves with different notch types. Formulating a strategy for identifying and locating a notch inside a bent plate may need careful consideration of the important conclusions drawn. Understanding these interactions, aim of the paper is to enhance the integrity assessment of structural components subject to such defects.

Advancing nonlinear problem solutions: Newton-like iterative techniques for varied convergence orders using homotopy perturbation

Abstract Iterative methods are crucial in numerical analysis for approximating solutions to nonlinear problems encountered in various fields, such as biomathematics, thermodynamics, chemical engineering, and fluid mechanics. This paper introduces innovative iterative methods of convergence orders three and six to eight, developed using the homotopy perturbation technique (HPT). We address the limitations of traditional derivative-based methods by incorporating divided differences, resulting in derivative-free schemes with optimal convergence properties. We present four newly designed algorithms (HPM1, HPM2, HPM3, and HPM4) and provide a comprehensive convergence analysis. Numerical simulations and basins of attraction demonstrate the superior performance of the proposed methods compared to existing methods of the same order. The proposed methods exhibit faster convergence and larger basins of attraction, making them highly effective for solving nonlinear equations. Our new numerical methods rely on approximations and iterative processes, with each small step bringing us closer to the exact solution. Exploring these numerical methods encourages us to apply mathematics to solve challenging problems in physics, engineering, finance, and more.

Medi-Cliq (A Drug Dispenser) - A Survey Paper

In this paper, the concept of automated drug dispensing is summarized, and its significance in the healthcare sector is illustrated. MediCliq is designed to efficiently dispense prescribed medication, is researched in detail, focusing on the integration of mechanical design with IT-based control systems. Key technologies, including prescription scanning, prescription validation, and user interac- tion interfaces, are explored to enable seamless dispensing and user authentication. This paper also conducts a formal review of interdisciplinary methodologies, combining mechanical engineering with IT for developing an effective, secure, and user-friendly automated drug dispensing solution. Keywords: Automated drug dispensing, Prescription scanning, Secure dispensing solution, Prescription validation

Novel application of metabolic imaging of early embryos using a light-sheet on-a-chip device: a proof-of-concept study.

Is it feasible to safely determine metabolic imaging signatures of nicotinamide adenine dinucleotide [NAD(P)H] associated auto-fluorescence in early embryos using a light-sheet on-a-chip approach? We developed an optofluidic device capable of obtaining high-resolution 3D images of the NAD(P)H autofluorescence of live mouse embryos using a light-sheet on-a-chip device as a proof-of-concept. Selecting the most suitable embryos for implantation and subsequent healthy live birth is crucial to the success rate of assisted reproduction and offspring health. Besides morphological evaluation using optical microscopy, a promising alternative is the non-invasive imaging of live embryos to establish metabolic activity performance. Indeed, in recent years, metabolic imaging has been investigated using highly advanced microscopy technologies such as fluorescence-lifetime imaging and hyperspectral microscopy. The potential safety of the system was investigated by assessing the development and viability of live embryos after embryo culture for 67 h post metabolic imaging at the two-cell embryo stage (n = 115), including a control for culture conditions and sham controls (system non-illuminated). Embryo quality of developed blastocysts was assessed by immunocytochemistry to quantify trophectoderm and inner mass cells (n = 75). Furthermore, inhibition of metabolic activity (FK866 inhibitor) during embryo culture was also assessed (n = 18). The microstructures were fabricated following a standard UV-photolithography process integrating light-sheet fluorescence microscopy into a microfluidic system, including on-chip micro-lenses to generate a light-sheet at the centre of a microchannel. Super-ovulated F1 (CBA/C57Bl6) mice were used to produce two-cell embryos and embryo culture experiments. Blastocyst formation rates and embryo quality (immunocytochemistry) were compared between the study groups. A convolutional neural network (ResNet 34) model using metabolic images was also trained. The optofluidic device was capable of obtaining high-resolution 3D images of live mouse embryos that can be linked to their metabolic activity. The system's design allowed continuous tracking of the embryo location, including high control displacement through the light-sheet and fast imaging of the embryos (<2 s), while keeping a low dose of light exposure (16 J · cm-2 and 8 J · cm-2). Optimum settings for keeping sample viability showed that a modest light dosage was capable of obtaining 30 times higher signal-noise-ratio images than images obtained with a confocal system (P < 0.00001; t-test). The results showed no significant differences between the control, illuminated and non-illuminated embryos (sham control) for embryo development as well as embryo quality at the blastocyst stage (P > 0.05; Yate's chi-squared test). Additionally, embryos with inhibited metabolic activity showed a decreased blastocyst formation rate of 22.2% compared to controls, as well as a 47% reduction in metabolic activity measured by metabolic imaging (P < 0.0001; t-test). This indicates that the optofluidic device was capable of producing metabolic images of live embryos by measuring NAD(P)H autofluorescence, allowing a novel and affordable approach. The obtained metabolic images of two-cell embryos predicted blastocyst formation with an AUC of 0.974. N/A. The study was conducted using a mouse model focused on early embryo development assessing illumination at the two-cell stage. Further safety studies are required to assess the safety and use of 405 nm light at the blastocyst stage by investigating any potential negative impact on live birth rates, offspring health, aneuploidy rates, mutational load, changes in gene expression, and/or effects on epigenome stability in newborns. This light-sheet on-a-chip approach is novel and after rigorous safety studies and a roadmap for technology development, potential future applications could be developed for ART. The overall cost-efficient fabrication of the device will facilitate scalability and integration into future devices if full-safety application is demonstrated. This work was partially supported by an Ideas Grant (no 2004126) from the National Health and Medical Research Council (NHMRC), by the Education Program in Reproduction and Development (EPRD), Department Obstetrics and Gynaecology, Monash University, and by the Department of Mechanical and Aerospace Engineering, Faculty of Engineering, Monash University. The authors E.V-O, R.N., V.J.C., A.N., and F.H. have applied for a patent on the topic of this technology (PCT/AU2023/051132). The remaining authors have nothing to disclose.

The Analysis of Applied Innovative Mechatronics Technology in Intelligent Driving - A Case Study of New-Energy Vehicles' Development in Mainland China

Abstract. The interdisciplinary field of mechatronics, which amalgamates elements of mechanical, electrical, computer, and control engineering, has fundamentally transformed the automotive industry. This transformative influence is evident in the development of advanced vehicular functionalities such as Automatic Fuel Filling Systems, Car Attitude Control, Antilock Brake Systems (ABS), and Electronic Stability Programs (ESP), as well as in the advent of vehicles equipped with semi-active suspensions. The integration of mechatronics has not only enhanced vehicle safety, efficiency, and performance but has also positioned itself as a cornerstone for the burgeoning electric vehicle (EV) market, particularly in China. Chinese companies, leveraging extensive smart factory and automation technologies, have consequently secured a dominant stance in the global EV landscape, capturing a staggering 60% market share. This paper explores the multifaceted applications of mechatronics in the automobile industry of industrialized nations, with a special focus on its pivotal role in China's technological ascendancy in automotive manufacturing. Through an exploration of practical applications including IoT integration and collaborative robotics, this study underscores the transformative potential of mechatronics in redefining automotive production and operation, propelling the industry toward unprecedented levels of innovation and efficiency.

Method for Constructing a Compact Component Mode Synthesis Model for Analyzing Nonlinear Normal Modes of Structures with Localized Nonlinearities

Abstract Nonlinear dynamics analysis is a crucial topic in mechanical and aerospace engineering. The analysis of nonlinear normal modes (NNMs) provides an effective mathematical tool for interpreting complex nonlinear vibration phenomena. Unlike the invariant normal modes of linear systems, NNMs often exhibit frequency-energy dependence and cannot be computed using the traditional eigen-decomposition method. Calculating NNMs relies on numerical methods that involve expensive iterative computations, especially for systems with numerous degrees-of-freedom. To relieve computational costs, this paper proposes a mode selection method for the component mode synthesis (CMS) technique to enable compact reduced-order modeling of structures with localized nonlinearities. The reduced-order model is then combined with a numerical continuation scheme to establish a low-cost NNM analysis framework. This framework can efficiently predict the NNMs of high-dimensional finite element models. The proposed framework is demonstrated on an I-shaped cantilever beam with localized nonlinear stiffness. The results show that the proposed approach can identify the key modes in the CMS modeling procedure. The NNMs of the nonlinear I-shaped beam structure can then be analyzed with a significant reduction in computational costs.

Effects of hybrid work on psychological detachment

AbstractAfter the coronavirus pandemic, hybrid work has become firmly established in many companies. This study investigated the relation of hybrid work and relevant working conditions with the psychological detachment of employees. A written online survey was conducted among 250 employees of a company in the mechanical engineering industry in Germany who worked from home at least part of the time. Multiple hierarchical regression was used for the analysis. The results show that, as expected, the quality of manager-employee communication has a positive (β = 0.13, p &lt; 0.05) and extended work availability a negative effect (β = −0.35, p &lt; 0.001) on psychological detachment. Contrary to the assumptions, however, the proportion of work from home has a positive effect on detachment (β = 0.15, p &lt; 0.05). Regarding the demographic variables, female employees are better able to detach from work (β = −0.36, p &lt; 0.01). The quantitative demands initially show a significant effect, but this disappears as soon as the extended work availability and the proportion of work from home are included in the analysis. The included predictors explain 19% (p &lt; 0.001) of the total variance.Practical Relevance Hybrid work offers the opportunity to organize work more flexibly and thus to adapt it more closely to the needs of employees. The results of this study show that work from home can foster psychological detachment from work, provided that health-promoting working conditions are in place.

DeepJEB: 3D Deep Learning-based Synthetic Jet Engine Bracket Dataset

Abstract Recent advances in artificial intelligence (AI) have impacted various fields, including mechanical engineering. However, the development of diverse, high-quality datasets for structural analysis remains a challenge. Traditional datasets, like the jet engine bracket dataset, are limited by small sample sizes, hindering the creation of robust surrogate models. This study introduces the Deep- JEB dataset, generated through deep generative models and automated simulation pipelines, to address these limitations. DeepJEB offers comprehensive 3D geometries and corresponding structural analysis data. Key experiments validated its effectiveness, showing significant improvements in surrogate model performance. Models trained on DeepJEB achieved up to a 23% increase in the coefficient of determination and over a 70% reduction in mean absolute percentage error (MAPE) compared to those trained on traditional datasets. These results underscore the superior generalization capabilities of DeepJEB. By supporting advanced modeling techniques, such as graph neural networks (GNNs) and convolutional neural networks (CNNs), DeepJEB enables more accurate predictions in structural performance. The DeepJEB dataset is publicly accessible at: https://www.narnia.ai/dataset.

Structure and properties of the boride layer of steel using the plasma alloying method

Boration is one of the promising methods for increasing surface hardness and wear resistance, resistance to oxidation and corrosion of mechanical engineering parts. The diffusion saturation process is characterized by a long duration, as well as a shallow depth of the hardened layer. The use of concentrated heating sources can solve these problems. Among the methods of high-energy exposure, the technology of plasma surface alloying should be highlighted. In this paper, the study of the microstructure and properties of the boride layer obtained on steel by plasma alloying is carried out. It is noted that the boron-doped layer has a heterogeneous structure and high hardness. It is noted that the layer obtained after alloying with a current of 120 A has the highest microhardness value and amounts to 859–1265 HV. With an increase in current to 140 A, the microhardness of the alloyed layer decreases and amounts to 761–1048 HV. Increasing the current to 160 A leads to a significant decrease in the microhardness of the surface layer and it is 452–747 HV. It is known that the volume of iron boride fractions determines the degree of hardening of the steel surface. An increase in the plasma arc current leads to a decrease in the proportion of primary borides in the surface layer after alloying, and therefore leads to a decrease in microhardness. The alloyed layer has characteristic zones: hypereutectic, eutectic and hypoeutectic. An increase in current leads to a significant change in the microstructure of the surface layer and a decrease in the microhardness of the alloyed layer. The surface layer after plasma alloying with a current of 120 A has the highest microhardness (1265 HV). It has been established that it is possible to obtain a boride layer using the technology of plasma surface doping with boron. After processing, the alloyed layer is characterized by a heterogeneous structure and has high hardness.

Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer

Metaheuristic algorithms (MAs) now are the standard in engineering optimization. Progress in computing power has favored the development of new MAs and improved versions of existing methods and hybrid MAs. However, most MAs (especially hybrid algorithms) have very complicated formulations. The present study demonstrated that it is possible to build a very simple hybrid metaheuristic algorithm combining basic versions of classical MAs, and including very simple modifications in the optimization formulation to maximize computational efficiency. The very simple hybrid metaheuristic algorithm (SHGWJA) developed here combines two classical optimization methods, namely the grey wolf optimizer (GWO) and JAYA, that are widely used in engineering problems and continue to attract the attention of the scientific community. SHGWJA overcame the limitations of GWO and JAYA in the exploitation phase using simple elitist strategies. The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. Remarkably, SHGWJA always outperformed or was very competitive with other state-of-the-art MAs, including CEC competition winners and high-performance methods in all test cases. In fact, SHGWJA always found the global optimum or a best cost at most 0.0121% larger than the target optimum. Furthermore, SHGWJA was very robust: (i) in most cases, SHGWJA obtained a 0 or near-0 standard deviation and all optimization runs practically converged to the target optimum solution; (ii) standard deviation on optimized cost was at most 0.0876% of the best design; (iii) the standard deviation on function evaluations was at most 35% of the average computational cost. Last, SHGWJA always ranked 1st or 2nd for average computational speed and its fastest optimization runs outperformed or were highly competitive with their counterpart recorded for the best MAs.

Optimizing the Operation of an Electrolyzer with Hydrogen Storage Using Two Different Methods: A Trade-Off Between Simplicity and Precision in Minimizing Hydrogen Production Costs Using Day-Ahead Market Prices

The potential for hydrogen is high in industrial processes that are difficult to electrify. Many companies are asking themselves at what cost they can produce hydrogen using water electrolysis with hydrogen storage. This article presents a user-friendly and less computationally intensive method (called method 1 in the following) for determining the minimum of the levelized cost of hydrogen (LCOH) by optimizing the combination of electrolyzer size and hydrogen storage size and their operation, depending on electricity prices on the day-ahead market. Method 1 is validated by comparing it with a more accurate and complex method (called method 2 in the following). The methods are applied to the example of a medium-sized industrial company in the mechanical engineering sector with a total natural gas demand of 8 GWh per year. The optimized LCOH of the analyzed company in method 1 is 5.00 €/kg. This is only slightly higher than in method 2 (4.97 €/kg). The article shows that a very good estimate of the LCOH can be made with the user-friendly and less computationally intensive method 1. For further validation of the methods, they were applied to other companies and the results are presented below.

Data proficiency in MAE education: Insights from student perspectives and experiences

This paper explores how mechanical and aerospace engineering (MAE) students understand and improve their data proficiency throughout their engineering curriculum. Data is essential for engineering students to be proficient in handling, as it is involved in every aspect of engineering. With the growing ubiquity of data and data analysis in all engineering fields, engineering students need to learn and master data skills to be competitive in the current and future job market. However, there is a lack of research on how non-computer science or software engineering majors perceive data proficiency and how they seek opportunities to develop data skills, especially as it relates to specific subdomains. In this paper, we investigate how students perceive data proficiency and how they develop using interview data from N = 27 MAE students at a research institution in the southeastern United States. Using the How People Learn framework, we analyzed the data through thematic analysis methods with a postpositivist approach, considering the bounded context of this study. The results show that MAE students value data proficiency as a crucial skill for their future careers and recognize its importance in making evidence-based engineering decisions. The study also reveals that, even though data proficiency is often a “hidden competency,” MAE students intuitively find various ways to enhance their data skills. These findings may help engineering educators to tailor their instruction to their students’ needs, address misconceptions about data and data proficiency, and prepare a data-literate future engineering workforce.