Xueting Ma | Engineering and Technology | Innovative Research Award

Published on by Popular Engineer

Innovative Research Award

Xueting Ma
Tarim University, China

Xueting Ma
Affiliation Tarim University
Country China
Scopus ID 57855482600
Documents 30
Citations 100
h-index 7
Subject Area Mechanical Engineering
Event Popular Engineer Awards
ORCID 0000-0002-7534-5519

Xueting Ma is a researcher at Tarim University whose academic work focuses on agricultural machinery, mechanical design, optimization of agricultural equipment, and nondestructive evaluation of agricultural product quality. Since August 2016, Xueting Ma has worked at Tarim University while undertaking further study at China Agricultural University. Ma’s academic training includes mechanical and electronic engineering and mechanical design and theory at Northeast Forestry University. The research profile combines mechanical engineering methods with agricultural applications, particularly for mechanized production in Southern Xinjiang.[1][2]

Abstract

Xueting Ma’s research is situated at the intersection of mechanical engineering and agricultural machinery. A representative study investigates lightweight structural design for a residual film recovery machine frame using finite element analysis, experimental design, and multi-objective optimization. A three-dimensional frame model was developed in SolidWorks and analyzed in ABAQUS using static and prestressed modal analyses. The study subsequently evaluated six structural dimensional parameters and identified the rear cross-member, upper main girder, and V-shaped support column as important design variables. A Box-Behnken response surface methodology was then applied to optimize frame mass while maintaining structural stress constraints. The optimized design reduced frame mass from 426.820 kg to 335.684 kg, corresponding to a 21.35% reduction, while maintaining reported strength and vibration performance. The study provides a technical basis for lightweight design of agricultural machinery frames and illustrates the application of computational mechanics and optimization techniques to agricultural equipment engineering.[1][2][3]

Keywords

Agricultural machinery; mechanical engineering; lightweight design; finite element analysis; residual film recovery; structural optimization; response surface methodology; agricultural product quality; nondestructive testing; mechanical design.

Introduction

Xueting Ma’s academic career has centered on the development, analysis, and optimization of agricultural machinery and technologies for evaluating agricultural product quality. The research is particularly relevant to agricultural mechanization in Southern Xinjiang, where machinery design must account for operational efficiency, structural reliability, and practical field requirements. Ma’s work combines mechanical design with numerical simulation, experimental analysis, and agricultural applications.

Xueting Ma studied mechanical and electronic engineering at Northeast Forestry University from September 2009 to July 2013 and subsequently completed studies in mechanical design and theory at the same university from September 2013 to July 2016. Since August 2016, Ma has worked at Tarim University and has also undertaken study at China Agricultural University. This academic progression provides a foundation for research integrating mechanical engineering principles with agricultural production technologies.[1][2]

Research Profile

Xueting Ma’s research profile includes optimization design of agricultural machinery and implements and nondestructive testing of agricultural product quality. The research program addresses both machine-level engineering problems and agricultural quality-assessment applications, combining computational mechanics, structural optimization, experimental methods, and spectroscopic analysis.

  • Completed or ongoing research projects: 6.
  • Consultancy and industry projects: 6.
  • Books published with ISBN: 4.
  • Patents published, filed, or under process: 5.
  • Research articles published in SCI, Scopus, and other indexed journals: 21.
  • Citation index: Not available (N/A).

The research profile also includes editorial and professional activities. Xueting Ma has served as an Editorial Board Member of the International Journal of Food Engineering and Technology. Collaboration with Northeast Forestry University, continuing from 2022, has involved mechanical vibration testing and fatigue analysis of agricultural machinery components, graduate academic exchange, and cooperation in monograph compilation concerning fruit nondestructive testing technology.

Xueting Ma is a member of the Chinese Society for Agricultural Machinery (CSAM) and the Xinjiang Agricultural Engineering Society, with both memberships reported from 2022 to the present. These professional activities complement research interests in agricultural machinery optimization and nondestructive assessment of agricultural products.[1][2]

Research Contributions

A significant contribution concerns the lightweight optimization of a residual film recovery machine frame. The study began with three-dimensional modeling in SolidWorks and subsequent finite element analysis in ABAQUS. Static and prestressed modal analyses were used to characterize the structural response. Single-factor experiments were then used to examine the influence of six dimensional parameters on mass, maximum displacement, maximum stress, maximum strain, and first-order modal frequency.[3]

The analysis identified the cross-sectional dimensions of the rear cross-member, upper main girder, and V-shaped support column as key variables. A three-factor, three-level response surface model based on Box-Behnken experimental design was subsequently developed. Multi-objective optimization targeted minimum frame mass subject to maximum-stress constraints. The reported optimal dimensions were 20 × 20 mm for the rear cross-member, 40 × 40 mm for the upper main girder, and 50 × 14 mm for the V-shaped support column. The reported difference between optimized simulation results and predicted values was below 3%.[3]

The optimized frame mass decreased from 426.820 kg to 335.684 kg, representing a reported 21.35% reduction. The maximum stress was reported as 94.87 MPa and the first-order modal frequency as 17.567 Hz, with the study concluding that the optimized design satisfied the stated strength and vibration requirements.[3]

Beyond structural optimization, Xueting Ma’s contributions include the development of residual film recycling equipment and orchard grass management machinery, static-dynamic simulation and lightweight optimization of equipment frames, and research using near-infrared spectroscopy for nondestructive fruit-quality testing. These activities connect mechanical engineering methods with practical agricultural production and quality-assessment requirements.

Publications

Xueting Ma’s reported publication record includes 21 research articles in SCI, Scopus Documents 30, Citations 100, an h-index 7 and other indexed journals, together with four books carrying ISBNs and five patents published, filed, or under process. The publication portfolio covers agricultural machinery design, structural optimization, weed-control equipment, and nondestructive quality assessment of agricultural products.[1]

  • Han, Z., Ma, X., Jia, N., Guo, G., & Wan, C. (2026). Lightweight design of a residual film recovery machine frame based on static and dynamic characteristics. Results in Engineering. [3]
  • Ma, X., Zhou, L., Wan, C., Guo, G., Zhao, J., & Zhang, Q. (2026). Performance analysis and parameter optimization of a weed control device through cutting shallow soil layer roots. Results in Engineering.[4]
  • Tong, Y., Luo, H., Ma, X., Yu, J., Liu, H., & Kang, L. (2026). Research on the spectral detection effect and data fusion of small white apricot quality based on different detection distances. Scientific Reports, 16, Article 52412. [5]

Research Impact

The reported research has practical relevance to agricultural machinery engineering, particularly through the application of lightweight structural design to equipment used in agricultural operations. Reducing structural mass while maintaining required strength and dynamic performance can support improvements in material efficiency and equipment design. The residual film recovery machine study provides a specific example of integrating finite element simulation, experimental design, and response surface optimization into agricultural machinery development.[3]

The broader research portfolio extends this engineering approach to weed-control equipment and nondestructive evaluation of fruit quality. Research on weed-control device optimization addresses mechanical performance and parameter selection, while spectroscopic research investigates detection effects and data fusion for agricultural product quality assessment.[4] [5]

The reported combination of research projects, industry and consultancy activities, publications, patents, books, editorial service, and professional memberships indicates sustained engagement with agricultural engineering research and technology development. The stated focus on Southern Xinjiang further connects the research program with regional mechanized agricultural production.

Award Suitability

The research profile is relevant to an Innovative Research Award because it demonstrates the application of established mechanical engineering methodologies to practical agricultural machinery challenges. In particular, the residual film recovery machine research combines computer-aided modeling, finite element analysis, modal analysis, experimental design, and multi-objective optimization to address material efficiency and structural performance.[3]

The reported 21.35% reduction in frame mass, together with the maintenance of stated stress and vibration requirements, provides a quantitative measure of the engineering outcome of the optimization process.[3] Additional research on weed-control equipment and nondestructive agricultural-product testing broadens the innovation portfolio across agricultural engineering applications.[4] [5]

On the information provided, the award relevance can be characterized as based on documented research activity, engineering methodology, measurable design optimization, and potential practical application. Final award decisions would depend on the applicable evaluation criteria, verification of research records, and assessment by the relevant award committee.

Conclusion

Xueting Ma’s academic profile reflects sustained research activity in mechanical engineering applied to agricultural machinery and agricultural product quality assessment. The work combines mechanical design, finite element analysis, structural optimization, experimental methods, and nondestructive testing. The reported lightweight optimization of a residual film recovery machine frame demonstrates a systematic approach to reducing structural mass while maintaining specified engineering performance.[1][3]

Together with research on weed-control machinery, fruit-quality detection, professional service, patents, books, and collaborations, these activities establish a multidisciplinary research profile connecting mechanical engineering with agricultural technology. The profile therefore provides a substantive basis for consideration under an Innovative Research Award category, subject to independent verification and the award’s formal assessment criteria.

References

  1. Elsevier. (n.d.). Scopus author details: Xueting Ma, Author ID 57855482600. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57855482600
  2. ORCID. (n.d.). Xueting Ma, ORCID record 0000-0002-7534-5519. ORCID. https://orcid.org/0000-0002-7534-5519
  3. Han, Z., Ma, X., Jia, N., Guo, G., & Wan, C. (2026). Lightweight design of a residual film recovery machine frame based on static and dynamic characteristics. Results in Engineering. https://doi.org/10.1016/j.rineng.2026.112268
  4. Ma, X., Zhou, L., Wan, C., Guo, G., Zhao, J., & Zhang, Q. (2026). Performance analysis and parameter optimization of a weed control device through cutting shallow soil layer roots. Results in Engineering. https://doi.org/10.1016/j.rineng.2026.112128
  5. Tong, Y., Luo, H., Ma, X., Yu, J., Liu, H., & Kang, L. (2026). Research on the spectral detection effect and data fusion of small white apricot quality based on different detection distances. Scientific Reports, 16, Article 52412. https://www.nature.com/articles/s41598-026-52412-y

Andrea Sutoova | Engineering and Technology | Applied Engineering Award

Published on by Popular Engineer

Applied Engineering Award

Andrea Sutoova
VSB – Technical University of Ostrava, Czech Republic
Andrea Sutoova
Affiliation VSB – Technical University of Ostrava
Country Czech Republic
Scopus ID 55980563600
Documents 21
Citations 148
h-index 8
Subject Area Quality Engineering
Event Popular Engineer Awards
ORCID 0000-0002-6689-046X

Andrea Sutoova is an academic researcher associated with engineering quality management, quality engineering, Quality 4.0, manufacturing improvement, sustainability, and related management systems. Her research record includes publications addressing Six Sigma, machine learning, Lean 4.0, quality engineering competencies, manufacturing processes, and organizational quality improvement. [1]

Abstract

Andrea Sutoova is a researcher whose academic activities are centered on quality management and quality engineering, with related work in Quality 4.0, Industry 4.0, open innovation, human resource management, manufacturing quality, and organizational improvement. Her documented research record includes 21 Scopus-indexed documents, 148 citations, and an h-index of 8, while her broader scholarly profile includes publications and peer-review contributions across engineering, materials, sustainability, and quality-management journals. [1]

Keywords

Quality Engineering; Quality Management; Quality 4.0; Six Sigma; DMAIC; Lean 4.0; Industry 4.0; manufacturing quality; sustainability; process improvement; materials engineering; human resource management; organizational quality.

Introduction

Andrea Sutoova, PhD, has an academic background in production quality and has undertaken teaching and research activities in quality-oriented engineering and management. Her reported teaching portfolio includes organization design and development, quality of products and services, human resource management, and integrated management systems. Her research has involved national and international projects and publications concerning quality improvement, engineering systems, organizational practices, and manufacturing applications. [2]

The research record supplied for this article connects her work with organizations including the Technical University of Ostrava, University of Ostrava, and Technical University of Košice. The profile also identifies subject categories spanning engineering, materials science, physics, business and economics, and chemistry, indicating an interdisciplinary research orientation. [1]

Research Profile

The research profile is principally associated with quality engineering and quality management. A recurring theme is the application of structured improvement methodologies to industrial and organizational settings, including Six Sigma DMAIC, Quality 4.0, Lean 4.0, process sustainability, and competence development. Recent publications further extend this work into machine learning-assisted quality improvement and advanced manufacturing processes. [3] [5]

  • Quality Management and Quality Engineering
  • Quality 4.0 and Industry 4.0
  • Six Sigma and DMAIC-based improvement
  • Lean 4.0 and operational improvement
  • Manufacturing quality and materials engineering
  • Sustainability and organizational quality systems
  • Human resources and quality-engineering competencies

Research Contributions

A significant contribution of Andrea Sutoova’s recent research is the integration of established quality-improvement methodology with emerging digital analytical approaches. A 2026 study applies Six Sigma DMAIC together with machine learning to quality improvement in a casting-manufacturing context, linking statistical process improvement with data-driven analytical methods. [3]

Her work also contributes to the developing literature on Quality 4.0 by examining competence gaps among early-career quality engineers and by investigating factors affecting Quality 4.0 implementation in organizations. These studies address both the technological and human-capital dimensions required for contemporary quality systems. [5] [8]

Additional contributions concern manufacturing and materials applications, including research on PVD-coated inserts in high-pressure die casting and the relationship between tooling lifetime and surface-quality requirements. Her publication record also includes interdisciplinary work involving sustainability, supplier management, education-process improvement, and advanced metallic materials. [7] [9] [10]

Publications

The supplied publication record demonstrates a multidisciplinary research trajectory spanning quality engineering, manufacturing, healthcare quality, sustainability, and materials science. Particularly relevant recent publications include studies of machine-learning-supported Six Sigma improvement in casting, Lean 4.0 applications in operating theatres, Quality 4.0 competence gaps, and thermomechanical processing of a medium-entropy alloy. These works illustrate the application of quality and engineering principles across distinct technical and organizational environments. [3] [4] [5] [6]

Earlier research includes studies on PVD-coated cutting inserts, Quality 4.0 implementation in Czech, Slovak and Polish organizations, corporate social responsibility in supplier management, and use of the EFQM model to improve processes toward sustainability. The publications provide evidence of a research program connecting operational excellence, quality systems, organizational development, and sustainable performance. [7] [8] [9] [10]

Research Impact

The supplied Scopus profile reports 148 citations across 21 documents and an h-index of 8. The broader profile information identifies 24 Web of Science documents, including 23 publications indexed in Web of Science and 22 publications in the Web of Science Core Collection. It also records 33 verified peer-review contributions in the supplied profile summary. [1]

The reported peer-review activity includes contributions to journals such as The TQM Journal, Sustainability, Total Quality Management & Business Excellence, Materials, Applied Sciences, Electronics, Forecasting, IEEE Access, Quality Innovation Prosperity, Sensors, and Social Responsibility Journal. Such activity reflects engagement with scholarly evaluation across several related research domains.

Award Suitability

For an award category concerned with applied engineering, the supplied record provides several objectively relevant indicators: an identifiable research specialization in quality engineering, a documented publication record, citation and h-index metrics, interdisciplinary work spanning engineering and materials-related subjects, and recent research applying quality methodologies to practical manufacturing and organizational problems. [1]

The suitability of the Popular Engineer Awards recognition should ultimately be assessed according to the event’s published eligibility criteria, verification procedures, nomination requirements, and independent evaluation standards. The academic record presented here can serve as supporting evidence of research activity and applied engineering relevance, but does not by itself establish that an award has been conferred.

Conclusion

Andrea Sutoova’s research profile is characterized by sustained work in quality engineering and quality management, complemented by research on Quality 4.0, manufacturing, sustainability, organizational improvement, and advanced materials. Her reported bibliometric indicators and publication portfolio provide measurable evidence of scholarly activity, while her peer-review contributions indicate participation in the wider academic publication process. [1]

The combination of applied quality methodologies, interdisciplinary engineering research, and contemporary themes such as machine learning, Lean 4.0, and Quality 4.0 establishes a coherent basis for considering her work within an applied engineering recognition context. The award assessment, however, remains dependent on the applicable award body’s independent criteria and verification.

References

  1. Elsevier. (n.d.). Scopus author details: Andrea Sutoova, Author ID 55980563600. Scopus. https://www.scopus.com/pages/authors/55980563600
  2. ORCID. (n.d.). Andrea Sutoova — ORCID record. https://orcid.org/0000-0002-6689-046X
  3. Sütőová, A., Palacka, R., Antony, J., Vijayan, G. E., Cudney, E., & Ciliberto, C. (2026). Integration of Six Sigma DMAIC methodology with machine learning in quality improvement: An application in the casting manufacturing process. The International Journal of Advanced Manufacturing Technology. Advance online publication. https://doi.org/10.1007/s00170-026-18472-0
  4. Karunakaran, A. P., Antony, J., McDermott, O., Sony, M., Sutoova, A., Kaul, A., Ghatak, R. R., Demir, S., Islam, D., & Ciliberto, C. (2026). Reducing patient waiting times in operating theatres via Lean 4.0: A qualitative study. International Journal of Health Care Quality Assurance. Advance online publication. https://doi.org/10.1108/IJHCQA-01-2026-0005
  5. Sütőová, A., Vykydal, D., Vargova, S., Palacka, R., & Kočiško, R. (2026). Competence gap analysis of early-career Quality Engineers in the field of Quality 4.0. The TQM Journal. Advance online publication. https://doi.org/10.1108/TQM-12-2024-0522
  6. Kočiško, R., Petroušek, P., Milkovič, O., Diko, P., Girman, V., Sütőová, A., Duchek, M., & Zemko, M. (2026). Tailoring the mechanical properties of Al0.4CrFe2Ni2 medium-entropy alloy via thermomechanical processing. Materials, 19(3), Article 502. https://doi.org/10.3390/ma19030502
  7. Sütőová, A., Kočiško, R., Petroušek, P., Kotus, M., Petryshynets, I., & Pylypenko, A. (2024). Study of PVD-coated inserts’ lifetime in high-pressure die casting regarding the requirements for surface quality of castings. Coatings, 14(8), 1043. https://doi.org/10.3390/coatings14081043
  8. Wawak, S., Sutoova, A., Vykydal, D., & Halfarova, P. (2023). Factors affecting Quality 4.0 implementation in Czech, Slovak and Polish organizations: Preliminary research. Advances in Production Engineering & Management, 18(3), 327–340. https://doi.org/10.14743/APEM2023.3.477
  9. Kóča, F., Pačaiová, H., Turisová, R., Sütőová, A., & Darvaši, P. (2023). The methodology for assessing the applicability of CSR into supplier management systems. Sustainability, 15(17), 13240. https://doi.org/10.3390/su151713240
  10. Sütőová, A., Teplická, K., & Straka, M. (2022). Application of the EFQM model in the education institution for driving improvement of processes towards sustainability. Sustainability, 14(13), 7711. https://doi.org/10.3390/su14137711