Key papers in Industrial and Manufacturing Engineering
Pofolia’s corpus holds 52 papers from the Industrial and Manufacturing Engineering subfield (2012–2026). The list below starts with the most cited.
Most cited
Ranked by citation count. Because citations accumulate over time, this list naturally leans towards work published a few years ago; for where the field is now, see “recently added”.
PRODUCT DESIGN AND DEVELOPMENT
2018 · 5,551 citations
This paper introduces integrative product development techniques designed to align marketing, design, and manufacturing functions.
Digital transformation: A multidisciplinary reflection and research agenda
Journal of Business Research · 2019 · Q1 · SJR 3.00 · FWCI 168.49 · 4,843 citations
This paper identifies three distinct stages of digital transformation—digitization, digitalization, and digital transformation—and outlines growth strategies, required assets, and capabilities for digital firms.
Digital Twin in Industry: State-of-the-Art
IEEE Transactions on Industrial Informatics · 2019 · Q1 · SJR 2.00 · FWCI 210.99 · 3,943 citations
This paper provides a comprehensive review of Digital Twin (DT) technology's state-of-the-art applications in industry, covering its key components, development, and use cases.
Digital Twin in manufacturing: A categorical literature review and classification
IFAC-PapersOnLine · 2018 · FWCI 131.91 · 3,209 citations
A literature review reveals a lack of common understanding and inconsistent application of the 'Digital Twin' (DT) concept across manufacturing disciplines.
Industry 4.0: state of the art and future trends
International Journal of Production Research · 2018 · Q1 · SJR 2.00 · FWCI 276.68 · 3,125 citations
Industry 4.0, a major initiative for integrated manufacturing, is emerging from the convergence of technologies like cyber-physical systems and IoT, but lacks powerful formal and systems methods for full exploitation.
Design Principles for Industrie 4.0 Scenarios
2016 · 2,941 citations
This paper identifies key design principles for Industrie 4.0, a concept central to the next industrial revolution driven by the Internet of Everything.
Intelligent Manufacturing in the Context of Industry 4.0: A Review
Engineering · 2017 · Q1 · SJR 1.00 · FWCI 207.58 · 2,816 citations
This review comprehensively examines intelligent manufacturing within Industry 4.0, highlighting its role in enabling mass customization, improved quality, and faster production of individualized products.
Digital Twin: Enabling Technologies, Challenges and Open Research
IEEE Access · 2020 · Q1 · FWCI 152.63 · 2,565 citations · Open access
This paper reviews Digital Twin technology, defining it as the seamless integration of data between physical and virtual machines, and categorizes recent research by application areas like manufacturing, healthcare, and smart cities.
2013 IEEE Conference on Computer Vision and Pattern Recognition
2013 · 2,401 citations
This paper introduces a novel discriminative approach for non-blind image deblurring, overcoming limitations of existing generative and manual methods.
Industry 4.0 and Industry 5.0—Inception, conception and perception
Journal of Manufacturing Systems · 2021 · Q1 · SJR 3.00 · FWCI 176.69 · 2,331 citations
This paper clarifies the distinctions between Industry 4.0 and the newly announced Industry 5.0, highlighting Industry 4.0 as technology-driven and Industry 5.0 as value-driven.
Characterising the Digital Twin: A systematic literature review
CIRP journal of manufacturing science and technology · 2020 · Q1 · SJR 1.00 · FWCI 21.56 · 2,189 citations
A systematic review of 92 publications consolidates the concept of Digital Twins, identifying 13 core characteristics and a framework for their operation.
Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems
International Journal of Industrial Engineering Computations · 2015 · Q2 · FWCI 135.03 · 2,054 citations · Open access
A novel optimization algorithm, Jaya, has been developed that moves solutions towards the best and away from the worst, requiring only common control parameters.
Fundamentals of Microfabrication
2018 · FWCI 30.24 · 2,019 citations
This textbook update covers recent advances in microfabrication technologies, methods, and applications, reflecting the field's rapid growth and miniaturization down to the molecular level.
Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal
International Journal of Production Research · 2017 · Q1 · SJR 2.00 · FWCI 30.04 · 1,996 citations
This systematic review analyzes academic progress in Industry 4.0 up to June 2016, identifying current research directions, applied standards, and software/hardware, while also highlighting deficiencies and proposing future research agendas.
2014 IEEE Conference on Computer Vision and Pattern Recognition
2014 · 1,772 citations
This paper introduces a novel discriminative approach for non-blind image deblurring, outperforming existing methods in efficiency and restoration quality.
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
IEEE Access · 2020 · Q1 · FWCI 127.58 · 1,743 citations · Open access
This paper reviews digital twin methodologies and techniques from a modeling perspective, highlighting their transformative role in designing and operating cyber-physical systems.
A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises
Procedia CIRP · 2016 · FWCI 93.98 · 1,679 citations
A new empirically grounded model is proposed to assess Industry 4.0 maturity in discrete manufacturing, extending previous models by integrating organizational aspects alongside technology.
Journal of Industrial Engineering
Journal of Industrial Engineering · 2017 · 1,636 citations
A model was developed to identify the best sales forecasting method for jute yarn, finding that the Winters additive model yielded the lowest forecasting errors.
Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison
IEEE Access · 2018 · Q1 · FWCI 113.89 · 1,632 citations
This paper reviews and compares big data and digital twin technologies, highlighting their complementary roles in advancing smart manufacturing and Industry 4.0.
The Traveling Salesman Problem
2019 · 1,631 citations
This chapter introduces the Traveling Salesman Problem (TSP), a well-known combinatorial optimization challenge focused on finding the shortest route visiting multiple locations.
Recently added
Nyx: Greybox Hypervisor Fuzzing using Fast Snapshots and Affine Types
Figshare · 2026 · 33 citations
NYX is a new hypervisor fuzzer that uses fast snapshots and a novel mutation engine with affine types to detect vulnerabilities. It uncovered 44 new bugs, including 22 with CVEs requested, significantly outperforming existing methods on complex targets.
YOLOv8: A Novel Object Detection Algorithm with Enhanced Performance and Robustness
2024 · 1,621 citations
YOLOv8, a new object detection algorithm, improves small object detection and video analysis using attention mechanisms, dynamic convolution, and voice recognition, outperforming state-of-the-art benchmarks in accuracy and efficiency.
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing · 2023 · Q1 · SJR 2.00 · 1,303 citations
A novel closed-form approximation for the unbiased inverse of the Anscombe variance-stabilizing transformation is presented, offering a computationally efficient alternative to existing iterative methods.
Industry 4.0 and Industry 5.0—Inception, conception and perception
Journal of Manufacturing Systems · 2021 · Q1 · SJR 3.00 · FWCI 176.69 · 2,331 citations
This paper clarifies the distinctions between Industry 4.0 and the newly announced Industry 5.0, highlighting Industry 4.0 as technology-driven and Industry 5.0 as value-driven.
Digital Transformation: An Overview of the Current State of the Art of Research
SAGE Open · 2021 · Q1 · FWCI 86.12 · 1,177 citations · Open access
A systematic literature review identifies technology as the primary driver of digital transformation (DT) and classifies DT research into technological, business, and societal impact clusters.
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