American Journal Of Industrial And Production Engineering
The American Journal of Industrial Engineering is an open-access, peer-reviewed journal dedicated to publishing high-quality research in the field of industrial engineering. It serves as a platform for scholars and professionals to share innovative methodologies, applications, and case studies that advance the understanding and practice of industrial engineering.
All articles published in the American Journal of Industrial and Production Engineering (AJIPE) are distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license allows others to copy, distribute, remix, adapt, and build upon the work, even commercially, as long as proper credit is given to the original author(s) and source. Authors are responsible for ensuring that their submissions do not infringe on any third-party copyrights and that all necessary permissions for copyrighted material have been obtained.
Image Authenticity Detection via YOLOv5 with Frequency Domain Feature Fusion
With continuously accelerated developments in digital image forgery technologies, authenticity verification in images is a key research direction for computer vision. The proliferation of forged images poses severe threats to information security, media credibility, and social stability. Current detection methods face limitations in real-time performance and generalization, struggling against increasingly sophisticated forgery techniques. This study proposes an efficient deep image authenticity detection framework based on the YOLO object detection model, aiming to achieve high-precision, real-time forgery region localization and classification. Traditional image authenticity detection methods, including manual inspection, watermark detection, and physical inconsistency analysis, suffer from poor generalization and low efficiency. To address these limitations, we propose an automated deep image authenticity detection algorithm based on the YOLO model. Using the IMDb-Wiki dataset from ETH Zurich's Computer Vision Lab, our method involves: (1) constructing a YOLOv5 model for portrait region identification, accurately extracting five human body parts (head, hand, body, leg, foot); (2) further localizing and cropping facial regions, enhancing image features through five preprocessing techniques for feature extraction: original image retention, Fourier transform, combined Fourier and high-pass filtering, Gaussian blur, and residual map analysis; (3) analyzing image frequency domain features using Convolutional Neural Networks (CNN) for comprehensive authenticity determination. Our experimental results demonstrate that the proposed framework achieves superior performance in terms of accuracy and real-time capability compared to existing methods. The integration of YOLOv5's multi-scale feature extraction with frequency domain analysis effectively captures subtle forgery traces, providing a robust solution for digital forensics applications.
Copyright (c) 2025 Danni Weng (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Predictive Maintenance Strategies for Reducing Downtime in Manufacturing
Predictive Maintenance (PdM) has emerged as a transformative strategy in manufacturing, shifting from traditional reactive approaches to proactive, data-driven maintenance. By leveraging advancements in Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), PdM enables manufacturers to anticipate equipment failures before they occur, thereby minimizing unplanned downtime and optimizing maintenance schedules. This paper explores various PdM strategies, their implementation challenges, and the measurable benefits observed in real-world manufacturing settings. Case studies highlight significant reductions in downtime and maintenance costs, underscoring the importance of adopting PdM for enhanced operational efficiency.
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
IoT-Driven Supply Chain Optimization in Industrial Engineering
The integration of the Internet of Things (IoT) into supply chain management has revolutionized industrial engineering by enhancing real-time visibility, automation, and decision-making capabilities. This paper explores the transformative impact of IoT technologies on supply chain optimization, focusing on key areas such as inventory management, predictive maintenance, and logistics. Through a comprehensive review of current literature and case studies, the paper identifies the benefits, challenges, and future directions of IoT implementation in supply chains. The findings underscore the necessity for strategic planning and technological investment to fully leverage IoT's potential in achieving efficient and resilient supply chains.
A Review of Techniques for Improving Productivity in High-Mix Production Systems
High-Mix, Low-Volume (HMLV) production systems present unique challenges in manufacturing due to their inherent variability and complexity. This review examines various techniques and strategies that have been proposed to improve productivity in such environments. The paper explores methodologies such as Lean Manufacturing, Six Sigma, Theory of Constraints, and Total Productive Maintenance, highlighting their applications and effectiveness in HMLV settings. Additionally, the integration of advanced technologies like automation, data analytics, and artificial intelligence is discussed as a means to enhance productivity. The review concludes with insights into future directions and potential challenges in leveraging these techniques for sustained productivity improvements in dynamic organizational environments.
The Influencing Factors of the Impermeability of Water-resistant and Sun-protective Agents and Their Action Pathways
Water-resistant sunscreens block ultraviolet rays through the construction of physical barriers and the synergistic effect of chemicals. Their anti-seepage performance is influenced by multiple factors such as the characteristics of film-forming agents, the compatibility of sunscreens, environmental conditions, and the physiological state of the skin. This article systematically reviews the molecular structure and film-forming mechanism of anti-water film-forming agents, analyzes the interaction pathways between physical and chemical sunscreens, reveals the destructive mechanisms of environmental factors such as humidity, temperature, and friction on the stability of the film layer, and explores the correlation between skin barrier function and the penetration of sunscreens. Research indicates that optimizing the molecular weight of film-forming agents, regulating the compounding ratio of sunscreens, and improving the hydrophilic and lipophilic balance value (HLB) of the formula are the key paths to enhance the efficacy of water-resistant sunscreens, providing a theoretical basis for the development of highly efficient and long-lasting sunscreen products.
Water-resistant and sun-protective agent
Copyright (c) 2025 Zimeng Wang (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Dynamic Evolution Mechanism of the Impact of Automation Technology on the Labor Market Structure
This article focuses on the dynamic evolution mechanism of the impact of automation technology on the structure of the labor market. By sorting out the development context of automation technology, it analyzes its substitution effect, productivity effect and employment creation effect on the structure of the labor market, and reveals the dynamic characteristics such as skill polarization, occupational reconfiguration and organizational form transformation. Research has found that through technological iteration and industry penetration, automation technology has driven the labor market to transform from a "pyramid" structure to a "pyramid-network" hybrid structure, forming an evolutionary trend of expanding skill premiums, the emergence of new occupations, and the networking of organizational collaboration. The research proposes countermeasures such as policy guidance, education system reform and the construction of lifelong learning mechanisms, providing theoretical support for promoting the high-quality development of the labor market.
Copyright (c) 2025 ZhongAo Wang (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
ENERGY ROUTING MECHANISM OF ENERGY STORAGE SYSTEM BASED ON ELECTRONIC POWER TECHNOLOGY
Driven by the dual forces of global energy structure transformation and the intelligent development of power systems, the energy routing mechanism of energy storage systems has become a core technology for achieving efficient energy allocation and the consumption of renewable energy. This article focuses on the application of electronic power technology in the energy routing of energy storage systems, systematically sorting out its technical principles, functional characteristics and practical value. Research shows that the energy routing mechanism based on electronic power technology significantly enhances the flexibility and reliability of energy storage systems through multi-port power conversion, bidirectional energy flow control and intelligent energy management, providing key technical support for the construction of a new type of power system.
Copyright (c) 2025 Hong Wei Song (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
THE BIOLOGICAL INTERFACE ADAPTATION MECHANISM OF GRAPHENE FLEXIBLE ELECTRODES
Graphene flexible electrodes, with their unique two-dimensional structure and excellent physical and chemical properties, have demonstrated significant advantages in the field of bioelectronic interfaces. This paper systematically explores the interface adaptation mechanism between graphene flexible electrodes and biological tissues, and conducts an analysis from four dimensions: material properties, interface interaction, biocompatibility regulation, and dynamic adaptability. Research shows that the electrical conductivity, mechanical flexibility and surface chemical modification ability of graphene jointly build the stable adaptation basis of the biological interface, while its interaction with the cell membrane, proteins and extracellular matrix determines the long-term functional stability of the electrode. By regulating the surface functional groups, conductive network structure and mechanical compatibility of graphene, dynamic synergy between electrodes and biological tissues can be achieved, providing key technical support for neural interfaces, wearable devices and implantable medical devices.
Copyright (c) 2025 Yi Li (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Process Optimization and Productivity Improvement by Waste Reduction
This research identifies the root causes of waste and defects in a sewing line within the apparel manufacturing industry by employing various lean manufacturing tools, including Value Stream Mapping (VSM), 5S, Pareto Chart, Cause-Effect Diagram and Kaizen. Key non-value-added activities such as unnecessary movement, waiting time, and manual counting were significantly reduced to 6.5%. As a result, the defect rate improved from 9.16% to 6.91%, and the 5S score increased from 2.40 to 3.80, reflecting a more organized workspace. Additionally, process cycle efficiency rose from 59.21% to 60.81%, and cycle time decreased from 192.62 seconds to 187.54 seconds per unit. Overall, this study provides effective solutions to enhance production efficiency and responsiveness to customer demand in the apparel industry. This study may provide the industries with a way out or solutions to the abovementioned drawbacks.
Copyright (c) 2025 Raihan Ahmed Joy, Shornali Akter Rumky , Sakibul Hasan, Md. Abdul Latif, Samiha Mehezabin Nitu (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Optimization Path for Gire Station Layout Based on PageRank
This article focuses on the optimization of fire station layout, aiming to explore a more scientific and reasonable layout path by introducing the PageRank algorithm. Firstly, the importance of optimizing the layout of fire stations and the limitations of the existing layout methods were expounded. Then, the basic principle and characteristics of the PageRank algorithm were introduced in detail, and the feasibility of applying it to the layout optimization of fire stations was deeply analyzed. By constructing a fire station layout model based on PageRank, the influence of key parameters of the model was explored, and a comparative analysis was conducted with other layout methods, demonstrating the effectiveness and superiority of this model in evaluating the importance of fire stations and optimizing the layout. Finally, the research results are summarized and prospects for future research directions are proposed, with the aim of providing new ideas and methods for the layout planning of urban fire stations.
OPTIMIZATION PATH FOR GIRE STATION LAYOUT BASED ON PAGERANK
Copyright (c) 2025 American Journal Of Industrial And Production Engineering https://creativecommons.org/licenses/by-nc-nd/4.0
Analysis of Cost Reduction Strategies in Industrial Engineering
Cost reduction is a key objective in industrial engineering, particularly as businesses seek to optimize their operations, enhance efficiency, and maintain competitive advantage. This paper analyzes various cost reduction strategies in industrial engineering, focusing on lean manufacturing, process optimization, and energy efficiency. We explore the effectiveness of different techniques such as waste reduction, automation, and the implementation of advanced technologies like predictive maintenance and Industry 4.0 solutions. The paper also discusses the challenges industries face in adopting these strategies and provides insights into successful case studies from different sectors. Ultimately, this analysis provides a comprehensive understanding of how cost reduction strategies can be applied effectively in industrial settings to achieve long-term sustainability and profitability.
Enhancing Production Line Efficiency through Process Automation
Process automation in production lines is revolutionizing the manufacturing industry by improving efficiency, reducing labor costs, and ensuring product consistency. This article explores various process automation technologies used to enhance production line efficiency, including robotics, artificial intelligence (AI), Internet of Things (IoT), and advanced sensors. We discuss the implementation challenges, potential benefits, and the impact of automation on productivity, product quality, and workforce dynamics. Furthermore, the article examines future trends and the growing role of automation in smart manufacturing systems.
The Influence of Industrial Engineering on Sustainable Supply Chain Design
Industrial engineering plays a critical role in shaping sustainable supply chains by optimizing processes, reducing waste, and improving the efficiency of production and distribution systems. The growing demand for sustainability in business operations has placed industrial engineering at the forefront of supply chain management, especially in designing systems that are resource-efficient, environmentally friendly, and economically viable. This paper explores the influence of industrial engineering on sustainable supply chain design, focusing on key techniques such as lean manufacturing, process optimization, and green logistics. The paper also examines real-world case studies, challenges in implementation, and future trends in sustainable supply chain design, providing a comprehensive analysis of how industrial engineering contributes to the development of sustainable practices in supply chains.
Design of Robust Manufacturing Systems: A Systemic Approach
The design of robust manufacturing systems is a critical factor in ensuring long-term sustainability, efficiency, and resilience in the face of challenges such as market fluctuations, supply chain disruptions, and technological changes. A systemic approach to manufacturing system design emphasizes the integration of various subsystems, including production processes, resource management, and technology infrastructure, to create adaptable, flexible, and efficient systems. This article explores the principles and strategies for designing robust manufacturing systems, highlighting the role of optimization, risk management, and innovation in achieving operational excellence. We also discuss the future trends and opportunities for enhancing the resilience and agility of manufacturing systems through advanced technologies and collaborative approaches.
Artificial Intelligence in Manufacturing: Enhancing Decision-Making Processes
Artificial Intelligence (AI) is increasingly being integrated into manufacturing processes to optimize decision-making, improve production efficiency, and reduce operational costs. AI-powered systems enable real-time analysis of data from production lines, predictive maintenance, quality control, and supply chain management. This paper explores the role of AI in enhancing decision-making processes in manufacturing environments, focusing on AI algorithms, machine learning techniques, and their applications in manufacturing operations. The paper also discusses the benefits and challenges associated with AI adoption in manufacturing, along with case studies and future trends in AI-driven manufacturing systems.
A Study on Multi-Objective Optimization in Production Systems
Multi-objective optimization (MOO) is a crucial approach in the design and operation of production systems, where multiple conflicting objectives must be balanced to achieve optimal performance. This study investigates the application of multi-objective optimization techniques in production systems, focusing on objectives such as cost minimization, time efficiency, resource utilization, and product quality. Various optimization methods, including Pareto-based approaches, genetic algorithms, and fuzzy logic, are explored for their effectiveness in solving complex production optimization problems. The paper also discusses the challenges in applying MOO to real-world production systems and presents case studies demonstrating the practical applications of these techniques.
Cybersecurity in Industrial Automation and Control Systems
Industrial automation and control systems (IACS) are increasingly becoming a target for cyberattacks as industries move towards greater digitalization and connectivity. The growing reliance on connected devices, IoT, and remote monitoring systems in industrial settings increases the risk of cyber vulnerabilities, which could result in significant disruptions, financial losses, and safety hazards. This paper explores the importance of cybersecurity in industrial automation and control systems, focusing on key challenges, risks, and best practices to secure these critical infrastructures. We also discuss the role of industry standards, regulatory frameworks, and emerging technologies in safeguarding IACS. Case studies and examples of cyberattacks on industrial systems highlight the need for robust cybersecurity strategies in the digital age.
The Future of Industry 5.0: Human-Centric Production Systems
Industry 5.0 represents a new era in manufacturing, where the focus shifts from automation to collaboration between humans and machines. While Industry 4.0 is characterized by intelligent automation and data-driven manufacturing, Industry 5.0 emphasizes human-centric production systems, where human workers collaborate with advanced robots, AI, and other technologies to enhance creativity, efficiency, and flexibility. This article explores the potential of Industry 5.0, highlighting the role of collaborative robots (cobots), AI-driven decision-making, and human-machine interaction in the future of production. We discuss the benefits, challenges, and opportunities of human-centric systems and their implications for the future of manufacturing.
Applications of Simulation Techniques in Industrial Manufacturing Systems
Simulation techniques have become indispensable tools in the design, optimization, and operation of industrial manufacturing systems. These techniques allow manufacturers to model complex systems, analyze different scenarios, and make informed decisions regarding system performance, resource allocation, and process optimization. This article explores the applications of simulation techniques, such as discrete-event simulation (DES), system dynamics, and agent-based modeling (ABM), in manufacturing environments. We examine how simulation can be applied to various aspects of industrial manufacturing, including production planning, resource management, quality control, and supply chain optimization. The article also discusses the challenges and benefits of implementing simulation techniques in real-world manufacturing systems.
The Role of Digital Technologies in Industrial Process Monitoring
The integration of digital technologies into industrial process monitoring systems is transforming how manufacturing and production processes are managed and optimized. Technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, and cloud computing provide real-time insights into equipment performance, production quality, and operational efficiency. This paper explores the role of these digital technologies in enhancing industrial process monitoring, focusing on their applications in predictive maintenance, quality control, and process optimization. We discuss the challenges and opportunities in implementing these technologies, along with case studies showcasing successful adoption in various industries.
Assessing the Benefits of Automation for Small-Scale Manufacturing Enterprises
Automation has long been associated with large-scale manufacturing, but it has the potential to provide significant benefits for small-scale manufacturing enterprises as well. This article explores the advantages and challenges of implementing automation in small-scale manufacturing settings, focusing on cost reduction, improved efficiency, enhanced product quality, and flexibility. By examining case studies and real-world examples, this paper assesses the impact of automation on small businesses and presents strategies for overcoming barriers to adoption. The findings suggest that with the right approach, small-scale manufacturers can leverage automation to achieve competitive advantages and sustain growth in an increasingly complex and dynamic market.
Innovations in Industrial Design: Addressing Environmental and Economic Challenges
The field of industrial design is undergoing a significant transformation, driven by the increasing need to address environmental sustainability and economic viability. Innovations in industrial design, including eco-design, sustainable manufacturing processes, and resource-efficient materials, are playing a pivotal role in minimizing the environmental impact of industrial products. At the same time, industrial designers are tasked with balancing these environmental considerations with the economic imperatives of production cost, product performance, and market competitiveness. This article explores the latest innovations in industrial design, highlighting cutting-edge technologies and approaches that address both environmental and economic challenges in product development and manufacturing.
Application of AI-Driven Predictive Analytics in Industrial Maintenance
The application of AI-driven predictive analytics in industrial maintenance is transforming how manufacturers manage equipment reliability and minimize downtime. By leveraging real-time data from IoT sensors, machine learning algorithms, and historical maintenance records, predictive analytics can forecast equipment failures before they occur, enabling timely and cost-effective interventions. This paper explores the role of AI-driven predictive analytics in industrial maintenance, discussing its applications, benefits, challenges, and real-world case studies. We examine the key technologies, including machine learning, data analytics, and condition monitoring, that power predictive maintenance systems, and explore the impact of these technologies on operational efficiency, cost savings, and equipment life cycle management.
Energy Efficiency in Industrial Production: Challenges and Innovations
Energy efficiency is a critical factor in the industrial sector as companies seek to reduce operational costs, minimize environmental impact, and meet regulatory requirements. Industrial production processes are energy-intensive, and improving energy efficiency offers significant benefits, including cost savings, reduced emissions, and enhanced sustainability. This paper explores the challenges and innovations associated with energy efficiency in industrial production, focusing on technologies, processes, and strategies that can lead to energy savings. We examine the role of industrial engineering in optimizing energy use, the adoption of energy-efficient technologies, and the challenges industries face in achieving energy savings. The paper also highlights successful case studies and discusses future trends in energy-efficient manufacturing systems.
Advanced Robotics in Industrial Production: Opportunities and Challenges
Advanced robotics is transforming industrial production by improving efficiency, precision, and flexibility in manufacturing processes. Robots are increasingly employed in tasks ranging from assembly, welding, and painting to material handling and quality control. This article explores the opportunities that advanced robotics presents for industrial production, including increased productivity, enhanced safety, and reduced labor costs. It also discusses the challenges associated with the adoption of robotics, such as high initial investment, integration with existing systems, and workforce adaptation. The article concludes with a look at the future trends in robotics and how they are expected to shape the manufacturing landscape.
Cost-Effective Strategies for Improving Industrial Process Performance
Improving industrial process performance while keeping costs low is a critical goal for organizations seeking to maintain competitiveness and profitability. This paper explores cost-effective strategies that can be implemented to improve efficiency, productivity, and quality in industrial production systems. We discuss various strategies such as lean manufacturing, process optimization, automation, and energy management, all of which can be adopted without significant capital investment. The paper highlights case studies, provides insights into the implementation of these strategies, and discusses the challenges and benefits associated with their application in industrial settings.
A Study of Lean Production Techniques in High-Volume Manufacturing Systems
Lean production techniques have revolutionized manufacturing operations by improving efficiency, reducing waste, and enhancing overall product quality. In high-volume manufacturing systems, where large quantities of products are produced under tight time constraints, the implementation of lean principles is essential for maintaining competitive advantage. This paper examines the application of lean production techniques in high-volume manufacturing environments, focusing on key methods such as Just-In-Time (JIT) production, Kaizen, and value stream mapping. We explore the benefits, challenges, and successful case studies, and discuss how lean techniques can be adapted and implemented to improve manufacturing processes in high-volume production settings.
An Integrated Approach to Product Design and Production Planning
The integration of product design and production planning is essential for optimizing manufacturing processes, improving product quality, and reducing lead times. In traditional manufacturing systems, product design and production planning are often treated as separate functions, leading to inefficiencies and misalignments. This paper explores the benefits of adopting an integrated approach to product design and production planning, focusing on techniques such as concurrent engineering, design for manufacturability (DFM), and just-in-time (JIT) production. We discuss the challenges, key strategies, and best practices for integrating these two functions, along with case studies highlighting successful implementation in various industries.
Collaborative Robots in Industrial Manufacturing: Enhancements in Productivity
manufacturing by enhancing productivity, improving safety, and promoting flexibility in production processes. These robots are designed to work alongside human operators, assisting in tasks such as material handling, assembly, inspection, and packaging. Unlike traditional industrial robots, cobots are safe to work in close proximity to humans without the need for safety cages or barriers. This article explores the role of collaborative robots in industrial manufacturing, examining their impact on productivity, efficiency, and workplace safety. We discuss the benefits of cobots in diverse manufacturing sectors and the challenges associated with their integration into existing production systems.