Industrial Engineering Research Articles

A Lagrange barrier approach for the minimum concave cost supply problem via a logarithmic descent direction algorithm

The minimisation of concave costs in the supply chain presents a challenging non-deterministic polynomial (NP) optimisation problem, widely applicable in industrial and management engineering. To approximate solutions to this problem, we propose a logarithmic descent direction algorithm (LDDA) that utilises the Lagrange logarithmic barrier function. As the barrier variable decreases from a high positive value to zero, the algorithm is capable of tracking the minimal track of the logarithmic barrier function, thereby obtaining top-quality solutions. The Lagrange function is utilised to handle linear equality constraints, whilst the logarithmic barrier function compels the solution towards the global or near-global optimum. Within this concave cost supply model, a logarithmic descent direction is constructed, and an iterative optimisation process for the algorithm is proposed. A corresponding Lyapunov function naturally emerges from this descent direction, thus ensuring convergence of the proposed algorithm. Numerical results demonstrate the effectiveness of the algorithm.

Heat transfer inspection and entropy optimization in water/MoS2-SiO2 Casson hybrid nanofluid flow with quadratic radiation ray over an exponentially contracting permeable Riga surface: Duality and stability analysis

In this study, we have examined the primary behaviour of a hybridized electro-magneto-non-Newtonian MoS2-SiO2/H2O nanofluid over a porous Riga surface that is exponentially contracting, in particular its flow dynamics and heat transfer characteristics. The key factors of this research are the presence of quadratic thermal radiation over the Riga surface under velocity slip and convective boundary. We have solved the highly circuitous coupled partial differential equations system by utilizing the bvp4c numerical method with MATLAB programming. A dual solution is determined based on a certain amount of mass suction parameter and shrinking parameter under the critical value range; beyond that value, no solution exists. We investigated the stability of the dual solutions by determining the minimal eigenvalue. An evaluation of the temporal stability of these solutions reveals that only the first solution remains stable. This is supported by the positivity of the smallest eigenvalues (β1> 0), indicating stability. Conversely, for the second solution, the smallest eigenvalues (β1< 0) are negative, signifying its instability. It can be seen that the nanofluid temperature is substantially enhanced for both branches of solution for the quadratic thermal radiating parameter, Eckert number, and Biot number. It was found that, in the first solution branch, the velocity layout was boosted with the velocity slip factor while reduced by enhancing the Casson parameter, whereas, in the second solution branch, the opposite behavior was observed. As the suction parameter increases, the heat transfer coefficient for the first solution is decreased by about 0.5 % and increases by about 0.75 % for the second solution branch. Quadratic thermal radiation parameter Nr significantly impacts the Nusselt number, as it is reduced by approximately 27.44 % and 28.72 % for the first and second solution branches, respectively. The shear stress coefficient is decreased by about 29.32 % for the first solution branch with contracting parameter λ. Because the Riga plate, paired with Casson nanofluid flows, has industrial and civil engineering applications, this study's thermal relevance makes it applicable to a wide range of industrial and engineering disciplines.

Negative Emotions and e-Learning Academic Performance of Engineering Students in a Private University

One of the early pandemic COVID-19 effects on the educational sector is that learning activities needto be conducted fully online (e-learning). This circumstance can trigger negative emotions thatcontribute to students’ academic performance. This study aimed to find empirical data regarding therelationship of negative emotions and students academic performance in this particular situation. Thestudy was a cross-sectional quantitative method. Questionnaire of negative emotion (DASS-21)Indonesian version was deployed using google form to students of Industrial Engineering andInformation Systems class of 2020 using convenience sampling. 292 questionnaires were returnedand used. Findings: All three negative emotions (depression, anxiety, and stress) were experiencedby students at different levels. Negative emotions had different correlations to academic performance.There were no significant differences between anxiety and depression to students’ academicperformance (anxiety: F (3) = 2.202, ρ = 0.088, depression: F (2) = 1.397, ρ = 0.249). Two-wayANOVA showed that students who experienced mild stress performed better than those with normalstress category (F (1) = 3.933, ρ = 0.048). Female students significantly had better academicperformance compared to male students (ρ (0.001) &lt; α= 0.05)) and that students experienced mildstress, performed better than those with normal stress category. Managing stress at a moderate levelis beneficial and can be done by media or counseling or other catharsis methods. Further study usinglarger samples from non engineering majors and randomized sampling is needed for generalizationas well as identifying factors that contribute to e-learning performance in a special situation.

Integrated FEM-Multibody Co-Simulation of Additively Manufactured Hip Prosthesis containing cracks.

The increase in life expectancy and attention to the quality of life of elderly people spurred the need, in the last decades, to increase the capabilities of medical and surgical techniques. Among these, the development of prosthetic implants has been a staple of biomedical engineering research since the 70’s. In order to satisfy the challenging demands, the latest novelties in industrial engineering are being tested in their applicability to subjects. The 3D printing of metal alloys can produce a highly customizable product, which, after the proper heat treatments, can possess adequate mechanical properties to ensure a satisfactory component life. Defective products are often the results of wrong or absent post-processing treatments which may cause an uncontrolled crack propagation and a premature total failure of the implant. The behavior of such a product, with various critical crack conditions, was investigated by an integrated MBD-FEM co-simulation environment, focused on a femur subjected to total hip replacement. It was concluded that the Stress Intensity Factor (SIF) computed by the model is compatible with the premature failures experienced by patients, and as such, this model opens the possibility for further analyses aimed at understanding the role of defects on the durability of prothesis

Development and effectiveness of short video tutorials in basic turning learning to enhance students' cognitive ability

This study aims to develop and evaluate the effectiveness of short tutorial videos in teaching the essential operation of lathe machines in mechanical engineering. Utilizing the ADDIE model (Analysis, Design, Development, Implementation, Evaluation), the research was conducted at SMK N 1 Sumatera Barat, involving 65 vocational school students. The short tutorial videos were designed to enhance students' comprehension and cognitive ability in lathe machine operations, addressing the challenges posed by traditional teaching methods. Data were collected through questionnaires and practical tests to assess students' understanding and skills. The findings revealed that the short tutorial videos significantly improved students' comprehension and cognitive ability, although variations in understanding levels were observed. Normality tests confirmed a normal data distribution, allowing for the use of paired sample t-tests, which indicated no significant difference between the Mechanical Engineering and Industrial Mechanical Engineering groups after using the tutorials. Validation by media and content experts demonstrated the high quality and relevance of the instructional material. This study underscores the importance of developing more interactive and adaptive learning media and highlights the need to explore further other factors influencing cognitive ability.

Key technology for digital twins in the architecture, engineering, and construction industry: new advances in point cloud semantic segmentation algorithms for buildings

Key technology for digital twins in the architecture, engineering, and construction industry: new advances in point cloud semantic segmentation algorithms for buildings

Investigating cross-docking criteria for raw materials with hybrid MCDM

The cross-docking process involves unloading raw materials from incoming vehicles and immediately loading them onto outgoing vehicles. This can greatly improve supply chain operations and expedite transportation to the factory. By minimizing warehouse storage expenses, space requirements, and inventory management, the process can be streamlined effectively. In industries where production profiles need to be responsive to market demands, the location of the cross-docking facility and transportation planning are crucial. This article aims to investigate the criteria for selecting a cross-docking location, using a case study of Arta Profile Company in Ardabil. The research population includes all industrial engineers and production planners in the company, with 10 industry experts selected for this study. The analytic network process (ANP) and grey complex proportional assessment (COPRAS-G) methods were used to compare and prioritize cross-docking locations. Additionally, the fuzzy DEMATEL method was used to determine the strength of connections between different locations. The COPRAS-G approach helps decision-makers make informed decisions by evaluating different options and their importance. The industry experts identified 28 criteria for this study. The results from the network analysis method showed that the most important criterion is the vehicle routing problem (VRP), with a value of 0.46. According to the ANP technique, strategic decision-making is the best option. The fuzzy DEMATEL method revealed that distribution centers are the most important factor, followed by reduced delivery/distribution operations, and finally, the cost of late or early delivery.

Industrial and Large Engines

Industrial and Large Engines

Assessment of the risk to the health of the population living in the zone influenced by atmospheric emissions from the engineering industry

Introduction. During operation, machine-building enterprises emit pollutants that can negatively affect the health of the population. The study aims to determine the impact of emissions from a machine–building plant, as well as background atmospheric pollution, on the health risk of the population of Novokuznetsk. Materials and methods. The work used data from the volume of maximum permissible emissions of a machine-building plant. The researchers calculated the maximum and average concentrations of pollutants using the "ECOcenter – Standard" program at 36 exposure points selected on the city map. Experts determined the maximum permissible concentrations of pollutants in the atmosphere in accordance with SanPiN 1.2.3685-21. The authors calculated the risks to public health in accordance with the Guidelines R 2.1.10.1920-04. The classification of risk levels was carried out on the basis of MP 2.1.10.0156-19. 2.1.10. Scientists also made a risk assessment considering background atmospheric pollution. Results. Specialists carried out a risk assessment from exposure to nitrogen dioxide, carbon monoxide, sulfur dioxide, carbon (soot), inorganic dust, hexavalent chromium. The maximum and average concentrations of pollutants, as well as the maximum concentrations calculated taking into account background pollution, did not exceed the maximum permissible level. The average concentrations of nitrogen dioxide and hexavalent chromium, taking into account the background, exceeded the hygienic standard. The values of the hazard indices for acute and chronic exposures without taking into account the background, as well as for acute exposures taking into account the background, corresponded to the minimum (target) risk level. The values of the hazard indices for chronic inhalation effects, considering the background, corresponded to the alarming risk level at five points, amounting to 3.084–3.800. With chronic exposure, taking into account the background, an alarming level of risk was revealed for the effect on the respiratory organs (at four points the hazard index was 3.117 to 3.616) and blood (at three points the hazard index was in the range from 3.090 to 3.433). The total individual carcinogenic risk, excluding background, did not exceed the permissible level, ranging from 1.08×10–8 to 2.43×10–7 at different points, taking into account the background, amounted to 1.79×10–4–2.26×10–4, which corresponds to an alarming level. Hexavalent chromium makes the main contribution to the formation of carcinogenic risk. Limitations. Calculated concentrations of pollutants were used to assess the risks. Conclusion. The risks from exposure to atmospheric emissions from the machine-building plant correspond to the minimum (target) level. Background concentrations of toxic substances in chronic inhalation exposures determine an alarming level of non-carcinogenic risk at five points, as well as an alarming level of carcinogenic risk at all points of exposure. Ethics. This study did not require the conclusion of the Ethics Committee.

Integrating Web-Based Weather Data into Building Information Modeling Models through Robot Process Automation

The rapid evolution of digital technologies has revolutionized the architecture, engineering, and construction (AEC) industry, driving the wide-spread adoption of digital twins for structures. These virtual replicas, developed using Building Information Modeling (BIM) methodology, incorporate extensive information databases, proving indispensable for enhancing project management throughout a structure’s entire lifecycle and towards smart city development. As the impact of climate change continues to grow, hazardous weather alerts play a critical role as an early-warning system that notifies stakeholders of imminent threats, thereby influencing decision-making processes in construction projects. Surprisingly, despite its evident value, the integration of alert systems for hazardous weather conditions into BIM is often overlooked. To fill this gap, this paper proposes Robot Process Automation (RPA) protocols to automate the integration of real-time weather parameters into a structure’s BIM models. These very protocols are also used as alert systems, enabling the timely notification of stakeholders in the event of detected hazardous weather conditions. The effectiveness of the proposed methodology is demonstrated through its practical application in enhancing the safety of an actual building in Viña del Mar, Chile.

Integrating Agile Methodologies and Gamification for Student Engagement and Success

The article highlights a flexible and adaptable approach for the development of game like activities for higher education students from Politehnica University of Timisoara, Romania. The approach embraces agile methodologies to guide the iterative development process of educational games and consists of several key elements. First, it underlines the importance of defining clear learning objectives and aligning them with the game’s design. Second, it encourages multidisciplinary collaboration between teachers and instructional designers to deliver relevant information to students, but also appropriate to their learning styles and needs. Regarding engineering problems and methods, students frequently encounter several difficulties. For this reason, the article attempts to provide an organized and engaging learning environment that encourages active participation and information retention. In industrial engineering, most of the students’ exposure is to theoretical materials; nevertheless, there are several ways to give them practical experience with the topics they are studying. Using a comprehensive review of the literature, the article explores the pedagogical benefits, challenges, and practices associated with the use of agile methodologies in education. Agile methods are very based on collaboration, teamwork, flexibility, and participation, and help create a more relaxed learning environment to support students' increasing need for control over their learning path. Throughout regular communication and feedback cycles, students can iterate on content and pedagogical approaches, resulting in activities and games that are more engaging and effective for learning. In the end, the paper presents the conclusions of the authors on the current advantages and limitations of using this approach based on agility and game-based learning in higher education.

Computational Models of Dynamic Load Sources for Modeling of Construction Structures Operation Used in Monitoring of Technical Condition of Buildings and Structures

This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is due to the steadily increasing intensity of such loads on buildings and structures in megacities, as well as the acute practical problem of significant differences in the dynamic characteristics of buildings and structures obtained as a result of mathematical modeling and determined by experimental methods. The article presents research materials on computational equivalent models of dynamic load sources for numerical modeling of the behavior of construction structures under their influence, using the method of vibroacoustic analogies. The article examines models of sources of dynamic impact on construction sites. Algorithms and final formulas for computational modeling of the simplest sources of dynamic load are developed using the method of vibroacoustic analogies. The dynamic properties of the simplest dynamic load sources were analyzed. A significant difference between the computational models of real and ideal dynamic load sources. The article presents research and development results intended for calculating the distribution of dynamic loads on elements of construction structures in industrial and civil engineering projects located in areas with high levels of transport vibrodynamic impacts. An important property of the proposed computational equivalent models of sources of dynamic impact on building structures is the possibility of computational verification of critical elements, points, or nodes of load-bearing structures of buildings and structures under dynamic overloads. The position of these critical elements, points, and nodes of load-bearing structures under dynamic loads can differ significantly from their position determined using static and quasistatic computational modeling methods.

Beyond the hype: quantifying the impact of VR visualization on client preferences and price perception in AEC client pitching

The architectural, engineering, and construction (AEC) industries are using virtual reality (VR) to improve engagement and interactions. However, VR visualization’s effectiveness in client pitching is unclear. This study analyzes how VR visualization affects customer preferences and price, as well as the complex interaction between architectural scale and demographic aspects. The outcomes enable more precise and personalized VR implementation. VR is the favoured alternative, with 14% price premiums according to a statistical analysis. Its realistic field of view and immersion allow users to explore sites at their own leisure. VR represents all architectural typologies and sizes without compromise. This VR utilization can serve as an ameliorating tool to augment marketing and sales for the client pitching stage in the AEC sectors.

Hygroscopic effects on sound absorption of multiscale bio-based porous materials

Hygroscopicity is the tendency of a material to absorb moisture from the surrounding environment. This work investigates hygroscopic effects on the sound absorption properties of multiscale bio-based materials. It is shown how moisture can significantly alter their acoustic performance as well as how to recover their original dry-material performance by means of heat treatment, akin to thermal reactivation commonly used in the chemical engineering industry. The results of an experimental campaign, conducted over an extended period of time, is reported. Possible theoretical explanations on the reduced acoustic performance of activated carbons by hygroscopic effects and the achieved improvement, obtained after heat treating the material, are also presented. The results of this work provide useful insights on the long-term acoustic behaviour of multiscale bio-based materials for noise control applications.

First Principles Unveiling Equilibrium Shapes for Understanding Morphological Growth Mechanisms in Alumina Polymorphs

Understanding the morphological evolution of crystals is crucial for industrial applications and surface engineering. This study employs a multifaceted analytical approach to comprehensively analyze gibbsite, boehmite, η, γ, δ, θ, κ, and α-Al2O3. Density Functional Theory (DFT) surface energy calculations provide essential viewpoints into facet exposure and stability, enriching our comprehension of growth patterns. Using the Bravais–Friedel–Donnay–Harker (BFDH) method, a meticulous investigation into morphological properties reveals equilibrium shapes for each structure. Crucially, our models unveil the inaugural equilibrium shapes for structures previously undocumented in the literature (e.g., η, δ, θ, and κ-Al2O3). The study explores morphological growth process during phase transitions from gibbsite and boehmite to alpha alumina, emphasizing nucleation and dissolution preferences for specific facets. A grain analysis, considering bulk energy, surface area, and volume, designates α-Al2O3 as the most stable phase, offering valuable standpoints on thermodynamics and indicating a direct correlation between facet area and volume. Additionally, a comprehensive 3D surface energy mapping offers intricate visualization of facet interactions, providing valuable viewpoints into the complex relationships between surface energy, facet area, and interplanar distance. Comparisons of Fourier-transform infrared spectroscopy (FTIR) spectra, exclusively within the 200–400 cm-1 range, underscore close agreement between theoretical and experimental spectra, consistent with the expected reduction in specific surface area during polymorphic transformation.

Smart Factory integration in industrial engineering curriculum: Preparing students for industry 4.0 challenges

This paper discusses the integration of Smart Factory technology into Industrial and Systems Engineering education, focusing on its transformative impact and educational implications. Smart factories are revolutionizing the modern manufacturing industry by leveraging Cyber-Physical Systems (CPS) and cutting-edge technologies. Through the integration of Artificial Intelligence (AI) and the Internet of Things (IoT), these factories enhance production efficiency, minimize costs, and elevate the overall quality of their goods and services. Understanding the impact of smart factories and the educational implications that follow from this technology is crucial. Doing so enables us to prepare students for the challenges of the modern manufacturing industry, fostering a more informed, skilled, and adaptable workforce. Therefore, this research highlights the benefits of incorporating smart factory concepts into industrial engineering education to prepare students for “Industry 4.0” challenges. By providing hands-on experience with smart factory technology, this research aims to enhance industrial engineering students' theoretical knowledge and practical understanding of smart factories.

Preface

Over the last 6 years, MEIE has been held in various locations, including in-person conferences in Hangzhou (2018 &amp; 2019), an online conference for COVID-19 (2020), a hybrid event in Kunming (2021), an online conference (2022) and a hybrid event in Sanya (2023), attracted participants from more than 14 countries and regions including Sweden, Canada, the United States, Australia, Singapore, South Korea, and Malaysia. The 7th International Conference on Mechanical, Electric, and Industrial Engineering (MEIE2024) was organized by the College of Mechanical Engineering, Donghua University, China, co-organized by Chinese Institute for Quality Research, the School of Mechanical Engineering and Mechanics, Ningbo University, China, the Shanghai Society for Modern Design Theory and Methodology Research, and Shanghai Graphics Society. It was successfully held during May 21-23, 2024 in Yichang, China and online. This event attracted over 100 participants from all over the world from China, Sweden, USA, Canada, Germany, Pakistan, and etc., and addressed both basic research and the societal/industrial-technological needs within mechanical, electric and industrial engineering. Conference program was divided into 4 sessions: keynote speeches, invited speeches, oral presentations and poster presentations. During these sessions, presenters shared their latest achievements and audiences were actively participated as well. The MEIE organizing committee extend their sincerest gratitude to all who have supported the conference in their ways, to the authors who have chosen this platform to publish their works and communicate with peers, to the participants who took an interest and attended the conference in person and/or online, to the chairs and committee members who have been indispensable in lending their professional expertise and judgment, to the keynote speakers who generously shared their vision and passion, and to the reviewers who held up the faith of being a scholar and contributed their experience and honest opinions. It has been a pleasure and honor working alongside them, and we look forward to future cooperation with them at future MEIE conferences to come. Finally, our sincere gratitude goes also to the IOP Publishing editors and managers for their helpful cooperation during the preparation of the conference proceedings. On behalf of the Organizing Committee of MEIE 2024. List of MEIE2024 Committee members are available in this Pdf.

Circular supply chain for smart production in Industry 4.0

Sustainable practices in industrial engineering are not just ideal but necessary. The push for Circular Supply Chain (CSC) in Industry 4.0 has become increasingly vital. Motivated by this, this study proposed the UNISONE framework, integrated with advanced smart production technologies grounded in CSC principles. The proposed framework resulted in enhanced operational efficiency and a sustainable production system that significantly minimizes waste. The research was validated through an empirical study within a bearing factory, successfully demonstrating the framework’s efficacy and creating value within the CSC paradigm. Key findings include the impact of different signal-to-noise ratios on model performance, with peak test accuracy at a noise ratio of 0.6, and the best results of 85.32% accuracy achieved by combining sparse and noise reduction autoencoder techniques in generative artificial intelligence. This study underscores the framework’s potential to address industrial engineering challenges and promote scalable, efficient, and eco-conscious manufacturing, benefiting both the environment and the economy.

Mutual stacked autoencoder for unsupervised fault detection under complex multi-residual correlations

Due to the increasing complexity of variable relationships, fault detection has garnered significant attention, as it is crucial for ensuring industrial safety and engineering reliability. Traditional detection methods can be classified as twofold: global-based and local-based strategies, which respectively focus on mining macro- and micro-level information. However, our theoretical derivation and experiment results reveal that some spurious assumptions, such as local groups and their provided information are mutually independent are implicitly adhered to but are hardly satisfied in unsupervised fault detection under real industrial scenarios. Hence, this study introduces a novel mutual stacked autoencoder (M-SAE) which can be divided into three sub-networks: L-Net, R-Net, and M-Net. L-Net enriches local information learning through multiple local backbones by incorporating the unsupervised clustering algorithm. R-Net, employing a multi-scale attention mechanism, leverages complete local information for residual strength calculation and utilizes local features to capture residual information within the latent feature space. M-Net fuses the multi-scale local feature information to perform a reconstruction for each local. A multitask entropy-aided loss function is introduced to enrich local details, the global structure, and the residual associations. Finally, results on eleven datasets validate the high-performance of the proposed M-SAE and the ablation experiments demonstrate the efficacy of each component in M-SAE, confirming that this research effectively and accurately addresses multivariable industrial fault detection tasks, thereby enabling timely interventions that are crucial for maintaining operational safety in real-world scenarios.

Fostering a Synergistic Approach to Curriculum Development and TVET-Engineering Qualifications

The involvement of various stakeholders, aligning diverse interests, and evolving industry requirements are some areas that need careful consideration. The dynamics of power and authority between collaborating partners can affect the efficacy of the collaborative relationship; hence, further study is required to identify obstacles in such partnerships and propose solutions for overcoming them. This study aims to build a collaboration paradigm between the TVET engineering sector and the industry, emphasizingcurriculum development and TVET engineering credentials. This quantitative study employs a survey to collect information from 115 Malaysian technologists in three fields. Simple random selection ensures accurate demographic representation and an even distribution of bias. Four experts developed and validated a questionnaire. Data was evaluated using PLS-SEM 3.3.9 software, algorithms, bootstrapping, and blindfolding techniques. The measurement model evaluates the items' precision under validity and reliability requirements. The results indicate a significant relationship between the certification system and curriculum development. The model has a high predictive power value with a significant contribution from the free extract. The influence of size is likewise considerable, but the effect of curriculum TVET is minor. The findings provide valuable insights into the predictive validity of the model and its possible curriculum development applications. Adeliberate effort is required to overcome obstacles such as lack of coordination, scarce resources, and low public awareness.