Hasil untuk "Industrial engineering. Management engineering"

M. Dumas, M. Rosa, J. Mendling et al.

Zimeng Zhao, Haoyun Li, Yangyang Peng et al.

Smart clothing with adaptive personal thermal management functionality is highly desirable for wearing comfort and energy efficiency. However, due to the lack of common materials that can fabricate dynamic thermoregulation fabrics, translating the existing technologies to commercial applications remains challenging. Herein, leveraging an industrial textile manufacturing approach, a hierarchically programmed meta‐louver fabric with switchable modes for both hot and cold is developed. The efficacy of adaptive pore channels by manipulating the orientation of chiral knit loops to regulate water evaporation, as well as thermal convection and radiation, is experimentally demonstrated. In sharp contrast to current pore‐actuated smart textiles, the designed meta‐louver fabric gains its adaptive thermoregulation capacity directly from the multiscale textile structure engineering, ranging from the single‐helical‐fiber enabled yarn actuators to pre‐tension induced chiral‐helical knit loops. This strategy is shown to be also effective for other fiber materials, such as cotton, and thus provides a universal paradigm for a new family of metamaterials by engineering the interconnection of multiscale structures.

Hui Feng, Yang Yue, Yan Zhang et al.

Abstract Tissue engineering holds great potential for tissue repair and rejuvenation. Plant-derived exosome-like nanoparticles (ELNs) have recently emerged as a promising avenue in tissue engineering. However, there is an urgent need to understand how plant ELNs can be therapeutically applied in clinical disease management, especially for tissue regeneration. In this review, we comprehensively examine the properties, characteristics, and isolation techniques of plant ELNs. We also discuss their impact on the immune system, compatibility with the human body, and their role in tissue regeneration. To ensure the suitability of plant ELNs for tissue engineering, we explore various engineering and modification strategies. Additionally, we provide insights into the progress of commercialization and industrial perspectives on plant ELNs. This review aims to highlight the potential of plant ELNs in regenerative medicine by exploring the current research landscape and key findings.

Min Pei, Jianke Yu, Chen Chen et al.

Inés Pérez-Gonzalo, Florentino Alvarez-Antolin, Alejandro González-Pociño et al.

This study investigates the mechanical, tribological, and electrochemical behaviour of a novel precipitation-hardenable martensitic alloy produced by selective laser melting (SLM). The alloy was specifically engineered with an optimised composition, free from cobalt and molybdenum, and featuring reduced nickel content (7 wt.%) and 8 wt.% chromium. It has been developed as a cost-effective and sustainable alternative to conventional maraging steels, while maintaining high mechanical strength and a refined microstructure tailored to the steep thermal gradients inherent to the SLM process. Several ageing heat treatments were assessed to evaluate their influence on microstructure, hardness, tensile strength, retained austenite content, dislocation density, as well as wear behaviour (pin-on-disc test) and corrosion resistance (polarisation curves in 3.5%NaCl). The results indicate that ageing at 540 °C for 2 h offers an optimal combination of hardness (550–560 HV), tensile strength (~1700 MPa), microstructural stability, and wear resistance, with a 90% improvement compared to the as-built condition. In contrast, ageing at 600 °C for 1 h enhances ductility and corrosion resistance (Rp = 462.2 kΩ; Ecorr = –111.8 mV), at the expense of a higher fraction of reverted austenite (~34%) and reduced hardness (450 HV). This study demonstrates that the mechanical, surface, and electrochemical performance of this novel SLM-produced alloy can be effectively tailored through controlled thermal treatments, offering promising opportunities for demanding applications requiring a customised balance of strength, durability, and corrosion behaviour.

Ayda Mussa Yousif Abdulrahman, Rafiduraida binti Abdul Rahman

This research aims to investigate the current operational status of the Ajman Police, focusing on identifying elements and issues that affect operational excellence. Using change management models, including Kotter's 8 Step Model and the ADKAR Model, the paper critically examines the hierarchical structure of the Ajman Police, its specialist groups, and their performance indicators. The problem statement highlights the negative impact of traditional and rigid organizational structures on innovation, responsiveness, and the limitations of implementing effective public safety measures, prevention, and community policing. The research design adopted is a qualitative methodology, and a sample of senior police officers was interviewed to record their views on the issues of operation and preparedness to change. In conducting the study, Semi-structured interviews were conducted with 10 participants. Results indicate that the Ajman Police has already ventured into technological advancements and civil policing. However, there are still gaps in continuous development, innovation, and the implementation of modern change management practices. The research proposes a culturally, operationally, and technologically oriented framework for change management, specifically tailored to the context of the Ajman Police. The study makes a significant research contribution to both the practice and theory fields by providing a guideline for a change management roadmap for the Ajman Police and other similar agencies, ensuring operational excellence in fast-changing environments.

Sara Bunian, Meshari A. Al-Ebrahim, Amro A. Nour

The use of artificial intelligence (AI), machine learning (ML), embedded systems, cloud computing, Big Data, and the Internet of Things (IoT) is influencing the paradigm shift toward advanced technologies and highly efficient manufacturing processes in Industry 4.0. The need for AI is increasing day by day due to the rapid progress contributed by the successful utilization of intelligent and learning machines. AI is implanted in smart manufacturing to solve crucial sustainability issues and to optimize the supply chain, use of energy and resources, and waste management. Industry 4.0 is striving for customer-driven manufacturing capabilities for enhanced agility, sustainability, and productivity. AI and ML are primarily used in the optimization and monitoring of modern industrial processes. Industrial AI system research is a multidisciplinary field with contributions from ML, robotics, and IoT. Industrial AI develops, validates, deploys, and maintains solutions for sustainable manufacturing. Because of the rise in cloud computing and a significant decrease in data storage costs, a massive amount of information and data can now be stored and transmitted to ML and AI algorithms to streamline and automate different processes of an organization. The framework of smart manufacturing and Industry 4.0 is based on smart process design, monitoring, control, scheduling, and industrial applications. Smart manufacturing encompasses a broad range of domains, originally referred to as IoT-based technologies.

Elena G. Panarskaya

Ekaterina G. Nikulina, Ekaterina K. Starkova, Vera G. Ryabchikova et al.

Problem statement . The modernization of higher education is a good ground for the use of electronic resources in ensuring accessibility, continuity and quality of teaching foreign languages. The use of interactive tools (simulators, flash cards, virtual whiteboards) meets the requirements to educational training programs for students of pedagogical directions and the challenges of modern society. A flash card is a card with a word, a concept, an image on one side and a translation on the other. The study aimed at substantiating the effectiveness of the use of flash cards for the formation of foreign language competence of future teachers. Methodology . Theoretical and methodological analysis and generalization were used to determine trends in the development of language education, the inclusion of informatization tools in foreign language activities and professional communication. The online platform Quizlet was chosen to work with ready-made flash cards and to create new thematic sets in digital format. The questions for the control work grouped into two blocks “Digital educational technologies” (50 points) and “Foreign language in professional communication” (50 points) were compiled. The study involved 54 students from Vyatka State University (the direction of 44.03.05 “Pedagogical education”, with two training profiles, bachelor's degree level). Pearson's chi-squared criterion was applied at the stage of statistical processing of the results. Results . The system of working with flash cards in the foreign language professional communication of future teachers is described: the study of the Quizlet functionality, working with ready-made sets of cards, automating and improving lexical units, developing their own thematic sets. In the course of independent work and network collaboration the students of the experimental group used Flashcards, Speller, Scatter, Quizlet Live modes. Statistically significant differences in the qualitative changes that occurred in the level of formation of foreign language competence were determined. Conclusion. The use of flash cards in the preparation of students of pedagogical specialties has a significant didactic potential for the development of their foreign language competence: the effect of immersion, competitiveness and obtaining positive emotions; resources for independent language learning in extracurricular time; overcoming the language barrier in the virtual gaming environment of information interaction. However, there are some drawbacks: monotony of forms for tests, lack of opportunity to practice pronunciation, partial support of operating modes in the mobile version.

Sean M. Noble, Jason D. Saville, Lori L. Foster

Abstract Post-secondary institutions are investing in and utilizing virtual reality (VR) for many educational purposes, including as a discretionary learning tool. Institutions such as vocational schools, community colleges, and universities need to understand what psychological factors drive students’ acceptance of VR for learning in discretionary contexts. The Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al. in MIS Quarterly 27:425–478, 2003) offers a theoretical framework for understanding students’ receptivity to VR for learning. Undergraduate university students (N = 300) read a description of VR and video training mediums, then indicated which they would choose to learn a novel task. Three psychological variables—performance expectancy, effort expectancy, and social influence—tended to be related to acceptance of VR, which was measured in two ways: (a) rated intentions to use VR and (b) preference for VR over a video-based alternative. Relative weight analyses compared the importance of the three predictors and revealed that performance expectancy tended to be the most influential antecedent of VR acceptance.

F. Garzon, É. Bonjour, Jean-Pierre Micaëlli et al.

Abstract The project management field has the imperative to increase the success probability of projects. Experts have developed several Project Management Maturity (PMM) models to assess project management practices and improve the project outcome. However, the current literature lacks models that allow experts to correlate the measured maturity with the expected probability of success. The present paper develops a general framework and a method to estimate the impact of PMM on project performance. It uses Bayesian networks to formalize project management experts’ knowledge and to extract knowledge from a database of past projects. An industrial case concerning large projects in the oil and gas industry is used to illustrate the application of the method to reduce the risk of project cost (or budget) overruns.

E. Rene, Jinyi Ge, Gopalakrishnan Kumar et al.

A. Singh, A. Rawani

Haibo MEI, Kun YANG, Xinyu FAN

Fog radio access network (F-RAN) is suitable for Internet of things applications of national important industries, such as pipeline network monitoring in wide area.However, the performance of the F-RAN based on the territorial fog access point will be affected greatly by the complicated territorial environment.This causes F-RAN not able to provide fog access service in a timely and effectively manner.To this problem, the research was proposed to utilize low altitude UAV as the fog access point to realize air ground edge communication and fog computing, which has attracted enormous research interests.How to use deep reinforcement learning (DRL) to improve the energy efficiency of UAV fog access point and extend the mission time of UAV were discussed.Deep reinforcement learning can ensure the UAV fog access point to adjust the configuration strategy timely of air ground communication and computing, including resource optimization, dynamic task offloading and caching.DRL can also optimize the UAV trajectory in 3-D space, and improve the overall performance of UAV enabled fog access network.The innovation of the research lies in the comprehensive discussion of the main optimization problems to be solved in the UAV-enabled F-RAN using DRL.The technical details were also summarized to solve the related optimization problems.Finally, the technical challenges and future research directions of the application of DRL in the UAV-enabled F-RAN were discussed.

Eleftherios Tzagkarakis, Haridimos Kondylakis, George Vardakis et al.

Advances in computers and communications have significantly changed almost every aspect of our daily activity. In this maze of change, governments around the world cannot remain indifferent. Public administration is evolving and taking on a new form through e-government. A large number of organizations have set up websites, establishing an online interface with the citizens and businesses with which it interacts. However, most organizations, especially the decentralized agencies of the ministries and local authorities, do not offer their information electronically despite the fact that they provide many information services that are not integrated with other e-government services. Besides, these services are mainly focused on serving citizens and businesses and less on providing services to employees. In this paper, we describe the process of developing an ontology to support the administrative procedures of decentralized government organizations. Finally, we describe the development of an e-government portal that provides employees services that are processed online, using the above ontology for modeling and data management.

F. J. Lozano, R. Lozano, Paulo Freire et al.

The special volume on green and sustainable chemistry and engineering has fourteen papers that were considered relevant to the present day issues and discussion, such as adequate use of raw materials and efficient energy, besides considering renewable sources for materials and energy; and changing economical canons towards circular economy. Businesses, governments and Society are facing a number of challenges to tread the sustainability path and provide wellbeing for future generations. This special volume relevance provides discussions and contributions to foster that desirable future. Chemicals are ubiquitous in everyday activities. Their widespread presence provides benefits to societies’ wellbeing, but can have some deleterious effects. To counteract such effect, green engineering and sustainable assessment in industrial processes have been gathering momentum in the last thirty years. Green chemistry, green engineering, eco-efficiency, and sustainability are becoming a necessity for assessing and managing products and processes in the chemical industry. This special volume presents fourteen articles related to sustainable resource and energy use (five articles), circular economy (one article), cleaner production and sustainable process assessment (five article), and innovation in chemical products (three articles). Green and sustainable chemistry, as well as sustainable chemical engineering and renewable energy sources are required to foster and consolidate a transition towards more sustainable societies. This special volume present current trends in chemistry and chemical engineering, such as sustainable resource and energy use, circular economy, cleaner production and sustainable process assessment, and innovation in chemical products. This special volume provides insights in this direction and complementing other efforts towards such transition.

Bond, Diana M, Hammond, Jeremy, Shand, Antonia W et al.

BackgroundTraditional data collection methods using paper and email are increasingly being replaced by data collection using mobile phones, although there is limited evidence evaluating the impact of mobile phone technology as part of an automated research management system on data collection and health outcomes. ObjectiveThe aim of this study is to compare a web-based mobile phone automated system (MPAS) with a more traditional delivery and data collection system combining paper and email data collection (PEDC) in a cohort of breastfeeding women. MethodsWe conducted a substudy of a randomized controlled trial in Sydney, Australia, which included women with uncomplicated term births who intended to breastfeed. Women were recruited within 72 hours of giving birth. A quasi-randomized number of women were recruited using the PEDC system, and the remainder were recruited using the MPAS. The outcomes assessed included the effectiveness of data collection, impact on study outcomes, response rate, acceptability, and cost analysis between the MPAS and PEDC methods. ResultsWomen were recruited between April 2015 and December 2016. The analysis included 555 women: 471 using the MPAS and 84 using the PEDC. There were no differences in clinical outcomes between the 2 groups. At the end of the 8-week treatment phase, the MPAS group showed an increased response rate compared with the PEDC group (56% vs 37%; P<.001), which was also seen at the 2-, 6-, and 12-month follow-ups. At the 2-month follow-up, the MPAS participants also showed an increased rate of self-reported treatment compliance (70% vs 56%; P<.001) and a higher recommendation rate for future use (95% vs 64%; P<.001) as compared with the PEDC group. The cost analysis between the 2 groups was comparable. ConclusionsMPAS is an effective and acceptable method for improving the overall management, treatment compliance, and methodological quality of clinical research to ensure the validity and reliability of findings.

C. Snider, J. Gopsill, Simon Jones et al.

Due to the situational and contextual individuality of engineering work, the in-progress monitoring and assessment of those factors that contribute to the success and performance in a given scenario poses a distinct and unresolved challenge, with heavy reliance on managerial skill and interpretation. Termed engineering project health management (EPHM), this paper presents a novel approach and framework for monitoring of engineering work through data-driven and computational analytics that in turn support the managerial interpretation and generation of higher level, context-specific understanding. EPHM is formed through the first adaptation of integrated vehicle health management (IVHM) to the field of engineering management; an approach that has been used to-date for the machine monitoring and predictive maintenance. The approach is applied to four industrial cases, which demonstrates the generation of project-specific information. The approach thereby acts to increase understanding of an engineering activity and a work state, and is complementary to existing managerial toolsets and approaches. A key tenet of the adaption of IVHM is to place the manager in a central role, supporting their professional judgment while reducing investigative effort.

Li Zhou, Chuan Zhang, I. Karimi et al.

Abstract In this paper, we develop a skeletal ontology for eco-industrial parks. A top-down conceptual framework including five operating levels (unit operations, processes, plants, industrial resource networks and eco-industrial parks) is employed to guide the design of the ontology structure. The detailed ontological representation of each level is realized through adapting and extending OntoCAPE, an ontology of the chemical engineering domain. Based on the proposed ontology, a framework for distributed information management is proposed for eco-industrial parks. As an example, this ontology is used to create a knowledge base for Jurong Island, an industrial park in Singapore. Its potential uses in supporting process modeling and optimization and facilitating industrial symbiosis are also discussed in the paper.

Xiong Li, Xiaodong Zhao, Wei Pu et al.

Abstract Industrial logistics plays a key role in industrial engineering. Since battle damage assessment and repair (BDAR) process is essentially military industrial logistics process, optimal decisions for operations management of BDAR are crucial to military industrial logistics planning. The purpose of this paper is to present a systematic procedure of optimal decisions for operations management of BDAR and form a framework of military industrial logistics data analytics. Based on war statistics from the collected historical real-world combat data, by classifying the damaged equipments into emergency group and non-emergency group, this study establishes three mathematical models on decision-making for operations management of BDAR, and presents resolutions to problems of optimized deployment, task allocation and selection of formation schemes for the resources in military industrial logistics system. Subsequently, an agent-based simulation model for military industrial logistics system is developed to demonstrate and verify the method. The results show that the method is feasible and effective.