Manufacturing Letters最新文献

英文中文

Collaborative problem-solving in mixed reality manufacturing environments 混合现实制造环境中的协同解决问题

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-30 DOI: 10.1016/j.mfglet.2025.10.018

Israa Azzam , Khalid Bello , Farid El Breidi , Faisal Aqlan

Extended Reality (XR) technology has shown promise in enhancing manufacturing training by providing realistic simulations in safe and controlled environments. Although many XR tools focus on single-user experiences to build individual skills, collaborative training plays a role in promoting teamwork and reinforcing production outcomes. Multi-user XR systems facilitate training on collaborative tasks and support the development of teamwork and communication skills. This study explores the use of a multi-user Mixed Reality (MR) training module in manufacturing education. The proposed MR module supports a multi-user experience, allowing trainees to work collaboratively in a shared virtual environment. The goal of this research is to assess how collaboration in MR-based training affects learning, particularly regarding how quickly tasks are completed and how effectively problems are solved. The study included 103 participants who experienced the collaborative MR module to design and assemble a hydraulic bike. The shared MR setup connected multiple HoloLens 2 headsets, allowing users to interact in the same virtual workspace and complete assigned tasks. To evaluate teamwork and problem-solving abilities, a survey focusing on team dynamics and collaboration was utilized. Participants’ experiences were also assessed using the System Usability Scale (SUS) and the Simulation Task Load Index (SIM-TLX) to understand the system usability and the mental and physical effort required during the training activity.

扩展现实（XR）技术通过在安全和受控的环境中提供逼真的模拟，在加强制造培训方面显示出了希望。尽管许多XR工具侧重于单个用户体验来培养个人技能，但协作培训在促进团队合作和加强生产成果方面发挥着重要作用。多用户XR系统促进了协作任务的培训，并支持团队合作和沟通技巧的发展。本研究探讨了多用户混合现实（MR）培训模块在制造业教育中的应用。提议的MR模块支持多用户体验，允许学员在共享的虚拟环境中协同工作。本研究的目的是评估基于核磁共振的培训中的协作如何影响学习，特别是如何快速完成任务和如何有效地解决问题。这项研究包括103名参与者，他们经历了协同磁共振模块来设计和组装液压自行车。共享的MR设置连接了多个HoloLens 2头显，允许用户在同一个虚拟工作区中交互并完成分配的任务。为了评估团队合作和解决问题的能力，我们利用了一项关于团队动力和协作的调查。参与者的体验也使用系统可用性量表（SUS）和模拟任务负荷指数（SIM-TLX）进行评估，以了解系统可用性和训练活动期间所需的精神和体力努力。

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引用次数: 0

Designing an LLM-based copilot for manufacturing equipment selection 基于llm的副驾驶机制造设备选型设计

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-29 DOI: 10.1016/j.mfglet.2025.10.017

Jonas Werheid , Oleksandr Melnychuk , Hans Zhou , Meike Huber , Christoph Rippe , Dominik Joosten , Zozan Keskin , Max Wittstamm , Sathya Subramani , Benny Drescher , Amon Göppert , Anas Abdelrazeq , Robert H. Schmitt

Effective decision-making in automation equipment selection is critical for reducing ramp-up time and maintaining production quality, especially in the face of increasing product variation and market demands. However, limited expertise and resource constraints often result in inefficiencies during the ramp-up phase when new products are integrated into production lines. Existing methods often lack structured and tailored solutions to support automation engineers in reducing ramp-up time, leading to compromises in quality. This research investigates whether large-language models (LLMs), combined with Retrieval-Augmented Generation (RAG), can assist in streamlining equipment selection in ramp-up planning. We propose a factual-driven copilot integrating LLMs with structured and semi-structured knowledge retrieval for three component types (robots, feeders and vision systems), providing a guided and traceable state-machine process for decision-making in automation equipment selection. The system was demonstrated to an industrial partner, who tested it on three internal use-cases. Their feedback affirmed its capability to provide logical and actionable recommendations for automation equipment. More specifically, among 47 equipment prompts analyzed, 24 involved selecting the correct equipment while considering most requirements, and in 20 cases, all requirements were fully met.

在自动化设备选择中有效的决策对于减少爬坡时间和保持生产质量至关重要，特别是面对不断增加的产品变化和市场需求。然而，有限的专业知识和资源限制往往导致在新产品集成到生产线上的提升阶段效率低下。现有的方法通常缺乏结构化和定制的解决方案来支持自动化工程师减少启动时间，从而导致质量上的妥协。本研究探讨了大语言模型（llm）与检索增强生成（RAG）相结合是否有助于简化爬升计划中的设备选择。我们提出了一种事实驱动的副驾驶，将llm与三种组件类型（机器人、喂食器和视觉系统）的结构化和半结构化知识检索集成在一起，为自动化设备选择决策提供了一个指导和可追溯的状态机过程。该系统向一个工业合作伙伴进行了演示，后者在三个内部用例上对其进行了测试。他们的反馈肯定了其为自动化设备提供逻辑和可操作建议的能力。更具体地说，在分析的47个设备提示中，有24个涉及在考虑大多数要求的情况下选择正确的设备，有20个案例完全满足所有要求。

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引用次数: 0

Agentic AI for smart manufacturing 智能制造的人工智能代理

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-26 DOI: 10.1016/j.mfglet.2025.10.013

Jay Lee, Hanqi Su

The rise of data-rich manufacturing environments has created demand for artificial intelligence (AI) systems capable of autonomous, adaptive, and goal-oriented operations. Traditional AI methods, being largely task-specific, often lack the flexibility to perform effectively in dynamic, complex industrial settings. Recent advances in large language models (LLMs) have led to the emergence of Agentic AI, which extends AI capabilities through advanced reasoning, planning, tool integration, and multi-agent collaboration. While Agentic AI has been explored in domains such as computer science, healthcare, education, and finance, its adoption in manufacturing remains limited.

This paper defines Agentic AI in the manufacturing context, differentiates it from traditional AI agents, and presents a novel framework designed for smart manufacturing. The proposed framework integrates multiple LLM-based agents, a unified Data–Model–Knowledge (DMK) lake, and human expertise to enable advanced perception, reasoning, planning, orchestration, evaluation, optimization, and iterative improvement. A case study of a retrieval-augmented generation (RAG)-based LLM QA system demonstrates the framework’s feasibility. Key technical challenges are also discussed. The work aims to provide strategic guidance for the development and deployment of efficient, trustworthy Agentic AI systems in smart manufacturing.

数据丰富的制造环境的兴起创造了对能够自主、自适应和目标导向操作的人工智能（AI）系统的需求。传统的人工智能方法主要针对特定任务，往往缺乏灵活性，无法在动态、复杂的工业环境中有效执行。大型语言模型（llm）的最新进展导致了人工智能的出现，它通过高级推理、规划、工具集成和多智能体协作来扩展人工智能的能力。虽然人工智能已经在计算机科学、医疗保健、教育和金融等领域进行了探索，但它在制造业中的应用仍然有限。本文对制造环境下的人工智能agent进行了定义，并将其与传统的人工智能agent进行了区分，提出了一种新的智能制造框架。提出的框架集成了多个基于llm的代理、统一的数据模型知识（DMK）湖和人类专业知识，以实现高级感知、推理、规划、编排、评估、优化和迭代改进。一个基于检索增强生成（RAG）的LLM质量保证系统的实例研究证明了该框架的可行性。讨论了关键的技术挑战。这项工作旨在为智能制造中高效、可信赖的人工智能系统的开发和部署提供战略指导。

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引用次数: 0

Reflections on the implementation of Short, authentic oral assessments in a university manufacturing course 关于在大学制造课程中实施简短、真实的口头评估的思考

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-26 DOI: 10.1016/j.mfglet.2025.10.011

Sandra Huffman, Kaitlyn Becker, John Liu, Rebecca Zubajlo, Warren Seering

With AI making it increasingly easy to cheat on tests, assessment methods must be adapted. Here, we document the creation, administration, and grading of short (7-minute) authentic oral assessments, and reflect on their implementation. In these oral assessments, students were asked to demonstrate authentic engineering practices such as weighing tradeoffs, data interpretation, troubleshooting, and design-for-manufacture. The teaching team was able to establish student buy-in through class discussions, clear rubrics, and ample opportunities for practice. Instructors developed the skills required to keep the oral assessments short, built fluency in the rubric, and took steps to reduce bias. Each of these actions helped create strong, fair oral assessments. Administering the oral assessments allowed instructors to better understand their students’ strengths and needs, and build better relationships in the classroom. Despite their brevity, instructors believed the oral assessments provided a clear picture of student understanding and helped bring nuance to different capabilities. Both students and instructors had a positive experience with the oral assessments; instructors will continue using them in future semesters. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

随着人工智能使考试作弊变得越来越容易，评估方法必须进行调整。在这里，我们记录了简短（7分钟）的真实口头评估的创建、管理和评分，并反思了它们的实施。在这些口头评估中，学生被要求展示真实的工程实践，如权衡权衡、数据解释、故障排除和为制造而设计。教学团队能够通过课堂讨论、清晰的规则和充足的实践机会来建立学生的支持。教师们发展了口头评估所需的技能，使其简短、流畅，并采取措施减少偏见。每一项行动都有助于形成有力、公平的口头评估。进行口头评估可以让教师更好地了解学生的优势和需求，并在课堂上建立更好的关系。尽管口头评估很简短，但教师们认为口头评估可以清楚地了解学生的理解情况，并有助于了解不同能力的细微差别。学生和教师对口头评估都有积极的体验；讲师将在未来的学期中继续使用它们。这项研究没有从公共、商业或非营利部门的资助机构获得任何具体的资助。

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引用次数: 0

An engineering design process course for high school preservice teachers based on 3D printer component analysis 基于3D打印机部件分析的高中职前教师工程设计过程课程

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-25 DOI: 10.1016/j.mfglet.2025.10.014

Weihang Zhu , Mariam Manuel , Paige Evans , Peter Weber

3D printing (3DP) has been becoming pervasive in the K-16 education system. However, in many schools, new 3D printers arrive, work for a certain period, and before long break down due to lack of maintenance and support. Teachers must develop a deeper understanding of 3D printing to fully realize its potential in engineering design. This course responds to that need by integrating 3D printer dissection with the Engineering Design Process (EDP) and culturally responsive pedagogy (CRP). In this project, the course of engineering design for preservice teachers (PST, current undergraduate students) is developed and implemented with mechanical components from dissected 3D printers. The approach is to dissect a 3D printer’s hardware, explain each component’s function, introduce each component’s manufacturing methods, describe possible defects, and elucidate what works and what does not. This allows the PSTs to develop a better understanding of 3D printing process, have a better idea on how to fix a 3D printer when it breaks down, and design components that are compatible with 3D printing. Findings from pre- and post-course quizzes and course evaluations indicate that preservice teachers not only improved their technical knowledge of 3D printing but also gained confidence in applying EDP and CRP practices, strengthening the sustainability and meaningful use of 3D printing in classrooms.

3D打印（3DP）已经在K-16教育系统中普及。然而，在许多学校，新的3D打印机到达，工作了一段时间，不久就因缺乏维护和支持而故障。教师必须深入了解3D打印，充分发挥其在工程设计中的潜力。本课程通过将3D打印机解剖与工程设计过程（EDP）和文化响应教学法（CRP）相结合来响应这一需求。本项目利用解剖式3D打印机的机械部件，开发并实施了面向职前教师（PST，在读本科生）的工程设计课程。方法是剖析3D打印机的硬件，解释每个组件的功能，介绍每个组件的制造方法，描述可能的缺陷，并阐明哪些有效，哪些无效。这使得PSTs能够更好地理解3D打印过程，更好地了解如何在3D打印机发生故障时修复3D打印机，并设计与3D打印兼容的组件。课前和课后测验和课程评估的结果表明，职前教师不仅提高了他们对3D打印的技术知识，而且在应用EDP和CRP实践方面获得了信心，加强了3D打印在课堂上的可持续性和有意义的使用。

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引用次数: 0

Shaping tomorrow’s engineering education with sustainable design and manufacturing practices 用可持续的设计和制造实践塑造明天的工程教育

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-25 DOI: 10.1016/j.mfglet.2025.10.015

Ismail Fidan

The future of engineering education depends on equipping students with advanced design tools and sustainable manufacturing practices. This article presents three innovative, hands-on modules: 1) Generative Design using Autodesk Fusion, 2) Portable Sand Casting with “foundry-in-a-box” kits, and 3) Green Manufacturing by converting waste plastics into 3D printing filaments. Each module integrates sustainability and entrepreneurial thinking. The modules were beta tested with STEM students and educators during a summer workshop, yielding positive feedback and valuable insights for refinement. These scalable educational models address current knowledge gaps and enhance STEM education by inspiring the next generation of engineers.

工程教育的未来取决于为学生提供先进的设计工具和可持续的制造实践。本文介绍了三个创新的动手模块：1)使用Autodesk Fusion的生成设计，2)便携式砂铸造与“铸造盒”套件，以及3)通过将废塑料转化为3D打印长丝的绿色制造。每个模块都整合了可持续性和创业思维。在夏季研讨会上，STEM学生和教育工作者对这些模块进行了测试，得到了积极的反馈和有价值的见解。这些可扩展的教育模式解决了当前的知识差距，并通过激励下一代工程师来加强STEM教育。

引用次数: 0

Analysis of user experience in extended reality: a comparative study of VR and MR for manufacturing training 扩展现实中的用户体验分析：制造业培训中VR和MR的比较研究

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-24 DOI: 10.1016/j.mfglet.2025.10.003

Israa Azzam , Khalid Bello , Farid El Breidi , Faisal Aqlan

With the advancement of Industry 4.0, extended reality (XR) technologies, such as Virtual Reality (VR) and Mixed Reality (MR), have become integral tools in manufacturing training and education. These technologies proved to lower training costs by eliminating the need for physical equipment and reducing safety concerns. However, both VR and MR still face challenges related to user experience (UX), interaction quality, environmental functionality, and hardware/software limitations, which affects their overall effectiveness in training. This research examines the unique features, strengths, and limitations of VR and MR environments based on users’ experiences during manufacturing assembly tasks, aiming to select the optimal XR environment for a better user experience. A study was conducted with 95 undergraduate engineering students using interactive training modules in both VR and MR settings. The modules included sensory inputs, such as sound and visuals, to help assess UX. Quantitative and qualitative data were collected and analyzed. Statistical methods were used for the numerical data and Natural Language Processing (NLP), specifically the Latent Dirichlet Allocation (LDA) model, was used to analyze the qualitative data. The findings showed that MR was more effective than VR for manufacturing training. Participants reported that MR provided a more immersive and interactive experience, reduced discomfort, and improved safety by allowing real-time interaction with the physical environment through holograms, while still maintaining awareness of their surroundings.

随着工业4.0的发展，扩展现实（XR）技术，如虚拟现实（VR）和混合现实（MR），已成为制造业培训和教育中不可或缺的工具。事实证明，这些技术通过消除对物理设备的需求和减少安全问题，降低了培训成本。然而，VR和MR仍然面临着与用户体验（UX）、交互质量、环境功能和硬件/软件限制相关的挑战，这些都会影响它们在培训中的整体有效性。本研究基于用户在制造装配任务中的体验，考察了VR和MR环境的独特功能、优势和局限性，旨在选择最佳的XR环境以获得更好的用户体验。研究人员对95名工科本科生进行了一项研究，使用虚拟现实和磁共振环境下的互动训练模块。这些模块包括感官输入，如声音和视觉，以帮助评估用户体验。定量和定性数据的收集和分析。数值数据采用统计方法，定性数据采用自然语言处理（NLP），特别是潜狄利克雷分配（LDA）模型进行分析。研究结果表明，MR在制造培训方面比VR更有效。参与者报告说，MR提供了更身临其境的互动体验，减少了不适，并通过全息图与物理环境实时互动，同时仍然保持对周围环境的感知，从而提高了安全性。

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引用次数: 0

Design, fabrication, and performance evaluation of low cost, open-source desktop milling machine 低成本、开源桌面铣床的设计、制造和性能评估

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-22 DOI: 10.1016/j.mfglet.2025.10.016

Tyler Woodard , John Greene , Andrew Honeycutt , Tony Schmitz

This paper describes the design, fabrication, and performance evaluation of a three-axis computer-controlled desktop milling machine. To increase availability for this technology and provide education and training opportunities for the machining workforce, a primary goal for this machine is to provide a low-cost option for educators and students to access milling technology. The intent of the machine and, later, the supporting curriculum is to introduce machining and machining science to the next generation of manufacturers using a desktop format. Results are provided for the machine design and testing, including error motions, dynamics, and machining performance.

本文介绍了一台三轴计算机控制台式铣床的设计、制造和性能评价。为了提高这项技术的可用性，并为加工劳动力提供教育和培训机会，这台机器的主要目标是为教育工作者和学生提供低成本的铣削技术选择。机器的目的，后来，配套课程是介绍加工和加工科学的下一代制造商使用桌面格式。结果提供了机器的设计和测试，包括误差运动，动力学和加工性能。

引用次数: 0

Superior fatigue response of LENS-manufactured Ti-5553 alloy lens制造的Ti-5553合金具有优异的疲劳响应

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-17 DOI: 10.1016/j.mfglet.2025.10.012

Mateusz Kopec , Tomasz Durejko

In this paper, fatigue performance of Ti-5553 alloy fabricated using Laser Engineered Net Shaping (LENS) was investigated. Mechanical testing revealed high tensile strength (UTS: 1377 MPa) and good ductility (16 %). Fatigue tests under fully reversed loading expose superior endurance, with crack initiation mechanisms transitioning from surface-induced at high stresses to internal defect-assisted at lower amplitudes. Fractography exposed unmelted particles as initiation sites under moderate cyclic loads. The results establish LENS as a reliable method for manufacturing high-strength Ti-5553 components for high-performance applications.

研究了激光工程净成形（LENS）制备Ti-5553合金的疲劳性能。力学试验表明，该材料具有较高的抗拉强度（UTS: 1377 MPa）和良好的延展性（16%）。完全反向载荷下的疲劳试验显示出优异的耐久性，裂纹起裂机制从高应力下的表面诱导转变为低振幅下的内部缺陷辅助。在中等循环载荷作用下，断口形貌显示未熔化颗粒为起始点。结果表明，LENS是制造高性能高强度Ti-5553组件的可靠方法。

引用次数: 0

Improving employer engagement in manufacturing workforce development programs 提高雇主对制造业劳动力发展计划的参与度

IF 2 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2025-10-13 DOI: 10.1016/j.mfglet.2025.10.004

Zhen Zhao, John Liu

U.S. manufacturers face significant recruitment and retention challenges, compelling them to seek support from workforce development (WD) programs. Effective WD programs actively incorporate employer input in program design, development, and implementation to ensure relevance and meet the specific hiring needs of the manufacturing industry. Using a multi-method approach, this study examined manufacturers' preferences for engagement across areas in oversight, design, delivery, recruitment, and resource support. The results show that employers seek greater involvement in strategic oversight, curriculum design, and program delivery. Structured strategies for employer participation are recommended to ensure that WD programs align closely with industry needs.

美国制造商面临着重大的招聘和人才保留挑战，迫使他们寻求劳动力发展（WD）计划的支持。有效的WD计划积极地将雇主的意见纳入计划的设计、开发和实施中，以确保相关性并满足制造业的特定招聘需求。本研究采用多种方法，考察了制造商在监督、设计、交付、招聘和资源支持等方面的参与偏好。结果表明，雇主希望更多地参与战略监督、课程设计和项目交付。建议雇主参与的结构化策略，以确保WD计划与行业需求紧密结合。

引用次数: 0

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