Procedia CIRP最新文献

英文中文

Inclusive Hiring through Technology: A Recruitment Platform for Individuals with Intellectual Disabilities 通过技术实现包容性招聘：智障人士招聘平台

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.05.091

Shalini Madan , Tarun Kumar , Ajit Bhagat

The current world development has been characterised by an increase in technology as people are currently interacting at a very high pace, and this includes individuals who have neurological and intellectual disabilities, including Down’s Syndrome, Asperger, Autism Spectrum Disorder, Learning Disability and Mental Retardation. The project develops a digital job search product for individuals with ID. This study presents ‘Workability’, a digital platform designed to support individuals with intellectual disabilities (ID) in India, striving to create an inclusive environment and facilitate improved job placements and social participation. Applying User-Centered Design (UCD) principles, the research involved collaboration with ID individuals, corporate employers, and vocational training centres. The methodology encompassed a preliminary study, in-depth stakeholder interviews, and surveys, culminating in a digital interface that offers accessible, customisable features such as speech-to-text and image recognition capabilities. Feedback from a diverse participant pool of over 60 individuals in the initial phase and 25 in subsequent phases informed iterative design enhancements. Results indicate that ‘Workability’ significantly empowers ID individuals by enabling easier access to employment opportunities and fostering community integration. The project concludes that by leveraging technology to capitalise on the abilities and preferences of ID individuals, it is possible to reshape the scope of employment and social engagement for this demographic, advocating for a more inclusive society in India. The project’s core objective is to make the prevailing system more inclusive, where people with ID will not be marginalised solely based on their condition but fully integrated into societies through the provision of streamlined and specialised placement services for employment that capitalise on their abilities and preferences.

当前世界发展的特点是科技的发展，因为人们目前的互动速度非常快，这其中包括神经和智力残疾人士，包括唐氏综合症、阿斯伯格、自闭症、学习障碍和智力迟钝。该项目为智障人士开发了一款数字求职产品。本研究介绍的 "Workability "是一个数字平台，旨在为印度的智障人士提供支持，努力创造一个包容性的环境，促进改善就业安置和社会参与。研究采用用户中心设计（UCD）原则，与智障人士、企业雇主和职业培训中心合作。研究方法包括初步研究、对利益相关者的深入访谈和调查，最终形成了一个数字界面，提供了无障碍、可定制的功能，如语音转文字和图像识别功能。最初阶段有 60 多人参与，随后阶段有 25 人参与，不同参与者的反馈意见为迭代设计的改进提供了依据。结果表明，"Workability "能使智障人士更容易获得就业机会，并促进他们融入社区，从而极大地增强了他们的能力。该项目得出结论，通过利用技术来发挥智障人士的能力和偏好，有可能重塑这一人群的就业和社会参与范围，从而倡导在印度建立一个更具包容性的社会。该项目的核心目标是使现行制度更具包容性，在这种制度下，智障人士不会仅仅因为自身条件而被边缘化，而是通过提供简化和专业化的就业安置服务，充分利用他们的能力和偏好，使他们充分融入社会。

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引用次数: 0

A Human-centred Tactile Perception Device for Enhanced Learning 以人为本的触觉感知设备促进学习

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.06.005

Pooja Shenoy , Tarun Kumar

This study proposes a toy-based product that uses tactile perception to enhance memory retention and is carefully created for different learner groups. Every person falls somewhere within the spectrum of learners. As per educational psychology, there are 3 types of learner groups namely; visual, auditory, and kinesthetic learners. This concept focuses primarily on kinesthetic learning and its link to other forms of perception. According to the Cambridge dictionary, kinesthesia is ‘the ability to know where the parts of your body are and how they are moving’. Kinesthetic learning links the movement of the body with learning of different skills and acquiring knowledge. Among somatosensory sub-modalities, this product aims to incorporate tactile perceptions namely, touch and temperature into the development of the playable toy. Using different patterns, engravings, and fidget movements, this product aims to improve the field of education. TRIZ method of ideation and conceptualisation is used and a variety of different forms and functions are discussed. Primary research was conducted with 20 people to analyse the impact of certain tactile perceptions on mental cognitive processing. The study was done with several patterned discs and was then tracked using bio-monitoring and questionnaires. The results showed specific patterns to have increased cognitive functioning and awareness. Based on these results, further study was conducted with memory and skill-based tests. It was conducted while the subject used the discs. These concepts include the development of a line of various educational toys that serve as an advancement in the education industry. It aims to create further prototypes for testing. In essence, this study hopes to design and develop a product for learners of all ages to help them learn and retain knowledge faster.

本研究提出了一种以玩具为基础的产品，它利用触觉感知来增强记忆，并针对不同的学习群体精心制作。每个人都属于不同的学习者。根据教育心理学，学习者分为三种类型，即视觉学习者、听觉学习者和动觉学习者。这一概念主要侧重于动觉学习及其与其他感知形式的联系。根据《剑桥词典》，"动觉 "是 "知道身体各部分在哪里以及它们如何运动的能力"。动觉学习将身体的运动与学习不同技能和获取知识联系起来。在躯体感觉子模式中，本产品旨在将触觉感知（即触摸和温度）融入可玩玩具的开发中。利用不同的图案、雕刻和小动作，该产品旨在改进教育领域。使用了 TRIZ 的构思和概念化方法，并讨论了各种不同的形式和功能。对 20 人进行了初步研究，以分析某些触觉感知对心理认知处理的影响。研究使用了几种图案的圆盘，然后使用生物监测和问卷进行跟踪。结果表明，特定的图案会增强认知功能和认知能力。在这些结果的基础上，还进行了进一步的记忆和技能测试研究。测试是在受试者使用光盘时进行的。这些概念包括开发一系列各种教育玩具，作为教育行业的进步。其目的是创造更多的原型进行测试。从本质上讲，这项研究希望设计和开发一种适合所有年龄段学习者的产品，帮助他们更快地学习和保留知识。

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引用次数: 0

Smart railways: the design and construction of an autonomous inspection and maintenance vehicle 智能铁路：自主检查和维护车辆的设计与制造

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.03.003

Jian Li , Isidro Durazo-Cardenas , Cristobal Ruiz-Carcel , Feiyang He , Rob Anderson , Amanda Hall , David Burbridge , Andrew Starr

The Railway Inspection and Maintenance Vehicle (RIMV) is a state-of-the-art autonomous ground robot for the railway environment. The robot has specialised hardware tailored for specific functionalities, ensuring optimal performance in its designated tasks. It incorporates a GPS, IMU, and encoder for robust localisation, and it integrates a LiDAR system and a depth camera for collision avoidance. Prioritising safety, the RIMV features an IP camera for real-time environmental monitoring and is equipped with emergency stop mechanisms. An Ubuntu Linux machine manages the robot’s data processing, complemented by a 5G Wi-Fi router for remote monitoring and operation when necessary. ROS2 is the primary platform for robot operations, standing out for its open-source solution and enhanced cybersecurity features. We validated the RIMV in a heritage railway setting with an ultrasonic inspection kit to detect rail-track defects. Beyond this specific application, the RIMV is versatile and designed to serve as a platform for other autonomous inspection and maintenance tasks within the railway sector. Its adaptability highlights its potential to enhance efficiency and safety in railway maintenance, offering invaluable assistance to human operators across varied scenarios.

铁路检查和维护车（RIMV）是一种用于铁路环境的最先进的自主地面机器人。该机器人拥有为特定功能定制的专用硬件，可确保在执行指定任务时发挥最佳性能。它集成了 GPS、IMU 和编码器，可进行稳健定位，还集成了激光雷达系统和深度摄像头，可避免碰撞。为了确保安全，RIMV 配备了一个 IP 摄像机，用于实时监控环境，并配备了紧急停止机制。一台 Ubuntu Linux 机器负责管理机器人的数据处理，辅以一台 5G Wi-Fi 路由器，在必要时进行远程监控和操作。ROS2 是机器人操作的主要平台，因其开源解决方案和增强的网络安全功能而脱颖而出。我们利用超声波检测套件在传统铁路环境中对 RIMV 进行了验证，以检测轨道缺陷。除这一特定应用外，RIMV 还具有多功能性，可作为铁路部门其他自主检测和维护任务的平台。它的适应性突显了其在提高铁路维护效率和安全性方面的潜力，可在各种场景下为人类操作员提供宝贵的帮助。

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引用次数: 0

Deep Learning Approach for Enhanced Transferability and Learning Capacity in Tool Wear Estimation 深度学习方法提高刀具磨损估算的可转移性和学习能力

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.08.376

Zongshuo Li , Markus Meurer , Thomas Bergs

As an integral part of contemporary manufacturing, monitoring systems obtain valuable information during machining to oversee the condition of both the process and the machine. Recently, diverse algorithms have been employed to detect tool wear using single or multiple sources of measurements. In this study, a deep learning approach is proposed for estimating tool wear, considering cutting parameters. The model's accuracy and transferability in tool wear estimation were assessed with milling experiments conducted under varying cutting parameters. The results indicate that the proposed method outperforms conventional methods in terms of both transferability and rapid learning capabilities.

作为当代制造业不可或缺的一部分，监控系统可在加工过程中获取有价值的信息，以监督加工过程和机床的状况。最近，人们采用了多种算法，利用单个或多个测量源检测刀具磨损。本研究提出了一种深度学习方法，用于估计刀具磨损，同时考虑切削参数。通过在不同切削参数下进行的铣削实验，评估了该模型在刀具磨损估算方面的准确性和可移植性。结果表明，所提出的方法在可移植性和快速学习能力方面均优于传统方法。

引用次数: 0

A method for the predictive and automated detection of the shrink line location during the powder bed fusion of metals using a laser beam 利用激光束预测和自动检测金属粉末床熔化过程中收缩线位置的方法

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.08.240

Dominik Rauner, Daniel Wolf, Lukas Spano, Michael F. Zaeh

The powder bed fusion of metals using a laser beam enables the additive manufacturing of topology-optimized parts involving structural transitions and rapid cross-sectional changes. Both geometry features can cause shrink lines, which reduce the dimensional accuracy and the fatigue resistance of the manufactured part. To provide reduction measures, their point of origin needs to be located in advance. This work presents an algorithm capable of automatically predicting the shrink line location for arbitrary discretized geometries. The results demonstrate the reliable detection and layer-wise characterization of the shrink-line-causing geometry features. Suitable discretization parameters were derived and the dependence of the computational time on the part complexity was quantified.

使用激光束对金属进行粉末床熔融，可以快速制造出拓扑优化的零件，其中涉及结构转换和快速截面变化。这两种几何特征都会导致收缩线，从而降低制造零件的尺寸精度和抗疲劳性。为了采取减少收缩线的措施，需要提前定位收缩线的起始点。这项工作提出了一种算法，能够自动预测任意离散几何形状的收缩线位置。结果表明，该算法能可靠地检测和分层描述导致收缩线的几何特征。得出了合适的离散化参数，并量化了计算时间与零件复杂度的关系。

引用次数: 0

A Generalized Multi-Stage Deep Machine Learning Framework for Tool Wear Level Prediction in Milling Operations 用于铣削操作中刀具磨损程度预测的通用多阶段深度机器学习框架

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.08.395

Mahmoud Hassan , Ayman Mohamed , Helmi Attia

This work proposes a tool condition monitoring system based on a generalized multi-stage deep machine learning framework for real-time measurement of flank wear in milling processes. At low computational cost, a deep wavelet scattering convolution neural network framework was developed and optimized to generate low-variant features. Discriminative features were automatically selected using a neighborhood component analysis. A gaussian process regression (GPR) model was developed for feature fusion and tool wear measurement. The model was benchmarked against different machine learning algorithms. Extensive experimental validation tests demonstrated the GPR model superiority under various cutting conditions, which facilitates its implementation in industrial facilities.

本研究提出了一种基于广义多级深度机器学习框架的刀具状态监测系统，用于实时测量铣削过程中的齿面磨损。以较低的计算成本开发并优化了深度小波散射卷积神经网络框架，以生成低变异特征。利用邻域成分分析自动选择了具有区分性的特征。为特征融合和刀具磨损测量开发了高斯过程回归（GPR）模型。该模型以不同的机器学习算法为基准。广泛的实验验证测试证明了 GPR 模型在各种切削条件下的优越性，这为其在工业设备中的应用提供了便利。

引用次数: 0

Machining-Induced Distortion during Peripheral Milling of High Strength Aluminum Parts 高强度铝零件外围铣削过程中的加工诱发变形

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.08.358

Moritz M. Mayer , Michael Ott , Matthias Wimmer , Roman Hartl , Wolfram Volk , Michael F. Zaeh

In the aerospace and automotive industries aluminum sheet metal components are often produced by forming and post-machining. Due to the change in the complex stress state during manufacturing, part distortion is a major challenge. The overall objective of this work is to streamline the process chain to minimize production costs. For this, a determination of the material properties and analysis of the machining process parameters and their influence on the resulting distortion are required.

First, tensile tests of the aluminum alloy EN AW-7075-T651 were performed. Subsequently, a series of machining tests were conducted to examine the effect of the machining process on the resulting part distortion. This paper presents machining-induced part distortion depending on the variation of the process parameters for down milling operations of thick aluminum plate material. It was found that the radial depth of cut and the cutting speed have a high impact on the resulting distortion, while the feed rate has a small influence.

在航空航天和汽车行业中，铝板金属部件通常是通过成型和后加工生产出来的。由于制造过程中复杂应力状态的变化，零件变形是一大难题。这项工作的总体目标是简化工艺链，最大限度地降低生产成本。首先，对铝合金 EN AW-7075-T651 进行了拉伸试验。首先，对 EN AW-7075-T651 铝合金进行了拉伸试验，随后进行了一系列机加工试验，以检验机加工工艺对零件变形的影响。本文介绍了在对厚铝板材料进行下铣加工时，根据加工参数的变化而导致的加工变形。结果发现，径向切削深度和切削速度对产生的变形影响较大，而进给量的影响较小。

引用次数: 0

Cutting force estimation from machine learning and physics-inspired data-driven models utilizing accelerometer measurements 利用加速度计测量数据，从机器学习和物理启发数据驱动模型中估算切削力

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.08.361

Gregory W. Vogl , Yongzhi Qu , Reese Eischens , Gregory Corson , Tony Schmitz , Andrew Honeycutt , Jaydeep Karandikar , Scott Smith

Monitoring cutting forces for process control may be challenging because force measurements typically require invasive instrumentation. To remedy this situation, two new methods were recently developed to estimate cutting forces in real time based on the use of on-machine accelerometer measurements. One method uses machine learning, while another uses a physics-inspired data-driven approach, to generate a model that estimates cutting forces from on-machine accelerations. The estimated forces from both approaches were compared against cutting force data collected during various milling operations on several machine tools. The results reveal the advantages and disadvantages of each model to estimate real-time cutting forces.

由于力测量通常需要侵入式仪器，因此监测切削力以实现过程控制可能具有挑战性。为了解决这一问题，最近开发出了两种新方法，在使用机载加速度计测量的基础上实时估算切削力。其中一种方法使用机器学习，另一种方法使用物理学启发的数据驱动方法，生成一个模型，根据机载加速度估算切削力。我们将这两种方法估算出的切削力与在几种机床上进行各种铣削操作时收集到的切削力数据进行了比较。结果显示了每种模型在估算实时切削力方面的优缺点。

引用次数: 0

A Platform for Model-based Learning and Gamification in Design Education 设计教育中基于模型的学习和游戏化平台

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.06.003

Pooja Shenoy , Tarun Kumar

This study proposes a design learning platform that combines concepts from gamification, model-based learning, and educational psychology to produce a dynamic learning environment created for design students. The platform’s main feature is a gamified approach to design education. It presents students with design quests and challenges that cross a variety of design disciplines. By using a subjective and open-ended approach, this platform encourages problem-solving, and critical thinking. To improve the learning experience, the platform incorporates educational psychology. Real-time feedback mechanisms are integrated with formative assessment methodologies to give students feedback on their progress. Model-based learning tools, such as concept models, 3D design, and flowcharts are incorporated. This helps students in understanding the connections between ideas, visualising complicated design concepts, and applying their learning to real-world situations. Gamification components such as point systems and prizes help to increase motivation and engagement. The platform aims to combine Augmented reality (AR) and Virtual reality (VR) technology into the concept. Students will be able to explore design environments and develop interesting concepts. This advancement will increase the depth and interaction of the learning experience. Primary research was conducted with preliminary prototypes of the platform with students of design to recognise the initial impact of the features of the platform. This showed to improve design thinking and problem-solving abilities. Prototype concepts have been discussed to further develop the platform’s capabilities. These concepts include the development of a mobile application to facilitate skill tracking and daily design challenges to encourage innovation. In essence, this design learning platform provides a systemic approach to design education, combining various design methods and principles, educational psychology techniques, and AR and VR technology. It hopes to empower design students by providing them with the skills, information, and drive they need to flourish in the dynamic and ever-changing world of design.

本研究提出了一个设计学习平台，它结合了游戏化、基于模型的学习和教育心理学的概念，为设计专业的学生创造了一个动态的学习环境。该平台的主要特点是以游戏化的方式开展设计教育。它向学生展示了跨越各种设计学科的设计任务和挑战。通过采用主观和开放式的方法，该平台鼓励解决问题和批判性思维。为了改善学习体验，该平台结合了教育心理学。实时反馈机制与形成性评估方法相结合，为学生提供进度反馈。该平台还纳入了基于模型的学习工具，如概念模型、三维设计和流程图。这有助于学生理解想法之间的联系，将复杂的设计概念可视化，并将所学应用到实际情况中。积分系统和奖品等游戏化组件有助于提高学习动力和参与度。该平台旨在将增强现实（AR）和虚拟现实（VR）技术结合到概念中。学生将能够探索设计环境，开发有趣的概念。这一进步将增加学习体验的深度和互动性。我们与设计专业的学生一起对平台的初步原型进行了初步研究，以了解平台功能的初步影响。结果表明，该平台提高了设计思维和解决问题的能力。为进一步开发该平台的功能，对原型概念进行了讨论。这些概念包括开发一个移动应用程序，以促进技能跟踪和日常设计挑战，从而鼓励创新。从本质上讲，这个设计学习平台提供了一种系统的设计教育方法，结合了各种设计方法和原则、教育心理学技术以及 AR 和 VR 技术。它希望通过为设计专业的学生提供所需的技能、信息和动力，使他们能够在充满活力、瞬息万变的设计世界中茁壮成长。

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引用次数: 0

From connectivity via intelligence toward sustainability? Maturity of shopfloor automation technology in the manufacturing industry 从连通性到智能化，再到可持续性？制造业车间自动化技术的成熟度

Procedia CIRP

Pub Date : 2024-01-01 DOI: 10.1016/j.procir.2024.03.024

Tobias Reichenstein , Christina Stefanie Reich , Kilian Hoffmann , Jörg Franke

The manufacturing industry is experiencing a significant transformation driven by digital technologies, Industry 4.0 concepts, and the potential for sustainable practices. This research presents an overview of the manufacturing industry, focusing on the design of manufacturing systems, digital transformation, and sustainability, identifying the gap between technological advancements and their application in industrial settings. In order to examine this, a panel survey of 899 industrial participants was conducted. This analysis assesses the potential for automation and digital factory implementation alongside the dedication for sustainability in the manufacturing industry. The findings indicate that while research has advanced in these areas, practical applications in the manufacturing industry still lag behind, particularly in terms of technology readiness levels and data implementation for automation. This paper serves as a foundation for future research, providing insights into technologies ready for industrial implementation and identifying areas requiring further optimization and study. Therefore, a matrix is presented that aids in selecting or strategizing technology utilization during the design of manufacturing systems. However, this research primarily focused on technological aspects, recommending future research to explore the interplay between organizational, human related factors, and technology to design manufacturing systems successfully with respect to sustainability.

在数字技术、工业 4.0 概念和可持续实践潜力的推动下，制造业正在经历一场重大变革。本研究对制造业进行了概述，重点关注制造系统的设计、数字化转型和可持续发展，找出技术进步与其在工业环境中的应用之间的差距。为此，我们对 899 名工业参与者进行了小组调查。这项分析评估了自动化和数字化工厂实施的潜力，以及对制造业可持续发展的贡献。研究结果表明，虽然这些领域的研究取得了进展，但制造业的实际应用仍然滞后，尤其是在自动化的技术准备水平和数据实施方面。本文为今后的研究奠定了基础，深入探讨了可用于工业实施的技术，并确定了需要进一步优化和研究的领域。因此，本文提出了一个矩阵，有助于在设计制造系统时选择技术或制定技术利用战略。不过，本研究主要侧重于技术方面，建议今后的研究探索组织、与人相关的因素和技术之间的相互作用，以成功设计出具有可持续性的制造系统。

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