Bonello A, Brown C A, Francalanza E, Gauci M V, Refalo P
Department of Industrial and Manufacturing Engineering, Faculty of Engineering, University of Malta, Msida, Malta.
Department of Mechanical & Materials Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
Prod Manuf Res. 2025 Jun 4;13(1):2508451. doi: 10.1080/21693277.2025.2508451. eCollection 2025.
Human-centred design of collaborative human-robot (HRC) workspaces is central to Industry 5.0. While proximity with collaborative robots offers productivity and flexibility gains, it also raises concerns for both physical safety and cognitive ergonomics. Although physical safety is well addressed, few studies integrate cognitive and physical well-being into workstation design. This research presents a novel approach that combines Kansei Engineering (KE) with Suh's Axiomatic Design (AD) to support physically and cognitively safe HRC workstations. Unlike existing studies that rely solely on Suh's Axiom 1 (maintain independence), this work also takes into account Axiom 2 (minimise information) to select between equally independent physical and cognitive design parameters. The approach is demonstrated through a case-study workstation, visually illustrating the relationship between functional and physical metrics. This study advances the field by providing a novel replicable, human-centred approach that unites cognitive and physical ergonomics,bridging theory and practical application for both academic and industrial contexts.
协作式人机（HRC）工作空间的以人为本设计是工业5.0的核心。虽然与协作机器人近距离接触可提高生产力和灵活性，但也引发了对人身安全和认知工效学的担忧。尽管人身安全问题已得到很好解决，但很少有研究将认知和身体福祉纳入工作站设计。本研究提出了一种将感性工学（KE）与Suh的公理设计（AD）相结合的新方法，以支持物理和认知安全的HRC工作站。与现有仅依赖Suh公理1（保持独立性）的研究不同，本研究还考虑了公理2（最小化信息），以便在同样独立的物理和认知设计参数之间进行选择。通过一个案例研究工作站展示了该方法，直观地说明了功能指标与物理指标之间的关系。本研究通过提供一种新颖的、可复制的、以人为本的方法推进了该领域的发展，该方法将认知和物理工效学结合起来，为学术和工业环境搭建了理论与实际应用之间的桥梁。
