School of Engineering, Stephenson Building, Newcastle University, Newcastle upon Tyne, UK.
School of Computing, Urban Sciences Building, Newcastle University, Newcastle upon Tyne, UK.
Ergonomics. 2020 Aug;63(8):1027-1043. doi: 10.1080/00140139.2020.1723683. Epub 2020 Feb 24.
This article presents a position statement on using ergonomics in conjunction with the multi-modelling paradigm. Multi-modelling is a computational approach to combine models of systems and components for design and simulation of cyber physical systems and systems of systems. Despite potentially significant benefits in terms of more human-centric system modelling, there is limited evidence of the application of ergonomics within multi-modelling. This article presents the case for applying ergonomics within multi-modelling. We open with an introduction to multi-modelling and benefits, applications and gaps for ergonomics in multi-modelling, and of potentially useful models from ergonomics. We then describe a proof-of-concept implementation of ergonomics within a multi-model of UAV control. This demonstrates that as well as user-centred modelling, this approach supports ergonomics in how we can access rich systems models, and the collaborative value of applying ergonomics theory in systems design. Examines multi-modelling, a computational approach for complex modelling, and the contribution of ergonomics. An autonomous UAV test implementation demonstrates the application of ergonomics knowledge for improving design and evaluation processes, and how multi-modelling can give ergonomics access to rich systems models. ACT-R: adaptive control of thought-rational; API: application programming interface; CFD: computational fluid dynamics; COTS: commerical off the shelf; CPS: cyber-physical system; CT: continuous time; DE: discrete event; DSE: design space exploration; FME: finite element modeling; FMI: functional mock-up interface; FMU: functional mock-up unit; GOMS: goals, operators, methods, selections; HCI: human-computer interaction; IMPRINT: improved performance research integration tool; INTO-CPS: integrated toolchain for cyber-physical system modeling; KLM: keystroke level model; MPC: model-predictive control; SysML: system markup language; SoS: system of system; UAV: unmanned aerial vehicle.
本文提出了在多模型范式中结合使用人体工程学的立场声明。多模型是一种用于组合系统和组件模型的计算方法，用于设计和模拟网络物理系统和系统的系统。尽管在更以人为中心的系统建模方面具有潜在的显著优势，但在多模型中应用人体工程学的证据有限。本文提出了在多模型中应用人体工程学的理由。我们首先介绍多模型及其优势、多模型中人体工程学的应用和差距，以及人体工程学中可能有用的模型。然后，我们描述了在无人机控制的多模型中实施人体工程学的概念验证。这表明，除了以用户为中心的建模外，这种方法还支持我们如何访问丰富的系统模型的人体工程学，以及在系统设计中应用人体工程学理论的协作价值。 考察了多模型，这是一种用于复杂建模的计算方法，以及人体工程学的贡献。一个自主无人机测试实现演示了如何应用人体工程学知识来改进设计和评估过程，以及多模型如何使人体工程学能够访问丰富的系统模型。 自适应控制的思维理性；API:应用编程接口；计算流体动力学；COTS:商用现货；CPS:网络物理系统；CT:连续时间；DE:离散事件；DSE:设计空间探索；FME:有限元建模；FMI:功能模拟接口；FMU:功能模拟单元；GOMS:目标、运算符、方法、选择；人机交互；改进性能研究集成工具；网络物理系统建模综合工具链；击键级模型；模型预测控制；SysML:系统标记语言；SoS:系统的系统；无人机。
