Industrial inspection automation in aerospace presents numerous challenges due to the dynamic, information-rich and regulated aspects of the domain. To diagnose the condition of an aircraft component, expert inspectors rely on a significant amount of procedural and tacit knowledge (know-how). As systems capabilities do not match high level human cognitive functions, the role of humans in future automated work systems will remain important. A Cyber-Physical-Social System (CPSS) is a suitable solution that envisions humans and agents in a joint activity to enhance cognitive/computational capabilities and produce better outcomes. This paper investigates how a work-centred approach can support and guide the engineering process of a CPSS with an industrial use case. We present a robust methodology that combines fieldwork inquiries and model-based engineering to elicit and formalize rich mental models into exploitable design patterns. Our results exhibit how inspectors process and apply knowledge to diagnose the component`s condition, how they deal with the institution`s rules and operational constraints (norms, safety policies, standard operating procedures). We suggest how these patterns can be incorporated in software modules or can conceptualize Human-Agent Teaming requirements. We argue that this framework can corroborate the right fit between a system`s technical and ecological validity (system fit with operating context) that enhances data reliability, productivity-related factors and system acceptance by end-users.
翻译:由于航空领域的动态、信息丰富和规范化,航空工业检查自动化带来了诸多挑战。为了分析航空部分的状况,专家检查员依靠大量的程序和隐性知识(诀窍)。由于系统能力与人的高度认知功能不匹配,人类在未来自动化工作系统中的作用仍然很重要。网络物理社会系统(CPSS)是一个适当的解决方案,它设想人和代理人在一项联合活动中增强认知/观察能力并产生更好的结果。本文探讨了以工作为中心的方法如何能够支持和指导以工业用途为例的CPSS的工程进程。我们提出了一种强有力的方法,将实地工作调查和基于模型的工程结合起来,以探索和正式确定丰富的精神模型,将其纳入可开发的设计模式。我们的成果展示了检查员如何处理和运用知识来诊断部件的状况,他们如何与机构的规则和业务制约(规范、安全政策、标准作业程序)打交道。我们建议如何将这些模式纳入软件模块,或如何将人类-用户团队要求概念化。我们提出一种强有力的方法,将实地调查和基于模型的工程设计方法结合起来,以吸引和正式确定丰富的精神模型,将其纳入可开发的设计模式。我们认为,检查员如何将知识运用于与机构的规则和业务制约(规范、安全政策、标准、标准)可以使生态系统的可靠性与最终用户更适合。我们认为,使与生态系统的可靠性框架能够改进。