  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.
