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.