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Automated production systems are critical enablers for Industry 4.0 because these design-to-order, custom-built mechatronic systems are not only capable of delivering automation capabilities to satisfy the stakeholder requirements in the manufacturing/production domain, but doing so for a long period of time (e.g., several decades) during which numerous changing needs shall also be accounted for. Although traceability has long been recognized as key to sustain changes, little is known about how the traceability information is managed in place, i.e., in the native environments where the engineering artifacts reside. We contribute in this paper a survey of traceability support within state-of-the-practice tools: seven for programming logic controllers and six for building models in systems modeling language. We draw the similarities and differences from our survey results, and further present a design by leveraging the in-place traceability to better support the development and evolution of automated production systems.
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Wang et al. (2018) studied this question.
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