Digital transformation increases the complexity of industrial product design by amplifying information flows, interdependence and coordination requirements between multidisciplinary engineering teams. In this context, knowledge management (KM) represents a critical organizational capability for capturing technical expertise, structuring information and ensuring efficient collaboration throughout the entire product lifecycle. This paper examines KM in the design of complex industrial products, with a particular focus on Product Lifecycle Management (PLM) systems and organizational conditions that influence knowledge reuse and decision consistency. An exploratory study combines a focused literature review with industrial evidence collected via semi-structured interviews (12 experts in design, validation, quality and PLM administration) and a survey of 48 practitioners from automotive and discrete manufacturing functions. The collected qualitative and quantitative data were synthesized using the Ishikawa cause–effect diagram to systematically identify and classify the root causes of inefficiencies related to knowledge flows in industrial product design. The results highlight that information fragmentation across teams, insufficient codification of tacit expertise and persistent communication barriers are the main factors limiting performance, leading to duplicated work, delays and decision-making inconsistencies. When supported by standardized capture routines and continuous training, PLM improves transparency, traceability and error reduction. The paper proposes an integrated improvement approach combining PLM-linked collaboration, formalized knowledge capture at project gates, and leadership-supported cultural change.
BALAȘ et al. (Wed,) studied this question.
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