Supporting product lifecycle collaboration and knowledge-related evaluation: an active-passive collaboration mechanism and fuzzy evaluation method

Abstract

Collaboration is essential to improve the efficiency of product research and development (R&D), shorten the R&D cycle, and reduce the R&D costs in complex product lifecycle model management (CPLMM). However, disorganized processes and the unreliability of the result evaluation remain enormous challenges for efficient collaboration. This article proposes an active-passive collaboration mechanism to enable a regulated collaboration system, which can direct the self-organized collaboration of stakeholders. C-D-Petri Net is presented for the formal collaboration process modeling. The result evaluation in active-passive collaboration involves multi-source knowledge across disciplines and phases. To address the unreliable collaboration evaluation (Co-evaluation) caused by insufficient evaluation knowledge and weak correlation between expertise and evaluation task, the collaborative fuzzy comprehensive evaluation (CFCE) model is established to support Co-evaluation actions, and its core improvement lies in the definition and introduction of collaboration volume. Finally, a simulated aircraft horizontal tail control system is regarded as an engineering application case to demonstrate and verify the effectiveness of the proposed method.

Simulation-Driven Strategies for Enhancing Water Treatment Processes in Chemical Engineering: Addressing Environmental Challenges

“…As digitalization and Industry 4.0 technologies continue to evolve, digital twins are expected to play an increasingly important role in water treatment optimization. Artificial intelligence (AI) and machine learning (ML) are poised to revolutionize simulationdriven optimization in water treatment processes by enabling autonomous learning, adaptive control, and data-driven decision-making (Cui et al, 2023). AI and ML techniques can be used to develop predictive models, identify patterns and trends in data, and optimize process performance in real-time.…”