Abstract

With the fast development of service economy, researches and applications of Industrial Product–Service Systems have become popular. Advantages and benefits of Industrial Product–Service Systems are widely discussed, while risks and uncertainties resulting from this transformation tide are rarely investigated. There are strong appeals from the industry for a holistic Industrial Product–Service Systems risk management architecture. Based on a full review on the existing work, an Industrial Product–Service Systems risk management framework integrating multiple methods is proposed trying to provide a possible solution. Structure–process correlation analysis is used for Industrial Product–Service Systems modeling. Risk recognition matrix and graphic risk units integrating with dynamic Bayesian network are developed for risk recognition and modeling. Entropy reduction value–based and effect chains’ visualized analysis offer an efficient approach for key risk and key node recognition. The proposed methods get tested and verified with a case study of risk management for hydraulic system maintenance service in excavator Industrial Product–Service Systems.

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