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Predictive maintenance (PdM) has attracted increasing attention in recent years owing to the emergence of advanced condition-monitoring technologies and data analytics tools. However, the application of PdM in spare parts inventory management across the supply chain (SC) has not been sufficiently investigated and its digital transformation (DT) requirements have not been adequately researched. Therefore, this study aims to analyse the organisational readiness for the use of integrated spare parts inventory management together with PdM systems across the SC.

A series of semi-structured interviews were designed and took place across organisations in various industries to address the pre-defined research aim. In total, 15 interviewees were recruited through purposive sampling, including managers and technicians in various organisations from different industries.

The findings reveal that while maintenance planning and optimisation has been the subject of extensive research for decades, manufacturers are still encountering barriers in adopting and implementing digital innovations. The experts also highlighted the need for an integrated information system (IS) enabling data sharing across the organisation since lack of integration has a vital impact on the overall business and operations performance as well as the successful DT of the enterprise. In addition, they report that the necessary and relevant data for implementing PdM is not captured or stored in their organisations.

The present study emphasises the technical, organisational, and environmental (TOE) dimensions that can affect such DT and sheds light on the enablers and inhibitors that organisations face in their efforts to be technologically ready to embrace the digital integration of PdM with spare part inventory management. It is recommended that a clear shift in management mindset and organisational culture is necessary for companies to realise the benefits of PdM and the DT that will result from its implementation.

This study aims to assess the feasibility and effectiveness of incorporating predictive maintenance (PdM) into existing practices of spare part inventory management and pinpoint the barriers and identify economic values for such integration within the supply chain (SC).

A two-staged embedded multiple case study with multi-method data collection and a combined discrete/continuous simulation were conducted to diagnose obstacles and recommend a potential solution.

Several major organisational, infrastructure and cultural obstacles were revealed, and an optimum scenario for the integration of spare part inventory management with PdM was recommended.

The proposed solution can significantly decrease the inventory and SC costs as well as machinery downtimes through minimising unplanned maintenance and addressing shortage of spare parts.

This is the first study with the best of our knowledge that offers further insights for practitioners in the Industry 4.0 (I4.0) era looking into embarking on digital integration of PdM and spare part inventory management as an efficient and resilient SC practice for the automotive sector by providing empirical evidence.