Article

Integrating spare part inventory management and predictive maintenance as a digital supply chain solution

Details

Citation

Shokri A, Toliyat SMH, Hu S & Skoumpopoulou D (2024) Integrating spare part inventory management and predictive maintenance as a digital supply chain solution. Journal of Modelling in Management. https://doi.org/10.1108/JM2-05-2024-0131

Abstract
Purpose-The present 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). Design/methodology/approach-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. Findings-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. Practical implications-The proposed solution can significantly decrease the inventory and SC costs as well as machinery downtimes through minimising unplanned maintenance and address shortage of spare parts. Originality-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.

Keywords
Inventory Management; Supply Chain Management; simulation; Procurement; Artificial Intelligence; Predictive Maintenance

Notes
Deposit licences Emerald allows authors to deposit their AAM under the Creative Commons Attribution Non-commercial International Licence 4.0 (CC BY-NC 4.0). To do this, the deposit must clearly state that the AAM is deposited under this licence and that any reuse is allowed in accordance with the terms outlined by the licence. To reuse the AAM for commercial purposes, permission should be sought by contacting permissions@emerald.com.

Journal
Journal of Modelling in Management

StatusEarly Online
FundersInnovate UK
Publication date online31/10/2024
Date accepted by journal24/09/2024
URLhttp://hdl.handle.net/1893/36536
ISSN1746-5664

People (1)

Dr Seyed Toliyat

Dr Seyed Toliyat

Lect in Business Analytics & Technology, Management, Work and Organisation

Files (1)