TY - GEN
T1 - Spare Parts Supply Capabilities and Equipment Coverage
T2 - 10<sup>th</sup> Changeable, Agile, Reconfigurable and Virtual Production Conference
AU - Didriksen, Simon Klarskov
AU - Sigsgaard, Kristoffer Wernblad
AU - Jespersen, Christian Brunbjerg
AU - Mortensen, Niels Henrik
N1 - Publisher Copyright:
© The Author(s) 2026.
PY - 2026
Y1 - 2026
N2 - Recent disruptions to the global supply chain have increased maintenance organizations’ focus on spare parts supply resilience and securing the continuous supply of critical spare parts for their production plants. Studies have identified several characteristics of spare parts that challenge planning for spare parts availability. Studies also indicate an industry need to reduce the technical expertise required to implement theoretical models for the management and alignment of spare parts supply capabilities and equipment coverage. To address these challenges, this study proposes a systematic, data-driven portfolio assessment approach to conducting risk-based assessments of spare parts supply capabilities and spare parts coverage of the maintainable asset. The approach is tested in a case study on a scope of 15,427 spare parts in a major offshore oil and gas company. The case study demonstrates enhanced decision-making due to the improved, risk-based overview. The approach also requires low modelling competencies and can be modelled in business intelligence software utilizing existing computerized maintenance management system data. Practitioners can use existing data to assess current spare parts coverage and strategically adjust supply chain capabilities to reach the desired portfolio coverage.
AB - Recent disruptions to the global supply chain have increased maintenance organizations’ focus on spare parts supply resilience and securing the continuous supply of critical spare parts for their production plants. Studies have identified several characteristics of spare parts that challenge planning for spare parts availability. Studies also indicate an industry need to reduce the technical expertise required to implement theoretical models for the management and alignment of spare parts supply capabilities and equipment coverage. To address these challenges, this study proposes a systematic, data-driven portfolio assessment approach to conducting risk-based assessments of spare parts supply capabilities and spare parts coverage of the maintainable asset. The approach is tested in a case study on a scope of 15,427 spare parts in a major offshore oil and gas company. The case study demonstrates enhanced decision-making due to the improved, risk-based overview. The approach also requires low modelling competencies and can be modelled in business intelligence software utilizing existing computerized maintenance management system data. Practitioners can use existing data to assess current spare parts coverage and strategically adjust supply chain capabilities to reach the desired portfolio coverage.
KW - Data-driven approach
KW - Maintenance
KW - Portfolio assessment
KW - Spare part management
KW - Supply chain resilience
U2 - 10.1007/978-3-032-16889-4_36
DO - 10.1007/978-3-032-16889-4_36
M3 - Article in proceedings
AN - SCOPUS:105040770473
SN - 978-3-032-16888-7
T3 - Lecture Notes in Mechanical Engineering
SP - 383
EP - 392
BT - New Paradigms for Anticipated Uncertainty, Lecture Notes in Mechanical Engineering,
A2 - Manns, Martin
PB - Springer
Y2 - 9 September 2025 through 12 September 2025
ER -