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Research report | Condition Based Maintenance Technology Impacts Study


This study considered the implications of adopting Condition Based Maintenance (CBM) within the military Land domain. A ‘CBM technology impacts map’ was developed, capturing the inputs required to generate a CBM-based capability, the expected effects resulting from that capability, and their causal relationships. The map was developed through reviewing the literature, internal DSTO workshops and two rounds of Delphi-based surveys of subject matter experts (SMEs). This map and associated material were then analysed using a triangulation approach to identify the key inputs, effects and issues relating to developing and implementing a CBM-based maintenance capability. Further, the analysis elicited the costs and benefits associated with adopting CBM in the military Land domain, and highlighted key areas of risk and opportunity.

Executive Summary

Condition-Based Maintenance (CBM) refers to preventive maintenance that is performed based on need, commonly identified by sensors built into equipment or platforms. It is used extensively in commercial and military aircraft and in some commercial vehicles. This study considered the implications for using CBM in the military Land domain, including the technology itself and the associated processes and policies. The study sought to clarify CBM costs and benefits, identify critical issues for implementation and highlight key areas of both risk and opportunity.

The study used a customised conceptual model of technology impacts that examined both the inputs required to generate a CBM-based capability and the expected effects. This conceptual model encompasses causal relationships between the various impacts, with consideration of key stakeholders and relevant contextual factors.

The study method involved constructing a preliminary ‘CBM technology impacts map’ based on a literature survey and internal DSTO workshops, and refined through two rounds of Delphi-based surveys of subject matter experts (SMEs). A triangulation approach was used in data analysis to identify the most significant issues by considering: strength of evidence; graph analysis of the constructed impacts map; and prioritisation of impacts by the SMEs. The data was further analysed to provide a Fundamental Inputs to Capability (FIC) perspective, identify economic implications and highlight areas of risk and uncertainty. The validity of results was examined in the context of the study method, SME demographics, uncertainties associated with future states, and underlying assumptions.

The study results indicate that developing CBM as a capability needs to involve leadership at both high and local levels. Historical analysis of equipment/platform failures and incidents should also be used to inform CBM requirements. It is these refined requirements that need to be incorporated into the capability acquisition processes for the relevant equipment and platforms. Other significant capability inputs include:

  • Developing new supply and maintenance processes with consideration of systems engineering practices
  • Acquiring CBM hardware and software
  • Training and certifying personnel
  • Establishing data management strategies for data transmission, analysis and use in decision-support
  • Developing prognostic and diagnostic algorithms
  • Integrating CBM hardware and software with equipment/platforms as well as with Defence Information and Communication Technology (ICT) infrastructure.

The identified benefits of CBM stem from its immediate functions of diagnosing, prognosing and automatically generating real-time equipment health and usage information. This would improve detection of faults and provide a greater awareness of equipment and platform condition, both for individual units and at the fleet level. Furthermore, CBM-generated data is expected to facilitate maintenance planning at local and fleet levels, improve overall operation and maintenance of the fleet and result in a longer and more predictable equipment life.

At the operational level, CBM is expected to reduce catastrophic failure rates for equipment and platforms and increase their operational availability and operator safety. The data generated by CBM can be used for decision support across a range of functions, including mission assignment of equipment and platforms with the flow on contribution to the overall mission effectiveness of the force. There is a divergence of opinions regarding the expected effects of CBM on the overall maintenance burden and on the inventory levels at supply chain nodes. However, agreement exists on establishment of more efficient and responsive supply processes for spare parts.

A FIC-based perspective of all expected impacts with prioritisation is provided as part of the post-activity data analysis for this study. Further data analysis draws out the key economic considerations for implementation of this capability. In particular, a summary is provided for recurring and non-recurring acquisition costs, as well as costs relating to administrative functions, training, research and development, support, fleet maintenance, data management and associated logistic functions. The financial savings expected from CBM implementation are based on efficiencies to be gained through improved maintenance planning, a more responsive supply chain, optimised asset utilisation, and associated reduction in use of resources such as fuel. In the longer term, this capability has the potential to reduce overall fleet costs for maintenance, upgrades and replacement. CBM-generated data use in decision support may result in efficiencies in fleet management and future capability acquisitions. At the same time, CBM would help reduce costs associated with equipment and platform failures. In addition to the potential economic benefits of CBM, significant nonquantifiable benefits would include operator safety, confidence and morale effects, and the various contributions to the overall mission effectiveness.

This CBM impacts study identified two potential areas of risk. The first is that these expected benefits are dependent on the successful implementation by the organisation and effective use by the operators. Consequently, any human or organisational factors that affect implementation (such as lack of leadership ‘buy-in’, failure to effectively manage change, or resistance to uptake) can have flow-on effects on the quality of CBM-generated information and other expected benefits. The second area of risk lies in the data management aspects and the requirement to manage an increase in data transmission and analysis requirements, while ensuring data security and addressing data ownership issues.

Thus the study results should be viewed in the context of the uncertainty associated with all future technology assessments and with recognition of the significant judgement-based component inherent therein. Recognising these limitations, this study was designed to explore CBM impacts in a consistent, iterative and logical manner involving multiple validation activities, a diverse range of SMEs and a critical approach to examination of results. While the study does not claim to make exact predictions, the findings can be used to clarify the cost-benefit picture for CBM, identify critical issues in implementation and highlight areas of risk.

Recommendations for further work in the assessment of a CBM capability for the Land domain include:

  • Historical analysis of equipment failure points that can be addressed by CBM in support of development of capability options
  • Quantitative economic modelling in support of establishment of a business case
  • Modelling of required changes to maintenance and supply processes
  • Establishing a detailed data-management strategy.

Key information


Ksenia Ivanova, Guy Edward Gallasch, Sreeja Rajesh and Christopher Manning

Publication number


Publication type

Research report

Publish Date

April 2015


Unclassified - public release