Life cycle valuation - Designing a modular methodology for managing the costs and benefits of physical assets over their life cycle
Due to the COVID-19 crisis the PhD defence of Willem Haanstra will take place online (until further notice).
The PhD defence can be followed by a live stream.
Willem Haanstra is a PhD student in the research group Design Engineering (DE). His supervisor is prof.dr.ir. L.A.M. van Dongen from the Faculty of Engineering Technology.
Across the world, many physical public infrastructure systems are reaching the end of their useful lives and need replacing in the near future. Many Asset Management (AM) organizations are therefore faced with crucial decisions concerning the replacement of aging systems or the development of new systems to keep up with increasing demand in goods, energy, and transportation. These assets typically require significant upfront investments and require long-term commitments for the operation and maintenance over their typically decades-long lifespan.
Oftentimes, these types of strategic decisions are supported by instruments such as Life Cycle Costing (LCC). Despite the advantages of this instrument in gaining a better understanding of the costs incurred over the lifecycle, there are also several important limitations to this instrument, especially concerning the complex and multidimensional objectives and requirements of AM. LCC is primarily aimed at minimizing financial impact from a technical perspective, whereas AM is concerned with simultaneously balancing a wide selection of objectives such as reliability, safety, condition, deterioration, sustainability, and social concerns. Additionally, a whole-life cycle perspective also necessitates a multidisciplinary collaboration process to collect the required information and data, and for subsequently building life cycle models. This information, however, is often fragmented across different organizational departments or missing altogether. Lastly, approaches such as LCC tend to ignore external factors that are crucial for an asset’s long-term viability, such as changes in technology, demography, legislation, interfaces with other technical systems, and the demands of various stakeholders.
Because the philosophies of LCC and AM seem to have partially misaligned objectives, LCC may not necessarily be the right decision-support instrument for AM. As such, AM organizations are looking for ways to assess and articulate what makes a physical system valuable over its entire life cycle. The main question that guides the research of the dissertation is therefore formulated as:
“How can the life cycles of physical systems be assessed to support value-driven decision-making that benefits Asset Management organizations and their relevant stakeholders?”
In order to answer this research question, a new methodology called Life Cycle Valuation (LCV) was developed, following a Design Science Research approach. LCV is rooted in LCC but is expanded upon with concepts from Life Cycle Assessment (LCA), forming a hybrid methodology aimed at the assessment of both costs and benefits in the lifecycles of assets. The design of the LCV methodology includes a quantitative approach for the valuation of non-financial impacts, allowing them to be evaluated alongside financial impacts as well as relevant qualitative factors. Environmental impact can be included in LCV by utilizing streamlined variants of LCA that retain a high degree of validity but require fewer resources compared to comprehensive LCAs. LCV employs the four-stage framework of LCA to support the assessment and decision-making process. The main steps in this process involve determining the goal and scope, inventory analysis for the life cycle, impact assessment, and the interpretation of the results. Lastly, it includes the design of a modular tool that supports the inventory and impact assessment phases of the LCV process.
The LCV methodology is primarily demonstrated, tested, and evaluated at Liander, a distribution system operator (DSO) that is responsible for the development, operation, and maintenance of the energy grids that distribute natural gas and electricity to millions of households and businesses in the Netherlands. The decision-making context of Liander offers an interesting and emblematic research environment because its AM organization needs to deal with the complexities of managing an aging asset population while making fundamental changes in the design of existing energy systems due to the ongoing energy transition. Furthermore, Liander needs to balance multiple objectives in its decision-making such as costs, asset performance, safety, reliability, and sustainability, among other concerns.
Following a participatory research strategy, the design of the LCV methodology was used to study a broad range of AM decision-making contexts at the DSO. It was applied to develop and evaluate the design of individual asset lifecycles (e.g., transformers), entire asset populations (e.g., switchgear), complex systems of multiple assets (e.g., entire energy grids), and in developing strategies for deferring asset investments (e.g., using demand flexibility). Furthermore, the application of the designed LCV approaches also covered a wide range of life cycle stages, including early design, procurement, maintenance, operation, and end-of-life decisions such as replacement and refurbishment. Additionally, some aspects of the methodology, such as the inclusion of environmental sustainability, were also designed and tested in another decision-making context, in the form of the early design stages of train modernization at passenger railway organization Netherlands Railways.
The empirical findings indicate that the designed Life Cycle Valuation methodology can be an effective instrument to support AM decision-making by: (1) Providing a life cycle perspective for the long-term planning of individual assets and their relation to other assets and systems by setting appropriate scopes. (2) Revealing the links that exist between specific activities and opportunities in the lifecycle of assets and the costs and benefits that are relevant to the AM organization. (3) Increasing the support for investment proposals through multidisciplinary data and information inventory, and transparency about which impacts are included in the assessment and how. And (4) by facilitating the assessment process itself using a supporting framework, streamlining strategies, and the use of supporting tools.
The dissertation aims to further close the gap that currently exists between existing asset management and life cycle evaluation theories and the practice of real-world decision-making and its empirical challenges. The core design of the LCV methodology is based on well-established, empirically tested, and generalizable design principles, allowing for the method to be adapted to other organizations and asset types. Overall, the research provides a better theoretical and empirical understanding of how to evaluate strategic asset-related decisions in complex and changeable AM environments.
