A cost estimate maturity benchmark method to support early concept design decision-making: a case study application to the small modular nuclear reactor
thesisposted on 04.03.2020 by Amritpal Agar
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
Constructing large Nuclear Power Plants (NPPs) is synonymous with significant cost and schedule uncertainty. Innovative Small Modular Reactors (SMRs) have been identified as a way of increasing certainty of delivery, whilst also maintaining a competitive Life Cycle Cost (LCC). Previous research into the cost of SMRs has focused on the economics of a design from the perspective of an owner or investor. There is a significant gap in the literature associated with cost estimating SMRs at the early concept development stage from the perspective of a reactor developer.
Early design stage cost estimates are inherently uncertain. Design teams, therefore, need to make decisions that will achieve a cost competitive product by considering uncertainty. Existing cost uncertainty analysis methods lack standardisation in their application, often relying on the subjective assessment of experts. The central argument presented in this research is that the SMR vendor can make more effective decisions related to achieving cost certainty by understanding the drivers of knowledge uncertainty associated with early design stage cost estimates.
This thesis describes research spanning the concept design phase of the UK SMR development programme. The research investigation is divided into two distinct phases. The first phase identifies the requirements for cost information from the perspective of the SMR vendor through interviews, a participatory case study investigation and surveys. Limited access to cost information means that early design cost assessment is highly subjective. Cost uncertainty analysis should provide decision makers with an understanding of the level of confidence associated with the estimate. A survey investigating how cost information is interpreted revealed that providing more granular detail about cost uncertainty would support the design team with additional rationale for selecting a design option. The main requirement identified from phase 1 of the research is the need for a standardised method to identify how sources of cost uncertainty influence the maturity of the estimate at each stage of the design development process. The second phase of the research involved a participatory research approach where the Acceptable Cost Uncertainty Benchmark Assessment (ACUBA) method was developed and then implemented retrospectively on the case study cost data. The ACUBA method uses a qualitative measure to assess the quality and impact of engineering definition, manufacturing process knowledge and supply chain knowledge on the cost estimate confidence. The maturity rating is then assessed against a benchmark to determine the acceptability of the estimate uncertainty range. Focus groups were carried out in the vendor organisation to investigate whether the design team could clarify their reasoning for decisions related to reducing cost uncertainty when given insight into the sources of cost uncertainty. The rationale for a decision is found to be clearer using the ACUBA method compared with existing cost uncertainty analysis methods used by the case study organisation.
This research has led to the development of a novel method which standardises and improves the communication of cost information across different functions within a design team. By establishing a benchmark acceptable level of cost maturity for a decision, the cost maturity metric can be employed to measure the performance of the SMR development programme towards achieving product cost maturity. In addition, the ACUBA method supports the more effective allocation of limited resources available at the early design stage, by identifying design activities which could lead to an acceptable cost maturity.
EPSRC Award Reference 1533156
- Mechanical, Electrical and Manufacturing Engineering