A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

Strategy management through quantitative modelling of performance measurement systems

This paper is based on previous works on performance measurement and on quantification of relationships between factors which affect performance. It demonstrates how tools and techniques developed can be used to evaluate the performance of alternative strategic choices through a quantitative approach to modelling of performance measurement systems. The paper provides a brief background to the research problem and preceding works. The tools and techniques used are briefly introduced. Use of these tools and techniques to evaluate the performance of alternative manufacturing strategies is demonstrated. Finally, the capability of the approach to deal with dynamic environments is demonstrated using sensitivity analysis

A metric for collaborative networks

The objective of this paper is to provide a metric that could be used to define success in acollaborative network. Design/methodology/approach - The methodology of this research consists of four stages: Review, Constructing, Testing and Description. Review stage comprised of a critical review of theliterature in order to understand the characteristics of collaborative network organisations and thereasons behind the successes and failures in collaborative networks. Construction stage resulted indevelopment of a metric for collaborative networks. Testing stage tested the model through case studyin a collaborative networks organisation. The outcome of the case study was discussed at thedescription stage to assess usability and usefulness of the metric for participants in turn to generatec onclusions

A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the

Logistics outsourcing and 3PL selection: A Case study in an automotive supply chain

Outsourcing logistics functions to third-party logistics (3PL) providers has been a source of competitive advantage for most companies. Companies cite greater flexibility, operational efficiency, improved customer service levels, and a better focus on their core businesses as part of the advantages of engaging the services of 3PL providers. There are few complete and structured methodologies for selecting a 3PL provider. This paper discusses how one such methodology, namely the Analytic Hierarchy Process (AHP), is used in an automotive supply chain for export parts to redesign the logistics operations and to select a global logistics service provider

Decision support for information systems management : applying analytic hierarchy process

Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision making. AHP can be applied if the decision problem includes multiple objectives, conflicting criteria, incommensurable units, and aims at selecting an alternative from a known set of alternatives. An AHP analysis is described by using the project selection decision as an example. The strengths and weaknesses of AHP are investigated based on a set of eight criteria for evaluating I/S decision support methods. This evaluation shows that AHP scores well on most criteria. Given this promising performance, other possible applications of AHP within the I/S function are listed.