This project aims to build an LCC-based decision support system.

This system is based on an innovative theoretical framework for life cycle costing which utilises the inherent capabilities of the fuzzy set theory, probability theory, and statistics to overcome various difficulties associated of different tasks of LCC.

Within this project, three novel models and algorithms have been launched in a series of research papers. The first model and algorithm aims to carry out life cycle costing analyses in the absence of ‘hard historic data’ which is one of the major obstacles facing the implementation of LCC in the industry. The second model and algorithm as developed to facilitate the effective choice between competing alternatives of different lives; on the basis of subjective judgements elicited from experts. The third model allows a flexible description of input data, analyses it systematically and provides the decision-maker with a better impression of the validity and the usability of these uncertain information and data.

Two other models and algorithms are being developed to integrate subjective, statistically-significant, and non-monetary data in LCC studies. The ultimate objective is to integrate all these models in a user-friendly Decision support system. 

Implementing Whole Life Costing in the Oil and Gas industries

This project investigates the feasibility of integrating an LCC model into the Shell UK Exploration’s SAP (Systems, Applications, and Products in Data Processing) system. The LCC model is being developed after an investigation of the data being held on the SAP system.