Optimal Supply Vendor Selection Model for LNG Plant Projects Using Fuzzy-TOPSIS Theory

Abstract

Interest in clean energy has led to increased international demand for liquefied natural gas (LNG), and the development of LNG plants as megaprojects is also expected to rise. In these megaprojects, the procurement phase is crucial in terms of costs and ripple effects in subsequent phases. If unexpected problems with supply vendors arise, then redesign, reprocurement, and reconstruction are often needed. Although many studies have been conducted on vendor selection, most have focused on identifying evaluation criteria from a general perspective. Existing models are still lacking a comprehensive approach that combines both quantitative and qualitative content to extract the priority level from a pool of candidate supply vendors, particularly for LNG plant projects. Seven evaluation criteria that reflect the uniqueness of LNG plants are identified in the literature and expert interviews. The suggested model can consider multiple scales for each criterion, as well as uncertainty in experts’ opinions, using fuzzy-technique for order preference by similarity to ideal solution (TOPSIS) to select optimal vendors. The model is validated through case studies, showing that the proposed model is worthwhile to enhance the reliability of vendor selection by reflecting multiple participants and criteria, such as vendors’ technical abilities, experience, quality control, and long-term relationships.