Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework

Abstract

Popularizing green distribution transformers is a viable way to reduce power loss and environmental pollution and improve energy conversion and transmission efficiency, which has become the trend of power equipment manufacturing and market demand. However, due to conflicting multi-criteria and goals and factors, higher standards are required for green distribution transformer manufacturing. High standard manufacturing makes many manufacturers shoddy the internal components of green distribution transformers, resulting in disorderly competition in the market, which poses great challenges to the users' choice of transformers and the government's quality supervision. This paper proposes a cloud-based q-rung orthopair fuzzy multi-criteria framework for assessing the green distribution transformer manufacturing process from the perspective of conflicting relationships between criteria. It is applied to rank order four green transformer manufacturers in China based on the twelve mono-criteria under four categories of resource and energy utilization, production process and equipment, environmental coordination, green technology innovation, and their overall performance ranking results. Our analysis revealed that resource and energy utilization and green technology innovation is the motivating factors to improve the quality of green distribution transformer manufacturing and expert recognition, and the production process and equipment and environmental coordination are the inducing factors that reduce the quality of green distribution transformer manufacturing and the recognition of experts. These findings provide the demanders and government quality inspection departments with guidelines on the selection and evaluation of green distribution transformers, also identify the direction for the manufacturers to improve the technology and optimize the production of green distribution transformers.