Cloud Manufacturing (CMfg) is a new manufacturing paradigm that can reduce costs, improve data analysis, increase efficiency and flexibility, and provide manufacturers with closer partnerships. However, most previous studies on CMfg focused on the planning and scheduling of a hypothetical CMfg system or its infrastructure. In addition, the cost effectiveness of a CMfg application has rarely been evaluated. Consequently, manufacturers are not certain about adopting specific CMfg applications. To address this issue, this research proposed a type-II fuzzy collaborative intelligence approach to assist in the selection of suitable CMfg applications in a factory. In the proposed methodology, first, an efficient approximating alpha-cut operations (exACO) method was proposed to enhance the efficiency of the derivation of the fuzzy priorities of factors, which is an innovative treatment. Subsequently, the membership function of a type-II fuzzy priority was derived from the overall and partial consensuses among decision makers using layered fuzzy intersection (LFI), which is also a novel approach. As the type-II fuzzy priority cannot be described using a type-II triangular or trapezoidal fuzzy set, a type-II fuzzy VIšekriterijumskoKOmpromisnoRangiranje (VIKOR) method based on the α-cuts of fuzzy priorities was employed to assess and compare nine CMfg applications. The experimental results revealed that “migrating legacy system to CMfg services” and “cloud-based customization environment” were the most and least preferable CMfg applications, respectively.