Abstract <p>Robot selection is one of the typical multi-criteria decision making (MCDM) problems. Many MCDM methods with linguistic evaluation terms have been used to solve robot selection problem. This paper proposed a new simple and straightforward MCDM method with linguistic evaluation data given by multiple decision-makers (DMs) based on final overall evaluation grade index. It consists of two major steps: (1) determining overall evaluation grade indices (OGIs) and overall evaluation grades (OGs) of the alternatives by each DM based on importance-weighted grade-membership degree, and (2) determining final OGIs, final OGs, and final ranks of the alternatives based on preference-weighted mean operation by integrating the OGIs from each DM. To illustrate its effectiveness, it was applied to evaluate and rank eight alternative industrial robots in consideration of 7 criteria. The final ranking determined using the proposed method was compared with the rankings determined using some previous works. The results demonstrated that the final ranking using the proposed method were pretty coincided with the rankings from the other previous works, and the proposed method had the highest mean correlation coefficient and lowest mean rank deviation from among the compared MCDM methods. It is not only simple, easy to understand and implement but also accurate and reasonable in the result. It could be easily and widely applied to many group linguistic MCDM problems with linguistic evaluation terms arising in the advanced industrial manufacturing technologies.</p>