In many industrial products, there are saturation of technical issues, so that customers satisfied with the most of technical issues. And they would like to have their own requirements within their budgets. Most of analysis of customer's satisfaction is basically from thinking of average. A thinking of average lose characteristic information of the product. We think that a hint to grasp the market needs of the next generation into that lost information is hidden. So, we need to explore design space to figure out that the results are satisfying as much requirements as possible. However, when we have more than three objective functions, it is not easy to grasp its situations. In that sense, visualization of multi-objective optimization becomes important issue. When we use DEA, we can have optimum weights for each objective function, but it is still difficult to see its relationships visually. In this paper, we propose DEA-mapping, which use Lagrange multiplier that is given by extended CCR model, and use them as key information of mapping. Actually, sum of multiplying Lagrange multiplier and each data becomes mapping to its frontier, in this study we use it as mapping to three dimensional space. As an example, we applied the proposed method to six objective function case and demonstrate the effectiveness of the method.