# Evaluating 3D Printers Using Data Envelopment Analysis
## 5 Conclusions  
In the present study, DEA is proposed as a method of evaluating the technical efficiency of 3D printers. In order to identify the most suitable DEA approach for the specific task, both CCR and BCC input-oriented models of DEA are employed for assessing the efficiency of a sample of 38 3D printers, which are based on FDM/FFF technology and priced at less than USD 5000. The specific sample comprised mostly of systems randomly selected from a wide list of currently available systems, plus a small number of systems that received top ratings and reviews from 3D printing experts. The initial DEA evaluation model involved the assessment of price as the sole input parameter and of eleven 3D printer characteristics/specifications as output parameters. Employing correlation analysis and successive DEA evaluations for different combinations of outputs, their number was reduced to eight, namely, building volume, number of extruders, layer thickness, the presence of a heated bed, number of materials, printing speed, open-source character, and weight. According to the results of the analysis, CCR DEA seems to be the most appropriate model for the specific problem. Employing CCR DEA, only three out of nine top-rated 3D printers achieved maximum efficiency, while another two exhibited efficiency scores greater than 0.9. The remaining four top-rated 3D printers were evaluated with efficiency scores lower than 0.5. To further investigate the efficiency, context-dependent DEA has been applied. According to the results of context-dependent DEA, five of the top-rated printers were assigned in the top-two efficient frontiers--a result that confirmed previous evaluations and rankings--while four were evaluated as relatively attractive in lower context levels. A possible interpretation of the result is that printers in the top-two levels are good all-around alternatives that combine good technical features with low price, while the remaining four are more attractive at specific contexts, where several other factors such as brand name, user base, and customer support are also considered. An examination of the price-efficiency relationship  
Figure 2: Ranking of the inefficient printers in levels by the original DEA. for the specific sample showed that there is a significant reciprocal relationship between the two values. Regarding the applicability of the DEA method for the problem at hand, it could be argued that the results of the study show that DEA can be a useful approach for a preliminary assessment of the technical efficiency of 3D printers, based on data which are readily and easily available from the world-wide-web and without the need for subjective judgments regarding their values or relative importance. Relying on online sources of data may be considered a weakness of the proposed approach, but we believe that data reliability can be assured with a careful selection of the employed online sources. Considering the relatively large number of 3D printers offered world-wide and the rapidly changing landscape of the corresponding market, DEA may be employed for identifying a relatively small set of efficient systems out of an initial high number of possible alternatives, in relatively short time. This way 3D printer manufacturers may evaluate in short time the strengths and weaknesses of their products, compared to those offered by the competition, and adjust their product development and marketing strategies. Potential buyers could, also, consider the identified set of efficient units as a list of candidates for further evaluation where other quite important factors such as production quality and repeatability, system robustness, ease-of-use, and quality of after-sales service are assessed. The evaluation of all these factors requires extensive study and testing, and their importance to the buyer is of a more-or-less subjective nature.