The Industrial Robot Evolution in the World. A First Dendrogram for a Cluster Analysis

Abstract

Adoption of high tech robot systems help economies and companies to be more competitive. We have analyzed the evolution of 71 countries, calculating the robot density (robots for each 10,000 people of active population). We have used a clustering algorithm using the dissimilarity measure which takes into consideration both the proximity of the values and the behavior of the series (temporal correlation). Our preliminary findings show that there exist four different clusters, based on their robot densification evolution over the years. These clusters, composed of countries with a similar evolution over time, have also similar competitiveness levels.

Adoption of high tech robot systems help economies and companies to be more competitive. We have analyzed the evolution of 71 countries, calculating the robot density (robots for each 10,000 people of active population). We have used a clustering algorithm using the dissimilarity measure which takes into consideration both the proximity of the values and the behavior of the series (temporal correlation). Our preliminary findings show that there exist four different clusters, based on their robot densification evolution over the years. These clusters, composed of countries with a similar evolution over time, have also similar competitiveness levels.