Dexterity skills or hand skills are generally not considered quantifiable unlike technical or soft skills. Dexterity skills like welding, spray painting, driving etc. are often measured by analysing the outputs – visually inspecting the weld, or doing destructive and non-destructive tests. Does it meet the various quality standards? However, a reverse mapping – what hand skills cause a good output? What mistakes cause defects? – has not been given the amount of attention it deserves. Skillveri has specialized in this in order to improve the effectiveness of skill training. 

Our R&D team performs multiple tasks for mapping dexterity digitally – starting with researching what hand actions cause what effects on the output quality, by how much, and how this can be improved. During our research phase, we take inputs from industry experts and practitioners alike. For example, an expert painter may not be able to verbally explain clearly how to paint perfectly, but he is able to show it himself. Our team considers this very crucial, and hence capture high quality super-slow-motion videos of several such experts from across the industry and also used sensors attached to their hands to constantly track their motion. Once this data is captured, using our expert data analytic algorithms, we drill them down to understand each aspect carefully as well as its effect on the output job quality. 

This helps us understand what’s ideal and what’s not in each skill/activity our simulators offer. The next step is to measure the hand movements (dexterity) dynamically of a trainee training on our simulator, so that his dexterity parameters may then be compared and contrasted with the ideal parameters that we now know. We use several methods for this, and while we still keep updating our hardware based on the latest technology, the best method we have identified so far is to use high quality precision 6-DoF sensors for motion tracking and  eXtended Reality (XR) technology to seamlessly blend the real world with the simulator training. 

And for the simulation training delivery, we use the principles of psychophysics – analysing what stimuli in the real world are used by a practitioner to control his/her hand movements in a corrective manner – and replicating them in the simulator. For example, in welding, the sense of vision and the sense of hearing are both used by the welder – judging the intensity of the spark and the sound of the welding, the welder can know if the machine settings are correct or if the speed or distance are wrong.

Skillveri simulators are hence the result of years of research and development, and we continue to better our own products every few years, thereby growing with the world of technology at a quick pace.