Abstract
A new approach for the operational monitoring for implementing the performance control of forest mechanisation chains is here proposed and discussed. The present study aims to develop a new approach of Precision Forestry. This innovative tool is developed around a GNSS device – the core of data-logging - and a specific inference engine. Thanks to the inference engine, process time, work distance, forward speed and number of working cycles in forest operations were assessed. In order to perform this assessment, the GNSS device was installed directly on the equipment to be monitored.
The study areas were set in the Autonomous Province of Bolzano (N-E of Italy). The logging system applied in the different study areas was the same, despite the different forest characteristics and the different terrain morphology. The tower yarder system – one of the most used logging systems in the alpine regions – was the machinery assessed during this study. This machinery is composed by a power unit and a carriage. The carriage is the component which carries out the harvesting operations, transporting the biomass from the felling land to the log land. The forest operations through the use of the tower yarder are composed of five working phases: outhaul empty, hook, inhaul and unhook. The study consisted of recording and elaboration of the times detected by the GNSS device at each position detections, their elaboration through the inference engine and finally their validation. Indeed, simultaneously, an integration of the GNSS information with a time study of work elements based on the continuous time methods supported by a time study board were performed. All the recorded GNSS data were integrated with the work elements study.
Thanks to this new operational monitoring approach it was possible to detect all the carriage’s movements. It was therefore possible to monitor the entire working cycles as well as each elementary working phase. As far as the entire working time is concerned, the comparison between the results obtained through automatic and manual study presented good correlation values. The absolute differences between the elemental times automatically recorded with those manually logged by the clock were below 10%.