GNSS-based operational monitoring devices for forest logging operation chains

The first results of a new approach for implementing operational monitoring tool to control the performance of forest mechanisation chains are proposed and discussed. The solution is based on Global Navigation Satellite System (GNSS) tools that are the core of a datalogging system that, in combination with a specific inference-engine, is able to analyse process times, work distances, forward speeds, vehicle tracking and number of working cycles in forest operations. As a consequence the operational monitoring control methods could provide an evaluation of the efficiency of the investigated forest operations. The study has monitored the performance of a tower yarder with crane and processor-head, during logging operations. The field surveys consisted on the installation of the GNSS device directly on the forest equipment for monitoring its movements. Simultaneously the field survey considered the integration of the GNSS information with a time study of work elements based on the continuous time methods supported by a time study board. Additionally, where possible, the onboard computer of the forest machine was also used in order to obtain additional information to be integrated to the GNSS data and the time study. All the recorded GNSS data integrated with the work elements study were thus post-processed through GIS analysis. The preliminary overview about the application of this approach on harvesting operations has permitted to assess a good feasibility of the use of GNSS in the relief of operative times in high mechanised forest chains. Results showed an easy and complete identification of the different operative cycles and elementary operations phases, with a maximum difference between the two methodologies of 10.32%. The use of GNSS installed on forest equipment, integrated with the inferenceengine and also with an interface for data communication or data storage, will permit an automatic or semi-automatic operational monitoring, improving the quantity of data and reducing the engagement of the surveyor.

[1]  Tim McDonald Time Study of Harvesting Equipment Using GPS-Derived Positional Data , 1999 .

[2]  John Sessions,et al.  Evaluating Global Positioning System Accuracy for Forest Biomass Transportation Tracking within Varying Forest Canopy , 2011 .

[3]  E. Næsset,et al.  Contributions of differential GPS and GLONASS observations to point accuracy under forest canopies , 2000 .

[4]  Fabrizio Mazzetto,et al.  Algorithms for the interpretation of continuous measurement of the slurry level in storage tanks , 2012 .

[5]  Marvin Everett Mundel,et al.  Motion and Time Study: Improving Productivity , 1970 .

[6]  T. P. McDonalda,et al.  Automated time study of skidders using global positioning system data , 2005 .

[7]  John P. Fulton,et al.  PRECISION FORESTRY IN THE SOUTHEAST U . S . , 2006 .

[8]  Kevin McDonnell,et al.  Assessing Real Time GPS Asset Tracking for Timber Haulage , 2009 .

[9]  Ger Devlin,et al.  Timber haulage routing in Ireland: an analysis using GIS and GPS , 2008 .

[10]  Timothy P. McDonald,et al.  Accuracy of Tracking Forest Machines with GPS , 2000 .

[11]  Jaakko Heinonen,et al.  Operational efficiency and damage to sawlogs by feed rollers of the harvester head. , 2010 .

[12]  Timothy P. McDonald,et al.  Using GPS to evaluate productivity and performance of forest machine systems , 2001 .

[13]  T. Nitami,et al.  Tower Yarder operation in Japan and the performance analysis by GPS-based system. , 2011 .

[14]  Lauri Sikanen,et al.  Transport control of forest fuels by fleet manager, mobile terminals and GPS , 2005 .