Efficiency Assessment of Fully Mechanized Harvesting System through the Use of Fleet Management System

Narcis Mihail Bacescu, Alberto Cadei (), Tadeusz Moskalik, Mateusz Wiśniewski, Bruce Talbot and Stefano Grigolato
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Narcis Mihail Bacescu: Department of Land, Environment, Agriculture and Forestry, Università degli Studi di Padova, Viale dell’Università 16, Legnaro, 35020 Padova, Italy
Alberto Cadei: Department of Land, Environment, Agriculture and Forestry, Università degli Studi di Padova, Viale dell’Università 16, Legnaro, 35020 Padova, Italy
Tadeusz Moskalik: Department of Forest Utilization, Institute of Forest Sciences, Warsaw University of Life Sciences—SGGW, Nowoursynowska 159/34, 02-776 Warsaw, Poland
Mateusz Wiśniewski: Kłobuck Forest District, Zakrzewska 85 Str., 42-100 Kłobuck, Poland
Bruce Talbot: Department of Forest and Wood Science, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch 7602, South Africa
Stefano Grigolato: Department of Land, Environment, Agriculture and Forestry, Università degli Studi di Padova, Viale dell’Università 16, Legnaro, 35020 Padova, Italy

Sustainability, 2022, vol. 14, issue 24, 1-17

Abstract: Nowadays the spread of precision forestry has led to the possibility of collecting data related to forest machines for an extended period and with enough precision to support decisions in the optimization of harvesting strategies in terms of technological and environmental efficiency. This study aims to evaluate the effective benefit of automatic data collection through the fleet management system (FMS) of two forest harvesters and two forwarders in pine forests in Poland. The study also aims to determine how the use of FMS can help forest companies to manage their fleet and take advantage of long-term monitoring. Focusing on performance indicators of fuel consumption and CO 2 emissions, as well as on the engine parameters from the Can Bus data, the exploration of data was performed following a Big Data approach, from the creation of an aggregate dataset, pre-elaboration (data cleaning, exploration, selection, etc.) using GIS and R software. The investigation has considered the machine productivity, in the case of the harvesters, and the specific fuel consumption of each machine studied, as well as the time used by each of them during the different working cycle activities and the total amount of timber processed. The main results indicate an average emission of 2.1 kg of CO 2 eq/m 3 for the harvesters and 2.56 kg of CO 2 eq/m 3 for the forwarders, which equates in total to 0.24% of the carbon stored in one cubic meter of wood.

Keywords: digital forestry; long-term monitoring; harvester; forwarder; CO 2 emissions; pine stands (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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