Selecting the most suitable machines to use for wood recovery is essential for computing the operating costs of the whole forestry machinery chain (FMC). Nevertheless, a generalized approach for selecting the most suitable FMC and quantifying the corresponding economic performances for wood recovery (i.e., harvesting and long-distance transport) is still missing. The primary aim of this study is to describe a decision support model, called FOREstry MAchinery chain selection (“FOREMA v1”), which is able to (i) select the most feasible FMC and (ii) calculate the costs (such as EUR·h−1; EUR·t−1 of dry matter, DM) of each operation (OP) comprising the FMC. The model is made up of three different modules (Ms): machinery chain selection (M1), machinery chain organization (M2), and cost calculation (M3). In M1, feasible FMCs are defined according to seven technical parameters that characterize the forest area. For each FMC, FOREMA v1 defines the sequence of OPs and the types of machines that can potentially be used. Once the characteristics of the area in which wood recovery occurs are processed, the user selects the types of machines to use according to the model’s suggestions. In M2 and M3, the user is supported in organizing the FMC (e.g., calculation of the required time, working productivity, and so on) and computing the operating costs. The secondary aim of this study is to discuss a case study focused on chips production for energy generation, providing empirical evidence on how FOREMA v1 works. The proposed model provides a systematic approach for the selection and optimization of the most suitable FMC to adopt for biomass recovery, thus supporting decision-making processes. The results showed that felling had the lowest cost per unit of time (63.7 EUR·h−1) but the highest cost per unit of mass (35.4 EUR·t DM−1) due to its longer working time and lower productivity. Loading and long-distance transport incurred the highest costs both per unit of time (223.5 EUR·h−1) and per unit of mass (29.4 EUR·t DM−1), attributed to the use of medium–small-sized trailers coupled with tractors operating at low speeds, leading to a high number of cycles. For the entire FMC the costs were equal to 147.3 EUR·h−1 and 101.1 EUR·t DM−1
A Preliminary Model for Forestry Machinery Chain Selection and Calculation of Operating Costs for Wood Recovery / L. Nonini, D. Cavicchioli, M. Fiala. - In: FORESTS. - ISSN 1999-4907. - 16:7(2025 Jun 27), pp. 1069.1-1069.24. [10.3390/f16071069]
A Preliminary Model for Forestry Machinery Chain Selection and Calculation of Operating Costs for Wood Recovery
L. Nonini
Primo
;D. CavicchioliSecondo
;M. FialaUltimo
2025
Abstract
Selecting the most suitable machines to use for wood recovery is essential for computing the operating costs of the whole forestry machinery chain (FMC). Nevertheless, a generalized approach for selecting the most suitable FMC and quantifying the corresponding economic performances for wood recovery (i.e., harvesting and long-distance transport) is still missing. The primary aim of this study is to describe a decision support model, called FOREstry MAchinery chain selection (“FOREMA v1”), which is able to (i) select the most feasible FMC and (ii) calculate the costs (such as EUR·h−1; EUR·t−1 of dry matter, DM) of each operation (OP) comprising the FMC. The model is made up of three different modules (Ms): machinery chain selection (M1), machinery chain organization (M2), and cost calculation (M3). In M1, feasible FMCs are defined according to seven technical parameters that characterize the forest area. For each FMC, FOREMA v1 defines the sequence of OPs and the types of machines that can potentially be used. Once the characteristics of the area in which wood recovery occurs are processed, the user selects the types of machines to use according to the model’s suggestions. In M2 and M3, the user is supported in organizing the FMC (e.g., calculation of the required time, working productivity, and so on) and computing the operating costs. The secondary aim of this study is to discuss a case study focused on chips production for energy generation, providing empirical evidence on how FOREMA v1 works. The proposed model provides a systematic approach for the selection and optimization of the most suitable FMC to adopt for biomass recovery, thus supporting decision-making processes. The results showed that felling had the lowest cost per unit of time (63.7 EUR·h−1) but the highest cost per unit of mass (35.4 EUR·t DM−1) due to its longer working time and lower productivity. Loading and long-distance transport incurred the highest costs both per unit of time (223.5 EUR·h−1) and per unit of mass (29.4 EUR·t DM−1), attributed to the use of medium–small-sized trailers coupled with tractors operating at low speeds, leading to a high number of cycles. For the entire FMC the costs were equal to 147.3 EUR·h−1 and 101.1 EUR·t DM−1| File | Dimensione | Formato | |
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