Purpose of the Review: This literature review focused on studies on alternative powertrains and fuels of non-road mobile machinery (NRMM) during the last 15 years and investigated their future potential and expectations. The goal was to evaluate different alternative powertrains based on previous research and highlight the possibilities and challenges of each technology. Additionally, the aim was to conduct a comprehensive overview about the technology development phase of alternative powertrains. Recent Findings: This review covered a total of 115 studies consisting of hybrid, full-electric, biofuels, biogas, and hydrogen solutions. The results highlighted that hybrid and full-electric technologies have the greatest potential to replace conventional diesel engines in the future. The main challenges identified were battery reliability and high technology costs. Regarding biofuel, biogas, and hydrogen, the benefits were mainly lower emissions while the challenges were high costs and low production. Full-electric and hydrogen powertrains were found to reach zero local emissions during operations, while compared to diesel, repair and maintenance caused less emissions of 36–46% during the life cycle with full-electric and hydrogen solutions. With hybrid, biofuels, and biogas powertrains, the emission reduction potential ranged from 37 to 81% during operations and 36–66% during the entire life cycle. The highest Technology Readiness Levels (TRLs) were identified for hybrid and full-electric technologies in industrial machinery (6.9–7.4). The lowest measurable TRL (2.5) was with biogas powered construction machinery. The TRLs of biogas and hydrogen of forest machinery were excluded from this review due to the lack of research. Summary: Alternative powertrains can eventually replace diesel engines, if the challenges with implementation, production, and reliability are solved. Furthermore, the benefits of electric and renewable technologies/fuels are unambiguous from the emission reduction and energy efficiency perspectives. Consequently, we recommend that future research focus especially on the implementation of alternative technologies as well as the improvement of the manufacturing infrastructure.

Prior tree marking is used to guide loggers or forest machine operators on which trees to cut to achieve the desirable silvicultural quality of a thinning treatment. In the future, this beneficial but expensive human work could be automated with advanced driver assistance systems. This study aimed to investigate the effect of conventional prior tree marking on cutting productivity and harvesting quality of the first and later thinnings. A comparative time study was conducted with four experienced harvester operators. The operators thinned 4825 stems with the cut-to-length (CTL) harvesting method in eight thinning stands. The time consumption of the different time elements of cutting work was measured to model the cutting productivity with average values or regress these values against the stem volume or density of removal. Prior tree marking increased the cutting productivity by an average of 2.8% in the first thinnings and 2.7% in later thinnings by reducing the time consumption of boom-out (positioning the harvester head for cut) and moving. The operator effect was notable, even though only experienced operators participated in the study. For some operators, prior tree marking did not make cutting work more efficient, and sometimes hampered it. Prior tree marking improved the quality of the remaining stands in thinnings by producing a more accurate density of remaining trees after the harvesting operation in relation to thinning guidelines. When the stands were not marked, the operators chose trees of poor quality with almost the same accuracy as the forester. These findings lay the foundation for the next-generation operators' guidance and decision support systems, which could detect trees around the harvester and guide the operator in tree selection and managing better thinning intensity in cutting work. Although prior tree marking increased productivity only marginally, the improvement in the quality of harvesting operations must be acknowledged.

The location information of strip roads in thinnings and the numerical variables of strip roads are one aspect of timber harvest quality information. The ideal of automatic quality management for mechanized logging is that the quality of the harvest is calculated and reported based on data collected by forest machines. At present, quality data is collected by means of laborious, manual, field-based, post-harvest measurements. The aim of this study was to develop an automatic method to compute the strip roads of the harvested stands after harvesting, based on the stem-specific location data of the harvester. Subsequently, the strip road variables were computed from the strip road networks. The computed strip road networks were validated with 21 manually recorded field references. The method was also applied to operational stand data, including 544 harvested stands collected from Southern Finland. The results showed that the computation method produces well-located, stand-specific strip road networks from which strip road variables can be accurately determined, covering the whole stand. Thus, the method promotes the automation of quality management and reporting. The computed strip road networks can also support harvester operator work during the harvesting and, later, the automation of harvesting operations.

The aim of this research was to determine the most productive tree-cutting methods, and the factors influencing them, in flat and sloping terrains in tree plantations in Brazil. The study utilized drone-captured video material from harvesting operations in eucalyptus and pine plantations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge or inside of the harvesting front. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned cutting methods. In sloping terrain, the machines were also equipped with a winch assistance system. The time study data of the harvesting work were processed using a video analysis tool developed for the research. The output data of the cut trees were collected with the automatic measuring system of the harvester. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m³, cutting productivity was 45 m³/E₀h in pine cuttings and 55 m³/E₀h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m³/E₀h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work on sloping terrain. The research results suggest that it would be most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident, if we want to precisely identify the factors and work phases in the tree-cutting cycle affecting differences in the productivity of the harvesting chain in tree plantations.

The aim of the research was to determine the most productive tree cutting methods and the factors influencing them in flat and sloping terrain in tree plantations in Brazil. The study utilized drone-captured video material from eucalyptus and pine plantations harvesting operations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge of the harvesting front or inside. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned methods. In slope terrain, the machines were also equipped with a winch assistance system. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m3, cutting productivity was 45 m3/E0h in pine cuttings and 55 m3/E0h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m3/E0h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work in sloping terrain. The research results suggest that it would be the most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident if we want to precisely identify the harvesting conditions and work phases in the tree cutting cycle affecting the differences in the productivity of the harvesting chain in tree plantations.

In the forest sector, the idle time of machinery has a significant impact on fuel consumption, greenhouse gas (GHG) emissions, and operating costs. This study investigated the idle times of forest machinery and timber trucks in Finland. Study materials were collected through questionnaires from small- and medium-sized logging ( loggers ) (N = 817) and timber-hauling ( timber-haulers ) (N = 339) enterprises (SMEs). The response rate from the loggers was 17.9% (n = 146) and 25.7% (n = 87) from the timber-haulers. The study revealed that only a quarter of the loggers and a half of the timber-haulers were aware of the idle times of their fleets. Of these, 55% of the loggers and 61% of the timber-haulers estimated their idle times at 6–14% of the total operating hours of their fleets. The results also indicated that idle time should be lower compared to current levels: respondents that were aware of idling suggested that 2–5% was a more desirable proportion, while the respondents that were unaware of idling rated desirable idle time at < 2% of total operating time. Respondents who had detected the idle times of their fleet noted significantly more opportunities to reduce idling than those who were unaware of idling. The work phases with the greatest potential to reduce idling times during logging operations were “Planning on the harvesting site” and “Operator breaks”. Correspondingly, “Waiting time at the destination (i.e., timber reception of the mill)” and “Driver breaks” were the phases with the most potential to reduce idling during timber-hauling. This study concluded that there is significant potential to reduce fuel consumption and GHG emissions by improving the awareness of the forest machine operators and truck drivers with regard to the idle times of machinery and vehicles. As such, more research data and operator/driver training are needed.