Plantation forests are established, and expanding, to satisfy increasing global demand for timber products. Shifting societal values, such as safety, productivity, environmental, quality and social are influencing the plantation forestry sector. This is primarily driven through an ever increasing world population, which in turn influences the way nations view the value systems by which they live. More people require more resources—also forest products. Also, the availability of information is influencing the pace of technological development. These changes could result in a difference in the management of plantations that could affect the forest engineering systems of the future. This review aimed to summarize the current status of plantation forests; summarize future developments and possible scenarios in forest plantation management for the various products; and assess whether these developments in a plantation environment could affect the harvesting systems used. Factors influencing the form of plantations include the type and nature of the plantation owner; the change in demand for different and new forest products; climate change factors, including the use of biomass for energy, carbon sequestration and trading; ecosystem services and other products and services; and sustainability certification of forest management. The impact and influence of these factors were summarised into a series of key drivers that will influence the technology used in harvesting machines, as well as the choice of harvesting machines, systems and methods. These drivers were the effect of variations in tree size, the expansion of plantation areas onto more difficult terrain, diversity in plantation design, increased attention towards site impacts and the increased use of biomass for energy. Specific information is provided regarding how the harvesting systems could be affected.

Productivity studies in forest operations are often carried out on new equipment, or on equipment being used in new conditions. Understanding how stand and terrain parameters impact the productivity of harvesting machines is important for determining their optimum use. Such information is normally presented as a productivity or efficiency function; that is, a regression equation that best represents the data. Most studies establish that piece size is the dominant predictor that impacts overall productivity. A common concept known as the “piece-size law” is that productivity increases at a decreasing rate with increasing piece size. What is not well understood is the upper limit to this piece-size law. That is, as the trees get “too” large, we can expect the machine to start to struggle, resulting in a decrease in productivity. Four different data sets—two based in New Zealand and two in Italy—are presented that clearly show an “optimum” piece size for maximum productivity. On average, productivity tended to decrease gradually, not drop off suddenly beyond the optimum. Using more complex statistical functions, it was possible to correctly correlate piece size to productivity.

A study was conducted to determine the effect of some wood characteristics such as species, moisture content and tree part on the performance and product quality offered by a mobile industrial chipper, of the type commonly used for roadside chipping. Two main species, two tree parts and two moisture content levels were combined in a factorial design yielding 8 treatments, each replicated 5 or 6 times. A flow meter was installed on the chipper engine, and all chips produced were weighed and sampled for moisture content and particle size distribution. The results indicated that some wood characteristics such as species and moisture content have a secondary effect on chipper productivity and fuel consumption, which are primarily controlled by piece size. In particular, fuel consumption per unit dry mass seem to be rather constant and in the range of 3.2 l per oven dry ton. Moisture content and tree part may have a significant effect on the particle size distribution of chips. Of course, these results were only verified for the species used in the test and for industrial chippers, and may change if substantially different species or machines are used.

Time and motion studies have been and still are frequently used to describe, understand, and improve forest operations. Delays are recognized as being one of the major factors that limit productivity in most operations and are, therefore, an integral part of most time studies. But, delay events are erratic in both occurrence and magnitude and are, therefore, difficult to precisely quantify within the relatively short observation period of a typical time and motion study. Thus, delay information from individual studies have limited transferability. This paper analyzes the delay component of 34 harvester time study data sets that were recorded between 1998 and 2006. All of the studies were designed and carried out with the same principal investigator. The data sets were all based on harvesters either harvesting and or processing. Three delays categories were used: mechanical, operator, and other. Delays averaged 28.9 percent of the total scheduled time for all 34 studies, comprising of 7.1 percent mechanical, 4.7 percent operator, and 17.1 percent other delays. Delay averages were compared within category descriptions assigned to each data set for statistical significance. Example results include: total delays were higher for operations working on hot decks versus cold decks and operations working in mixed stands had more than twice the overall delays compared to operations in plantations. Considering only mechanical delays, machines that both felled and processed, compared to just processing, had higher mechanical delays. Interestingly, dedicated harvesting machines versus harvesting heads mounted on an excavator base had on average higher operator delays.

The study compared motor-manual cut-to-length (CTL) harvesting, motor-manual whole-tree (WT) harvesting, mechanized CTL harvesting and mechanized WT harvesting as applied to the production of energy chips from the second thinning of Mediterranean pine plantations in flat terrain. Mechanization increased productivity between 6 and 20 times, depending on process step. It also allowed reducing thinning cost by a factor 4. Shifting from CTL to WT harvesting resulted in a reduction of harvesting cost between 40 and 50%. Fuel consumption was between 40 and 100% higher for CTL harvesting than for WT harvesting. Mechanization entailed a reduction of fuel consumption between 10 and 40%. Stand damage was generally low, between 1.5 and 6%. Mechanized CTL harvesting resulted in the lowest incidence of wounding, and the difference between mechanized CTL and manual WT harvesting was statistically significant. Soil compaction was absent or very small, depending on treatment. Mechanized thinning may produce larger increases of soil bulk density, compared to motor-manual thinning, but the difference is small, although significant. CTL harvesting leaves a larger amount of biomass on the soil, which relieves possible concerns about soil nutrient depletion. On the other hand, heavy residue loads may increase fire risk especially in sensitive Mediterranean environments.