Han Han-Sup, PhD

This paper offers a conceptual analysis of the unaccounted-for cost of owning and operating used machines from an operational, financial and market perspective. It is based on input from experts and a literature review. In the scientific literature, assessing the operating cost of used machines in forest operations is typically based on standard cost assessment methods using costing/pricing input from similar unused machines. This is the case since there are usually no historical data for observed used machines available to analyze. This substitute analysis is problematic to many used and depreciated machines owners. The changing trends in forest technology attest that old machinery do not hold to the same input cost data variables or values of new machines. In fact, they belong to two rather competing different markets: (used vs. new equipment markets). With the technological, market and machinery regulations and dynamic changes, the substitute cost analysis is not representative. Better data is required to understand the cost of owning and operating used machines and the justification is the focal point of this paper. The outcome of the expert and literature analysis in this paper demonstrates that a broader understanding of the cost of a used machine is required and doable. A proposed understanding integrates the machine availability (performance), cost factors (financial) and market evaluation (price), in isolation (single piece of machine) as well as in a fleet, to assess a used machine ownership cost. The study is intended to offer forest machine operators, owners, scientists, and practitioners a proposed new approach to value used machines and further investigations and data inputs required to make used machines costing methods more relevant.

As mechanization increases, the percentage of the total cost of the logging operation due to equipment purchase and operation increases. This makes assumptions about machine life, machine maintenance costs, and fuel consumption more critical in understanding the costs of logging operations. For many years machine rate calculations have followed a fixed format based on the concept of scheduled and productive machine hours. When equipment utilization is less than 100%, the traditional machine rate calculation assumes that the machine continues to depreciate and machine wear occurs during the non-productive time at the same rate as during the productive time. This can lead to overestimates of the hourly cost of machine operation by effectively shortening the machine lifetime productive hours as the utilization decreases. The use of inflated machine rates can distort comparisons of logging systems, logging strategies, equipment replacement strategies, and perhaps the viability of a logging operation. We propose adjusting the life of the machine to account for non-productive time: machine life in years should be increased with a decrease in machine utilization, while cumulative machine life in hours remains the same. Once the life has been adjusted, the traditional machine rate calculation procedure can be carried out as is normally done. We provided an example that shows the traditional method at 50% utilization yielded a machine rate per productive hour nearly 30% higher than our modified method. Our sample analysis showed the traditional method consistently provided overestimates for any utilization rate less than 100%, with lower utilization rates yielding progressively increasing overestimates. We believe that our modified approach yields more accurate estimates of machine costs that would contribute to an improved understanding of the machine costs of forest operations.

Forestry equipment simulators offer opportunities for new operators to become familiar with operating logging machines as well as a promising solution to the high costs of training forestry equipment operators. Current literature lacks a synthesis on how best to train forestry equipment operators using simulators. The goal of this review was to identify effective ways to incorporate forestry equipment simulators into an equipment operator training curriculum. We analyzed a total of 14 independent studies in which construction and forestry equipment operators were trained on simulators and engaged in discussions with nine professionals in the field of heavy equipment operator training. In this review, traditional machine training and simulator training practices are introduced. Then, four key aspects of skill acquisition for forestry equipment operators are identified. Information collected from peer-reviewed literature and discussions with industry experts are used to consider how each aspect of skill acquisition is addressed in both traditional training using real machines and simulator-based training. Drawing on these sources, benefits and drawbacks of traditional machine training and simulator-based training for forestry equipment operators are synthesized and discussed. Finally, a model for an integrated and adaptive training curriculum that incorporates principles and technologies from both traditional machine training and simulator training is presented.