Patrick Hiesl

Date of Award


Level of Access

Campus-Only Thesis

Degree Name

Master of Science (MS)


Forest Resources


Jeffrey G. Benjamin

Second Committee Member

Robert S. Seymour

Third Committee Member

Aaron Weiskittel


The forest industry is a highly cost intensive business and therefore effective management is necessary. Information about productivity and time consumption of harvesting equipment in a variety of stand and site conditions can help operation managers to be efficient. In the state of Maine there have not been any productivity related publications within the past 25 years. Due to this lack of information and the need of information of productivity, especially in small diameter stands, the presented research developed. The focus of this study is on whole-tree harvesting systems including feller-buncher, grapple skidder and stroke delimber, as well as cut-to-length harvesting systems consisting of harvester and forwarder.

Time and motion studies have been carried out during the summer of 2012 during the observation of seven whole-tree and five cut-to-length operations. All operations were carried out in high density, small diameter wood stands common to Maine and this region. In addition to time, tree volume and residual stand damage data was collected. Results of this study present a new model for feller-buncher harvesting time prediction, which includes an algorithm that accounts for the specific harvesting conditions in this region. Further the results show the variation in productivity for the remaining four pieces of equipment. Predictive models are presented for productivity and time estimation. The analysis of the influence of the combination of operator, machine and site conditions shows that this influence explains between 5% and over 50% of the variation in the data for individual machine types (e.g. feller-buncher, grapple skidder). A residual stand damage analysis carried out for the harvesting machines only (feller- buncher, harvester), shows that the damage ranges from less than 10% to over 50% of the residual trees. With the small sample size no significant differences could be found between the two harvesting machines and the stand damage caused.

Recommendations for the future are to collect additional data to verify the predictive models and to expand the data collection to extreme stand and site conditions such as extensive slopes. Additional stand damage data will be necessary to draw more accurate conclusions about the difference between the two harvesting machines. After a limited verification process, however, the results seem to be legitimate and can be incorporated into existing cost and productivity prediction software used in this region. Land managers and contractors will now be able to benchmark their productivity against the baseline productivity encountered in Maine to identify areas of improvement within their own harvesting operations. Participants of this study already agreed on participating again in the future to assist in further data collection as they have identified the benefit of this research to their business.