ACADEMIA – FOREST MACHINE INDUSTRY COLLABORATION IN SUSTAINABLE ENERGY PRODUCTION University of Eastern Finland Faculty of Science and Forestry Teijo Palander -Finish national target for forest chip-based energy production is 8-12 milj. m 3 (16-25 TWh) by Today it is 6.5 milj m 3 (13 TWh).

June 26, 2016University of Eastern Finland2 JOHN DEERE FOREST MACHINE FACTORY — Locates in the middle of large Boreal forests zone. — Locates in a forestry research center. — Locates in a forestry education center. — Locates in near Russian forests. — Locates in Finnish high technical infrastructure. — Locates in Finnish advanced logistics systems. JOENSUU 1000 forest harvesters and forwarders Euros/machine 400 employers in production 300 workers in development and marketing 6.5 milj. € investments to Joensuu in 2012

MULTIPLE-USE OF HARVESTERS -Multiple-use of forest machines are very important, because still 80 % of wood are harvested using cut-to- length system alone. -Machines (2-4) are owned by small entrepreneurs. -Forest machines are expensive. Therefore they must be cost-efficient. University of Eastern FinlandJune 26, 20163

1) Improving harvesting conditions: - Tending of seedling stands - Delaying harvesting operations - Pre-clearance of spruce undergrowth - New wood production methods: - - Intensive first thinning - - Energy wood harvesting as a part of wood production chain - Creating clusters of stands - Larger stand reserve volume 2) Rationalization of harvesting systems: - Multiple-tree processing - Grapple scale measuring - Harvesting as whole trees - Careful selection of harvested trees and stands - Fewer timber assortments - Integration of pulpwood and energy wood harvesting: - - Whole-tree bundling - - Two-pile cutting method 3) Better utilization of harvesting machinery: - Harwarders - Machines requiring lower investments: - - Small harvesters - - Tracked excavator-based harvesters - Maximization of load size and enlarging of load space - More working hours for harvesting machinery - Larger harvesting companies and networks 4) Development of harvesting machinery and working methods: - Advanced automation in machinery - Improvement of the cutting work process - Training of harvester operators - More efficient use of operators POTENTIAL APPROACHES FOR MORE EFFICIENT SUSTAINABLE WOOD HARVESTING Focus of Academia - John Deere collaboration University of Eastern FinlandJune 26, 20164

A MULTIPLE-TREE PROCESSING – EXAMPLE 2 A harvester is processing small-sized energy wood. First thinning: - height is <15 m, - diameter d 1.3 is <10 cm, - harvesting costs is €/m 3, (8-11 €/MWh). The national target presupposes that the harvesting of first ( d 1.3m <10 cm ) thinning wood is tripled over the current harvesting volume. University of Eastern FinlandJune 26, Two examples of ongoing fruitful development projects.

AN ACCUMULATION HEAD A felling head for the multiple-tree processing: -Number of trees 1-6, -Stand density >4000 trees/ha, -The size of removed trees <38 dm 3 /tree, -Productivity increases 3-6 m 3 /h, -Productivity increases %, -Cost-efficiency increases %. University of Eastern FinlandJune 26, 20166

Operators have a lot potential for more efficient work: -Cost-efficiency increases %, -Automatic data collection provides huge data for self- learning by operators, -Adaptive work study methods are replacing conventional comparative work studies, -Overlapping work phases can be recognized using new work study methodology, -Overlapping work phases are key for learning new more effective work models. HARVESTER SIMULATOR EDUCATION – EXAMPLE 2 University of Eastern FinlandJune 26, 20167

OWN WORK MODELS FOR OPERATORS View from the operator's position in the cab of the John Deere harvester simulator. A typical work rule used by the harvester’s adaptive controller is the following: "IF stem is selected from sector A3 AND felled in direction B4 AND logs are put on the pile to the left of the harvester, THEN move stem after felling to this processing location. University of Eastern FinlandJune 26, 20168

Some collaborators of the fruitful simulator development project are depicted at the end of the project. University of Eastern FinlandJune 26, 20169

University of Eastern Finland10 CONCLUSIONS — Multiple-tree processing and simulator education are successful parts of our vision for more efficent sustainable energy production. — There, of course, could be a gap between academia and industry that would largely be a result of difference in objectives: academia seeking to create new knowledge and to disseminate it broadly, while business having a need to maximize profit and protect R&D results. — This cap has not been an issue because when working together for decades in order to meet our missions, there is enough space in business to publish sufficient amount of results for theory and/or carefully selected and tested experiments, e.g., in simulator environment or few years later.