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Holappa Jonsson, Sara, 2018. Evaluation of the increased pre-harvest forecasting precision of sawlog supply by use of historical harvester data and wood properties models : a case study on Scots pine in northern Sweden. Second cycle, A2E. Umeå: SLU, Department of Forest Biomaterials and Technology (from 131204)

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Abstract

Nordic wood procurement is customer-oriented and involves real-time steering of the procurement according to products and markets. The development of better products and increased process efficiency is important for industrial customers. Sawmills’ demand usually covers total volume, species, lengths, diameter, time of delivery and stock levels, but the development is moving towards a more specific demand targeting also wood characteristics.

Thanks to StanForD2010 it is possible to store detailed data of harvested trees through harvester files from previously harvested stands in a standardized manner. Skogforsk has developed the tool hprImputation, which uses kMSN imputation to make yield forecasting of planned harvesting stands based on the known outcome from stored harvester data of similar stands. It is possible to combine the imputation tool with earlier developed models for forecasting wood characteristics, thereby en-abling forecasts on both stand- and log level. With the possibilities to measure qual-ity with 3D/X-ray scanners in sawmills, the forecasting precision on log level can be evaluated.

The aim of this masters’ thesis was firstly to evaluate the perceived benefits of in-creased precision in yield forecasting from a value chain perspective and identify key forecasting variables for different perspectives of the value chain. Secondly, the aim was to evaluate the influence of applying the imputation method based on har-vester data and wood properties models on the forecasting precision for key varia-bles at the case company SCA.

The study showed that there is a considerable need and value potential for more accurate and detailed forecasting, which would improve the management along the whole value chain from forest to sales of sawmill products. However, there is a need for development of analytical tools that enable a more standardised and transparent handling of the data.

The imputation method developed by Skogforsk provided higher accuracy of fore-casting on stand level compared to traditional methods at SCA but is dependent on accurate input data which was best provided by airborne laser scanning data among currently available data sources. The wood properties model developed by Skog-forsk could provide accurate forecasts on mean heartwood diameter, but further studies should evaluate whether the models should be adjusted to varying stand age as is indicated in this study.
Abstract
This development could provide the missing link between stand characteristics and a sawmill’s outcome of specific products, which combined with high data transpar-ency and integrated analytical tools could boost the abilities of integrated forecast-ing along the value chain.

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Dagens skogsindustri är kundinriktad och styrs av produkter och marknader. Trad-itionellt har sågverkens önskemål berört totalvolym, trädslag, längder, diameter, le-veranstider och lagernivåer, men utvecklingen går mot mer specifika önskemål in-riktade på inre virkeskvaliteter.

Tack vare standarden StanForD2010 är det idag möjligt att samla detaljerad inform-ation om avverkade träd genom skördardata från avverkade bestånd. Skogforsk har utvecklat verktyget hprImputation, som genom kMSN-imputering skapar utbytes-prognoser för planerade avverkningsbestånd baserat på kända utfall från historiskt skördardata för liknande bestånd. Imputeringsverktyget går att kombinera med tidi-gare utvecklade modeller för trädegenskaper, vilket möjliggör prognoser på både bestånds- och stocknivå. Med dagens möjligheter att mäta inre virkesegenskaper genom 3D/röntgenmätramar kan prognoskvaliteten från imputering och trädegen-skapsmodellerna utvärderas för en stor datamängd och därmed bana vägen för en framtida praktisk implementering av prognoser på stocknivå.

Syftet med studien var att utvärdera de upplevda fördelarna av en ökad precision av utbytesprognoser ur ett värdekedjeperspektiv och identifiera önskvärda variabler att prognostisera, samt att utvärdera noggrannheten i prognoser på bestånds- och stock-nivå skapade med Skogforsks verktyg.

Resultatet visade ett stort behov av ökad precision i utbytesprognoser jämfört med nuvarande metoder vid värdföretaget SCA. Detta skulle underlätta planeringen ge-nom hela värdekedjan från bestånd till färdig produkt. Dock finns ett övergripande behov av att utveckla analysverktyg för en mer standardiserad och transparent data-hantering.

Tillämpningen av Skogforsks imputeringverktyg genererade tillförlitliga prognoser på beståndsnivå, men resultaten påverkas av kvaliteten på ingångsdata. Bland da-gens tillgängliga datakällor var laserdata det bästa alternativet för SCA. Egenskaps-modellerna kan med säkerhet generera prognoser på medelkärnvedsdiameter för stora datamängder.

Main title:Evaluation of the increased pre-harvest forecasting precision of sawlog supply by use of historical harvester data and wood properties models
Subtitle:a case study on Scots pine in northern Sweden
Authors:Holappa Jonsson, Sara
Supervisor:Erlandsson, Emanuel and Lindroos, Ola
Examiner:Athanassiadis, Dimitris
Series:Rapport från Institutionen för skogens biomaterial och teknologi
Volume/Sequential designation:2018:9
Year of Publication:2018
Level and depth descriptor:Second cycle, A2E
Student's programme affiliation:SY001 Forest Science - Master's Programme 300 HEC
Supervising department:(S) > Department of Forest Biomaterials and Technology (from 131204)
Keywords:forecasting, wood characteristics, imputation, value chain, wood procurement, heartwood diameter, big data
URN:NBN:urn:nbn:se:slu:epsilon-s-9802
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-s-9802
Subjects:Forestry - General aspects
Forest engineering
Language:English
Deposited On:27 Sep 2018 10:58
Metadata Last Modified:27 Feb 2019 11:42

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