Gradewood: Strength grading for engineered wood products Project duration

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1 Gradewood: Strength grading for engineered wood products Project duration Alpo Ranta-Maunus, VTT

2 Project Partners and their Roles VTT, Finland, Project Coordinator BRE, UK, Dissemination of results FCBA, France, Statistical analysis TUM, Germany, Experimental research SP, Sweden, Input for standards HFA, Austria, Experimental research TUW, Austria, Modelling of effect of defects UL, Slovenia, Simulation of grading ETH, Switzerland (from 2009-), New methods Grading equipment developing industries : LuxScan Technologies, MiCROTEC GmbH, TRIOMATIC CBS, Brookhuis Micro-Electronics, Rosén & Co Maskin AB Building With Wood (CEI-Bois), Industrial funding and leadership Puupäivä Alpo Ranta-Maunus 2

3 Content of presentation 1. Joint analysis of experimental results 2. Variability of properties 3. Variability of grading methods 4. Quality 5. Potential for improvement Puupäivä Alpo Ranta-Maunus 3

4 Joint analysis of experimental results Participants had access to same test data: Transparency improved Large data base: smaller statistical error New countries tested Puupäivä Alpo Ranta-Maunus, VTT 4

5 Number of existing data analysed in Gradewood (all measurements- min measurements) country pine spruce Measurements: 1. MOR/UTS bending bending tension 2. MOE AT Density CZ tkar DE E dyn EE FI FR LV NO RU SE SI UK total Puupäivä Alpo Ranta-Maunus 5

6 New experiments of Gradewood project Measuremets: strength, MOE, Density, tkar, E dyn, IPs of 5 grading machines country pine spruce total bending tension bending tension CH FI FR PL RO RU SE SI SK UA total Puupäivä Alpo Ranta-Maunus 6

7 New experiments of Gradewood project Part 1 Puupäivä Alpo Ranta-Maunus 7

8 What we found - variability High variability of grade determining properties GDP (Strength, MOE, density) Country is not a good predictor of GDP Trends between Nordic zone and rest of Europe Source: FCBA, D.Reuling, A.Bouvet Puupäivä Alpo Ranta-Maunus 8

9 Variability in sawmill Changes of input quality take place in daily production Timber quality is clustered Input quality influences output quality Puupäivä Alpo Ranta-Maunus 9

10 Conclusions - variability Small growth areas (e.g. countries) as a criteria for the determination of settings for grading machines do not make sense - neither from an industrial nor from a scientific point of view Incoming quality in mill production is typically clustered Incoming quality influences quality of graded timber Therefore: Grading method must be able to cope with the variability Possible solution: Dynamic settings + testing as a means of factory production control Puupäivä Alpo Ranta-Maunus 10

11 Example: variation of dynamic adaptive settings Figure 5: Production settings of IP- MOR for the windows size 100 and 300 when grading to C40-C30-C18 CIB-W18, August 29, 2011 Turk & Ranta-Maunus

12 Variability of grading methods Coefficient of explanation (r 2 ) between GDP and measured variables. CEE spruce in bending Grading machines Laboratory data single IP multiple IP MOE density KAR strength MOE density Puupäivä Alpo Ranta-Maunus 12

13 f t (N/mm 2 ) f t (N/mm 2 ) Variability of regression lines r 2 (IP1/f t ) = r 2 (E freq /f t ) = IP E freq (kn/mm 2 ) Figure. Regression lines between tension strength of pine and IP1 (left) and E freq (right) in regions of Sweden, Finland, Russia, Poland and France. Puupäivä Alpo Ranta-Maunus 13

14 Quality Project objectives: Full utilization of properties of timber Credibility of timber as structural material Changes are needed in grading practices to meet objectives The overall vision improved competitiveness, and increased market share in construction will in the long run only be reached by high quality in terms of strength, stiffness and density Puupäivä Alpo Ranta-Maunus 14

15 Cumulative distribution Cumulative distribution 1 0,8 0,6 0,4 0, Strength [N/mm2] C35 C24 C24 alone all Strength distribution of graded timber: CEE spruce (n=2069) 0,05 0,04 0,03 0,02 0,01 C35 C24 C24 alone all Strength [N/mm 2 ] Puupäivä Alpo Ranta-Maunus 15

16 Potential for improvement Findings Correlation of machine parameter (IP) and GDP s vary very much visual parameters have low correlations Higher correlations lead to more reliable grades Variation in grades are lower when grade combinations are graded (e.g. C18/C24/C35) than when only single grades with high yield are graded (e.g. C24 alone) Improvement of reliability will reduce yield in single grades but hardly reduce yield in multiple grades full use of strength potential is possible Puupäivä Alpo Ranta-Maunus 16

Potential for improved grading methods in future Improvements in using fibre deviation measurements in nearer future seems possible (Results of TUM Frank Hunger) Future

17 Potential for improved grading methods in future Improvements in using fibre deviation measurements in nearer future seems possible (Results of TUM Frank Hunger) Future improvements of grading by modelling growth features are further possible Source: TUM, Frank Hunger Source: TU Wien, Karin Hofstetter Puupäivä Alpo Ranta-Maunus 17

18 Further actions A transition group, financed by industry, should be formed to transfer the results into standardisation Possible changes: 1. Variability of timber properties was been found to be more severe than was known before the project. This will have an impact to sampling and grading methods. Until now, settings have relied too much on capability of a sample to represent the timber to be graded in production. 2. New methods were found to cope also with less representative sampling and with quality shifts during production. 3. Output control method, as used in Europe, is proposed to be withdrawn. Puupäivä Alpo Ranta-Maunus 18

19 Summary of results and conclusions A statistical criterion for definition of a grading area Prediction limit method to be used as a robust method of determination of initial settings Adaptive production settings method was developed and suggested for continues adjustment of settings Output control method standard to be withdrawn Strength of spruce from new tested countries is not remarkably different from existing CE data Quality control of strength graded timber is needed independently of grading method, visual or machine Puupäivä Alpo Ranta-Maunus 19

20 MOR [MPa] Example of prediction limit (10%) method IP Puupäivä Alpo Ranta-Maunus 20

21 Acknowledgements Research plan of Gradewood-project was based on a feasibility study made by the European wood industries under the Roadmap 2010 Building With Wood programme, and this project was supported by the industry via CEI- Bois. CEI-Bois was the main industrial financier of this project. Besides the Building With Wood programme financing industries the following companies supported one of the research participants: Martinssons såg, Setra Group, Norra Skogsägarna, SCA, Swedish Forest Industries Federation, Wood Center North (TCN). The Gradewood-project belongs to the Wood Wisdom.Net-programme and was funded by national technology development bodies: Tekes, Finnish Funding Agency for Technology and Innovation (Finland), Vinnova (Sweden), Federal Ministry of Education and Research (Germany), Ministry of Agriculture (France), and Slovenian Research Agency. The contributions from funding organisations and other support are gratefully acknowledged. Research partners want to thank the active industrial leadership of the project and participating grading equipment producers for their valuable contributions. Puupäivä Alpo Ranta-Maunus 21

22 Some main publications Buksnowitz C, Konnerth J, Hackspiel C, Hofstetter K, Müller U, Gindl W, and Teischinger A (2010). Knots in trees strain distribution in a naturally optimized material. Wood Science and Technology 44: Ranta-Maunus A (ed) (2009). Strength of European Timber, Part 1: Analysis of growth areas based on existing test results. VTT Publications: 706 (105 p + app 63p ) Ranta-Maunus Alpo, Denzler Julia K. & Stapel Peter (2011). Strength of European Timber, Part 2: Properties of spruce and pine tested in Gradewood project. VTT Working Papers: 179 (67 p + app 46). Stapel P, van de Kuilen J.W.G. (2010): Growth areas in Europe with regard to different wood species and grading principles. WCTE Riva del Garda, Italy. Stapel P, Rais A, van de Kuilen J.W.G. (2010). Influence of origin and grading principles on the engineering properties of European timber. Council for research and Innovation in Building and Construction, Working Commission W18 -Timber Structures, Meeting 43, Nelson, New Zealand. Ranta-Maunus A,Turk G (2010). Approach of dynamic production settings for Machine strength grading. WCTE 2010, Riva del Garda, Italy Ziethén R, Bengtsson C (2010). Machine strength grading prediction limits evaluation of a new method for derivation of settings. WCTE 2010, Riva del Garda, Italy Puupäivä Alpo Ranta-Maunus 22

Introduction. Keywords: grading standard, mechanical properties, sawn timber, timber grading, timber source

Introduction. Keywords: grading standard, mechanical properties, sawn timber, timber grading, timber source DOI 1.1515/hf-213-42 Holzforschung 214; 68(2): 23 216 Peter Stapel* and Jan-Willem G. van de Kuilen Efficiency of visual strength grading of timber with respect to origin, species, cross section, and grading