Research Article
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Approaches on Primary Log Breakdown Process

Year 2017, Volume: 17 Issue: 3, 479 - 490, 27.11.2017
https://doi.org/10.17475/kastorman.285229

Abstract

Abstract



Aim of study: Innovations of “primary breakdown process” which is the
first step of log sawing process were evaluated with their reasons and results.



Area of study: Primary log breakdown process were investigated with
products of domestic and foreign log sawing machine manufacturers, scientific
studies and operations at especially foreign sawmills.



Material and Methods: Log quality assessment techniques, sawing
techniques and sawing machines were compared with conventional methods.



Main results: Losses during the log sawing can be minimized with small
but effective innovations. However, domestic sawmills which are
foreign-dependent on especially raw material (log) should consider their
financial situations while taking an investment decision.



Research highlights: Domestic sawmills can try “non-destructive
evaluation techniques” for required evaluations while before, during and after
the primary breakdown process.

References

  • Berglund A. 2014. Efficient utilization of sawlogs using scanning techniques and computer modelling. Luleå University of Technology, Skellefteå, Sweden.
  • BS 4978. 2007. Visual Strength Grading of Soft Wood – Specification. British Standards Institution, United Kingdom.
  • Burdurlu E. 1995. Lumber Industry and Drying, Bizim Büro Printing House.
  • Campbell E. 2013. Simulation of sawmill yields at Hyne Tuan Pine Mill, Dissertation Report of ENG4112 Research Project, Faculty Health, Engineering & Sciences University of Southern Queensland, Australia.
  • Cook D.F., Wolfe M.L. 1991. Genetic algorithm approach to a lumber cutting optimization problem. Cybernetics and Systems, 22(3):357–365.
  • Dündar T., Divos, F. 2014. European Wood NDT & NDE Research and Practical Applications. Eurasian Journal of Forest Science, 2(1), 35-43.
  • Dündar T., Kurt Ş., As N., Uysal B. 2012. Nondestructive Evaluation Of Wood Strength Using Thermal Conductivity. Bioresources, vol.7, pp.3306-3316.
  • Fredriksson M. 2014, The value of wood. Doctoral thesis, Luleå University of Technology, Skellefteå, Sweden.
  • Giudiceandrea F., Ursella E., Vicario E. 2011. A high speed CT scanner for the sawmill industry. In Proceedings of the 17th International Non Destructive Testing and Evaluation of Wood Symposium, University of West Hungary, Sopron, Hungary.
  • Giudiceandrea F., Ursella E., Vicario E. 2012. From research to market: a high speed CT scanner for the sawmill industry. In Bonfiglio, A., Magenes, G., Pietrabissa, R., and Gabriella, M., editors, Dalla ricerca al mercato trasformare il risultato della ricerca in un prodotto., pages 159–169, Bressanone, Italy. XXXI Scuola Annuale di Bioingegneria.
  • Görgün H.V., 2013. Determination Of Bending Strength And Modulus Of Elasticity In Wooden Beam With Nondestructive And Destructive Test Methods. Master's Degree Thesis, Institute Of Science And Technology Istanbul University, Istanbul.
  • How S.S., Sik H.S., Ahmad I. 2007. Review on six types of log cutting methods in various applications: part 1. Forest Research Institute, (45), Malaysia.
  • Ištvanić J., Beljo Lučić R., Jug M., Karan R. 2009. Analysis of factors affecting log band saw capacity. Croatian Journal of Forest Engineering, 30(1), 27-35.
  • İçel, B., Beram, A. 2016. Non-destructive evaluation methods that can be used for the determination of some properties of historical wooden structures. Turkish Journal of Forestry, 17(2), 201-207.
  • Johansson E. 2013. Computed tomography of sawlogs knot detection and sawing optimization. Doctoral thesis, Luleå University of Technology, Skellefteå, Sweden.
  • Kol, HŞ., Yalçın, İ. 2015. Predicting Wood Strength using Dielectric Parameters. BioResources, 10(4), 6496-6511.
  • Korkut S. 2003. Researches On Optimization In Lumber Production. Doctoral Thesis, Institute of Science, Istanbul University, Istanbul, Turkey.
  • Lewis D.W. 1985. Sawmill simulation and the best opening face system: a user's guide. US Department of Agriculture, Forest Service, Forest Products Laboratory.
  • Özen R. 1982. Lumber Industry Lecture Note (Unpublished). Faculty of Forest, Karadeniz Technical University, Trabzon, Turkey.
  • Pellerin R.F., Ross R.J. 2002. Nondestructive Evaluation of Wood. Forest Products Society Publication, Madiosun, USA, 1-892529-26-2.
  • Reinders M.P., Hendriks T.H.B. 1989. Lumberproduction optimization. European Journal of Operational Research, 42(3): 243–253.
  • Robichaud Y. 1975. Band resaws for sawing hardwoods: a comparison between horizontal and vertical resaws. Can. Dept. Environ., Eastern Forest Prod. Lab. OPX 148E. 13 pp.
  • Schmidt J. 2009. "Developments in Log Merchandising, Board Handling and Trimming Systems in the Sawmill" Catalogue. Springer Maschinenfabrik AG.
  • Singmin M., NTRI (National Timber Research Institute - South Africa). 1978. SIMSAW: A simulation program to evaluate the effect of sawing patterns on log recovery. National Timber Research Institute, Council for Scientific and Industrial Research.
  • Sohrabi P. 2013. A Three-stage Control Mechanism for the Lumber Production Process of a Sawmill Based on a Powers-of-two Modelling Approach. Master of Applied Science Thesis, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Steele P.H. 1984. Factors determining lumber recovery in sawmilling. US Department of Agriculture, Forest Service, Forest Products Laboratory.
  • Szymani R. 1990. The latest developments in scanning technology and process optimization in the North American wood industry. Proceedings of the First European Wood Symposium "Wood and Computer Integrated Manufacturing: What is the Future?" Centre Technique du Bois et de l'Ameublement, Paris, France, May 10-11, 1990.
  • Szymani R. 1995. Latest Advances in Sawmilling. Serninario Internacional de Utilizacao da Maderia de Eucalipto para Serraria, Sao Paulo, Brazil, 5-6.
  • Tejavibulya S. 1981. Dynamic programming sawing models for optimizing lumber recovery. College of Forest Resources, University of Washington.
  • Todoroki C.L. 1990. AUTOSAW system for sawing simulation. New Zealand Journal of Forestry Science, 20(3):332–348.
  • Todoroki, C.L., Rönnqvist, E.M. 1997. Secondary log breakdown optimization with dynamic programming. Journal of the Operational Research Society, 48(5), 471-478.
  • Todoroki C.L.. Ronnqvist E.M. 1999. Combined primary and secondary log breakdown optimisation. The Journal of the Operational Research Society, 50(3):219–229. ISSN 0160-5682.
  • TS 1265. 1973. Sawn timber (Coniferous) - For building construction, Turkish Standards Intitution.
  • URL1. 2016. Metal Legs for natural wood products, Massam.
  • URL2. 2006. The SAWSIM Sawmill Simulation Program, HALCO Software Systems Ltd.,
  • URL3. MWP. 2016. CT scanning of timber to increase the product value. The Marcus Wallenberg Prize 2016, http://mwp.org/ct-scanning-of-timber-to-increase-the-product-value
  • URL4. Microtec-Springer. 2016. Innovative wood processing solutions. http://springer-microtec.com/
  • URL5. 2016. Manufacturer of Sawmill Line and Equipment, Linck,
  • URL6. The Wassmer Group. 2016. Sawmill Technology, Log Band Saw,
  • URL7. Üstünkarlı. 2016. Log Sawing Lines, http://ustunkarli.com.tr/
  • URL8. Wood-Mizer. 2016. WM1000 Sawmill, http://www.woodmizer-europe.com/Products/Industrial/Sawmills/WM1000
  • URL9. 2016. EWD, The SawLine Company, http://www.ewd.de/en/technology-products/bandsaw-technology/band-resaw-systems/
  • URL10. 2016. Sawmill Hydraulics Inc. http://www.4helle.com/scragg_mills.htm
  • Zeng Y. 1991. Log breakdown using dynamic programming and 3-D log shape. Thesis, Oregon State University.
  • Zeng Y. 1995. Integration of an expert system and dynamic programming approach to optimize log breakdown using 3-dimensional log and internal defect shape information. Thesis, Oregon State University.
  • Steele P., Wade M.W., Bullard S.H., Araman P.A. 1992. Relative kerf and sawing variation values for some hardwood sawing machines. Faculty Publications. Stephen F. Austin State University, Texas, 130.

Birincil Tomruk Biçme İşlemiyle İlgili Yaklaşımlar

Year 2017, Volume: 17 Issue: 3, 479 - 490, 27.11.2017
https://doi.org/10.17475/kastorman.285229

Abstract

Özet



Çalışmanın amacı: Tomruk biçme işleminin ilk aşaması olan “Birincil tomruk biçme prosesiyle
ilgili geliştirilen yeniliklerin, sebepleri ve sonuçlarıyla birlikte
irdelenmiştir.



Çalışma alanı: Yerli ve yabancı tomruk
biçme makinesi üreticilerinin ürünleri ve bilimsel çalışmalar ile özellikle
yurtdışında faaliyet gösteren kereste fabrikalarında prosesin bu aşamasında
yapılan yenilikler ele alınmıştır.



Materyal ve Yöntem: Tomruk kalitesinin değerlendirme yöntemleri, kullanılan
biçme teknikleri ve biçme makinelerinin incelenmiş ve geleneksel yöntemlerle
karşılaştırılmıştır.



Sonuçlar: Tomruğun işlenmesinde
yaşanan kayıplar, ufak ama etkili yeniliklerle en aza indirgenebilir. Ancak
tomruk bakımından büyük oranda dışa bağımlı olan kereste endüstrisi, bu
müdahaleleri yaparken finansal durumlarını göz önünde bulundurmaları
gerekmektedir.  



Araştırma vurguları: Yerli üreticilerin bu proses öncesi, sırası ve sonrasında gerekli
incelemelerin yapabilmesi adına alternatif yöntemlerden tahribatsız değerlendirme
yöntemlerinin değerlendirmesi tavsiye edilmektedir.

References

  • Berglund A. 2014. Efficient utilization of sawlogs using scanning techniques and computer modelling. Luleå University of Technology, Skellefteå, Sweden.
  • BS 4978. 2007. Visual Strength Grading of Soft Wood – Specification. British Standards Institution, United Kingdom.
  • Burdurlu E. 1995. Lumber Industry and Drying, Bizim Büro Printing House.
  • Campbell E. 2013. Simulation of sawmill yields at Hyne Tuan Pine Mill, Dissertation Report of ENG4112 Research Project, Faculty Health, Engineering & Sciences University of Southern Queensland, Australia.
  • Cook D.F., Wolfe M.L. 1991. Genetic algorithm approach to a lumber cutting optimization problem. Cybernetics and Systems, 22(3):357–365.
  • Dündar T., Divos, F. 2014. European Wood NDT & NDE Research and Practical Applications. Eurasian Journal of Forest Science, 2(1), 35-43.
  • Dündar T., Kurt Ş., As N., Uysal B. 2012. Nondestructive Evaluation Of Wood Strength Using Thermal Conductivity. Bioresources, vol.7, pp.3306-3316.
  • Fredriksson M. 2014, The value of wood. Doctoral thesis, Luleå University of Technology, Skellefteå, Sweden.
  • Giudiceandrea F., Ursella E., Vicario E. 2011. A high speed CT scanner for the sawmill industry. In Proceedings of the 17th International Non Destructive Testing and Evaluation of Wood Symposium, University of West Hungary, Sopron, Hungary.
  • Giudiceandrea F., Ursella E., Vicario E. 2012. From research to market: a high speed CT scanner for the sawmill industry. In Bonfiglio, A., Magenes, G., Pietrabissa, R., and Gabriella, M., editors, Dalla ricerca al mercato trasformare il risultato della ricerca in un prodotto., pages 159–169, Bressanone, Italy. XXXI Scuola Annuale di Bioingegneria.
  • Görgün H.V., 2013. Determination Of Bending Strength And Modulus Of Elasticity In Wooden Beam With Nondestructive And Destructive Test Methods. Master's Degree Thesis, Institute Of Science And Technology Istanbul University, Istanbul.
  • How S.S., Sik H.S., Ahmad I. 2007. Review on six types of log cutting methods in various applications: part 1. Forest Research Institute, (45), Malaysia.
  • Ištvanić J., Beljo Lučić R., Jug M., Karan R. 2009. Analysis of factors affecting log band saw capacity. Croatian Journal of Forest Engineering, 30(1), 27-35.
  • İçel, B., Beram, A. 2016. Non-destructive evaluation methods that can be used for the determination of some properties of historical wooden structures. Turkish Journal of Forestry, 17(2), 201-207.
  • Johansson E. 2013. Computed tomography of sawlogs knot detection and sawing optimization. Doctoral thesis, Luleå University of Technology, Skellefteå, Sweden.
  • Kol, HŞ., Yalçın, İ. 2015. Predicting Wood Strength using Dielectric Parameters. BioResources, 10(4), 6496-6511.
  • Korkut S. 2003. Researches On Optimization In Lumber Production. Doctoral Thesis, Institute of Science, Istanbul University, Istanbul, Turkey.
  • Lewis D.W. 1985. Sawmill simulation and the best opening face system: a user's guide. US Department of Agriculture, Forest Service, Forest Products Laboratory.
  • Özen R. 1982. Lumber Industry Lecture Note (Unpublished). Faculty of Forest, Karadeniz Technical University, Trabzon, Turkey.
  • Pellerin R.F., Ross R.J. 2002. Nondestructive Evaluation of Wood. Forest Products Society Publication, Madiosun, USA, 1-892529-26-2.
  • Reinders M.P., Hendriks T.H.B. 1989. Lumberproduction optimization. European Journal of Operational Research, 42(3): 243–253.
  • Robichaud Y. 1975. Band resaws for sawing hardwoods: a comparison between horizontal and vertical resaws. Can. Dept. Environ., Eastern Forest Prod. Lab. OPX 148E. 13 pp.
  • Schmidt J. 2009. "Developments in Log Merchandising, Board Handling and Trimming Systems in the Sawmill" Catalogue. Springer Maschinenfabrik AG.
  • Singmin M., NTRI (National Timber Research Institute - South Africa). 1978. SIMSAW: A simulation program to evaluate the effect of sawing patterns on log recovery. National Timber Research Institute, Council for Scientific and Industrial Research.
  • Sohrabi P. 2013. A Three-stage Control Mechanism for the Lumber Production Process of a Sawmill Based on a Powers-of-two Modelling Approach. Master of Applied Science Thesis, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Steele P.H. 1984. Factors determining lumber recovery in sawmilling. US Department of Agriculture, Forest Service, Forest Products Laboratory.
  • Szymani R. 1990. The latest developments in scanning technology and process optimization in the North American wood industry. Proceedings of the First European Wood Symposium "Wood and Computer Integrated Manufacturing: What is the Future?" Centre Technique du Bois et de l'Ameublement, Paris, France, May 10-11, 1990.
  • Szymani R. 1995. Latest Advances in Sawmilling. Serninario Internacional de Utilizacao da Maderia de Eucalipto para Serraria, Sao Paulo, Brazil, 5-6.
  • Tejavibulya S. 1981. Dynamic programming sawing models for optimizing lumber recovery. College of Forest Resources, University of Washington.
  • Todoroki C.L. 1990. AUTOSAW system for sawing simulation. New Zealand Journal of Forestry Science, 20(3):332–348.
  • Todoroki, C.L., Rönnqvist, E.M. 1997. Secondary log breakdown optimization with dynamic programming. Journal of the Operational Research Society, 48(5), 471-478.
  • Todoroki C.L.. Ronnqvist E.M. 1999. Combined primary and secondary log breakdown optimisation. The Journal of the Operational Research Society, 50(3):219–229. ISSN 0160-5682.
  • TS 1265. 1973. Sawn timber (Coniferous) - For building construction, Turkish Standards Intitution.
  • URL1. 2016. Metal Legs for natural wood products, Massam.
  • URL2. 2006. The SAWSIM Sawmill Simulation Program, HALCO Software Systems Ltd.,
  • URL3. MWP. 2016. CT scanning of timber to increase the product value. The Marcus Wallenberg Prize 2016, http://mwp.org/ct-scanning-of-timber-to-increase-the-product-value
  • URL4. Microtec-Springer. 2016. Innovative wood processing solutions. http://springer-microtec.com/
  • URL5. 2016. Manufacturer of Sawmill Line and Equipment, Linck,
  • URL6. The Wassmer Group. 2016. Sawmill Technology, Log Band Saw,
  • URL7. Üstünkarlı. 2016. Log Sawing Lines, http://ustunkarli.com.tr/
  • URL8. Wood-Mizer. 2016. WM1000 Sawmill, http://www.woodmizer-europe.com/Products/Industrial/Sawmills/WM1000
  • URL9. 2016. EWD, The SawLine Company, http://www.ewd.de/en/technology-products/bandsaw-technology/band-resaw-systems/
  • URL10. 2016. Sawmill Hydraulics Inc. http://www.4helle.com/scragg_mills.htm
  • Zeng Y. 1991. Log breakdown using dynamic programming and 3-D log shape. Thesis, Oregon State University.
  • Zeng Y. 1995. Integration of an expert system and dynamic programming approach to optimize log breakdown using 3-dimensional log and internal defect shape information. Thesis, Oregon State University.
  • Steele P., Wade M.W., Bullard S.H., Araman P.A. 1992. Relative kerf and sawing variation values for some hardwood sawing machines. Faculty Publications. Stephen F. Austin State University, Texas, 130.
There are 46 citations in total.

Details

Journal Section Articles
Authors

Hızır Volkan Görgün

Öner Ünsal

Publication Date November 27, 2017
Published in Issue Year 2017 Volume: 17 Issue: 3

Cite

APA Görgün, H. V., & Ünsal, Ö. (2017). Approaches on Primary Log Breakdown Process. Kastamonu University Journal of Forestry Faculty, 17(3), 479-490. https://doi.org/10.17475/kastorman.285229
AMA Görgün HV, Ünsal Ö. Approaches on Primary Log Breakdown Process. Kastamonu University Journal of Forestry Faculty. November 2017;17(3):479-490. doi:10.17475/kastorman.285229
Chicago Görgün, Hızır Volkan, and Öner Ünsal. “Approaches on Primary Log Breakdown Process”. Kastamonu University Journal of Forestry Faculty 17, no. 3 (November 2017): 479-90. https://doi.org/10.17475/kastorman.285229.
EndNote Görgün HV, Ünsal Ö (November 1, 2017) Approaches on Primary Log Breakdown Process. Kastamonu University Journal of Forestry Faculty 17 3 479–490.
IEEE H. V. Görgün and Ö. Ünsal, “Approaches on Primary Log Breakdown Process”, Kastamonu University Journal of Forestry Faculty, vol. 17, no. 3, pp. 479–490, 2017, doi: 10.17475/kastorman.285229.
ISNAD Görgün, Hızır Volkan - Ünsal, Öner. “Approaches on Primary Log Breakdown Process”. Kastamonu University Journal of Forestry Faculty 17/3 (November 2017), 479-490. https://doi.org/10.17475/kastorman.285229.
JAMA Görgün HV, Ünsal Ö. Approaches on Primary Log Breakdown Process. Kastamonu University Journal of Forestry Faculty. 2017;17:479–490.
MLA Görgün, Hızır Volkan and Öner Ünsal. “Approaches on Primary Log Breakdown Process”. Kastamonu University Journal of Forestry Faculty, vol. 17, no. 3, 2017, pp. 479-90, doi:10.17475/kastorman.285229.
Vancouver Görgün HV, Ünsal Ö. Approaches on Primary Log Breakdown Process. Kastamonu University Journal of Forestry Faculty. 2017;17(3):479-90.

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