Simulation of a real-time process adaptation in the manufacture of high-density fibreboards using multivariate regression analysis and feedforward control

Andre N, Cho HW, Baek SH, Jeong MK, Young TM (2008) Prediction of internal bond strength in a medium density fiberboard process using multivariate statistical methods and variable selection. Wood Sci Technol 42(7):521–534

Andre N, Young TM, Zaretzki P (2010) Real-time process modeling of wood composite panels. In: Teischinger A, Barbu MC, Dunky M et al (eds) Processing technologies for the forest and biobased products industries, PTF BPI, Kuchl, Austria. Salzburg University of Applied Sciences, Salzburg, pp 28–33

Bernardy G, Scherff B (1997) Process modelling provides online quality control and process optimization in particleboard and fiberboard production. Holz Roh Werkst 55(3):133–140

Chachuat B, Srinivasan B, Bonvin D (2009) Adaptation strategies for real-time optimization. Comput Chem Eng 33(10):1557–1567

Clapp NE Jr, Young TM, Guess FM (2008) Predictive modeling the internal bond of medium density fiberboard using a modified principal component analysis. For Prod J 58(4):49–55

Coleman TF, Li Y (1994) On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds. Math Program 67(1–3):189–224

Cook DF, Chiu CC (1997) Predicting the internal bond strength of particleboard, utilizing a radial basis function neural network. Eng Appl Artif Intell 10(2):171–177

Danzer K, Hobert H, Fischbacher C, Jagemann K-U (2001) Chemometrik. Springer, Berlin

De Jong S (1993) SIMPLS: an alternative approach to partial least squares regression. Chemom Intell Lab Syst 18(3):251–253

Dolezel-Horwath E, Hutter T, Kessler R, Wimmer R (2005) Feedback and feedforward control of wet-processed hardboard production using spectroscopy and chemometric modelling. Anal Chim Acta 544(1–2):47–59

Dunky M, Niemz P (2002) Holzwerkstoffe und Leime. Springer, Berlin

EN 319 (1993) Particleboards and fibreboards—determination of tensile strength perpendicular to the plane of the board. European Committee for Standardization

EN 326-1 (1994) Wood-based panels—sampling, cutting and inspection—part 1: sampling and cutting of test pieces and expression of test results. European Committee for Standardization

EN 622-5 (2006) Fibreboards—specifications—part 5: requirements for dry process boards (MDF). European Committee for Standardization

Esteban LG, Fernández FG, De Palacios P (2011) Prediction of plywood bonding quality using an artificial neural network. Holzforschung 65(2):209–214

Hasener J (2004) Statistische Methoden der industriellen Prozessmodellierung zur Echtzeitqualitätskontrolle am Beispiel einer kontinuierlichen Produktion von Faserplatten. Univ, Hamburg

Little RJA, Rubin DB (2002) Statistical analysis with missing data. Wiley series in probability and statistics, 2nd edn. Wiley, New York

Marutzky R (2006) Energetische und stoffliche Verwertung von Holzresten und Altholz in der Holzwerkstoffindustrie—eine aktuelle Bestandsaufnahme. In: 3. Fachtagung Umweltschutz in der Holzwerkstoffindustrie Göttingen, 18–19.Mai 2006. Univ. Göttingen, Institut für Holzbiologie und Holztechnologie, pp 17–26

Mehmood T, Liland KH, Snipen L, Sæbø S (2012) A review of variable selection methods in partial least squares regression. Chemom Intell Lab Syst 118:62–69

Nelson PRC, Taylor PA, MacGregor JF (1996) Missing data methods in PCA and PLS: score calculations with incomplete observations. Chemom Intell Lab Syst 35(1):45–65

Nørgaard L, Saudland A, Wagner J, Nielsen JP, Munck L, Engelsen SB (2000) Interval partial least-squares regression (iPLS): a comparative chemometric study with an example from near-infrared spectroscopy. Appl Spectrosc 54(3):413–419

Rials TG, Kelley SS, So CL (2002) Use of advanced spectroscopic techniques for predicting the mechanical properties of wood composites. Wood Fiber Sci 34(3):398–407

Riegler M, Gindl-Altmutter W, Hauptmann M, Müller U (2012) Detection of UF resin on wood particles and in particleboards: potential of selected methods for practice-oriented offline detection. Eur J Wood Prod 70(6):829–837

Sjöblom E, Johnsson B, Sundström H (2004) Optimization of particleboard production using NIR spectroscopy and multivariate techniques. For Prod J 54(6):71–75

Steffen A, Janssen A, Kruse K (2001) Analysis of the MDF production process by means of statistical process modelling. Holz Roh Werkst 58(6):419–431

Thömen H (2000) Modeling the physical processes in natural fiber composites during batch and continuous pressing. Oregon State University, Corvallis

Vojinović V, Cabral JMS, Fonseca LP (2006) Real-time bioprocess monitoring: part I: in situ sensors. Sens Actuators, B 114(2):1083–1091

Weigl M, Maschl G, Wimmer R, Mitter R (2012) Within-process and seasonal changes during industrial production of high-density fibreboard. Part 2: PLS modelling of chemical alterations, refining conditions and panel thickness swell. Holzforschung 66(5):673–678

Wilson JB, Krahmer RL (1976) Particleboard: microscopic observations of resin distribution and board fracture. For Prod J 26(11):42–45

Wise BM, Gallagher NB, Bro R, Shaver JM, Windig W, Koch RS (2006) Chemometrics tutorial—for PLS_Toolbox and Solo. Wenatchee, Washington

Wise BM, Gallagher NB, Bro R, Shaver JM, Windig W, Koch RS (2012) Eigenvector Documentation Wiki. Eigenvector Research, Inc., http://wiki.eigenvector.com. Accessed 8 May 2012

Wold S, Sjöström M, Eriksson L (2001) PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst 58(2):109–130

Young TM, Guess FM (2002) Mining information in automated relational databases for improving reliability in forest products manufacturing. Int J Reliab Appl 3(4):155–164

Young TM, Shaffer LB, Guess FM, Bensmail H, Leon RV (2008) A comparison of multiple linear regression and quantile regression for modeling the internal bond of medium density fiberboard. For Prod J 58(4):39–48

Zeng Y (2011) A study of missing data imputation and predictive modeling of strength properties of wood composites. University of Tennessee, Knoxville