An integrated holistic model of a complex process

Conducting experiments to understand and model a complex process or system is usually costly and time-consuming due to multistages, multivariables, and multidisciplinary issues involved in the complex process. To reduce the complexity, for a single experiment, experimenters often fix some variables and investigate the effects of a smaller subset of variables. If then, it is possible to build individual models for each subset of variables, but this only allows partial understanding of the whole process. In this paper, we propose a method for building a holistic model of a complex process using multiple partial models that are learned from multiple sub-experiments that focus on different variables or the same variables but with different variable ranges. Using the proposed holistic model, it should be possible to provide an initial understanding of the complex process involving all variables. The effectiveness of the proposed method is demonstrated using a real example from a buckypaper process.

[1]  Kwai-Sang Chin,et al.  STEP-Based Multiview Integrated Product Modelling for Concurrent Engineering , 2002 .

[2]  Ben Wang,et al.  Application of response surface methodology in the optimization of laser treatment in buckypaper lighting for field emission displays , 2013 .

[3]  Ivica Kolaric,et al.  Carbon nanotube sheets for the use as artificial muscles , 2004 .

[4]  T. Ebbesen,et al.  Exceptionally high Young's modulus observed for individual carbon nanotubes , 1996, Nature.

[5]  Xin Wang,et al.  Layers of Experiments with Adaptive Combined Design , 2015 .

[6]  Ali Aldalbahi,et al.  Electrical and mechanical characteristics of buckypapers and evaporative cast films prepared using single and multi-walled carbon nanotubes and the biopolymer carrageenan , 2012 .

[7]  Tirthankar Dasgupta,et al.  A physical–statistical model for density control of nanowires , 2011 .

[8]  W. D. de Heer,et al.  Carbon Nanotubes--the Route Toward Applications , 2002, Science.

[9]  Rong Li,et al.  Research of design and analysis integrated information modeling framework for multibody mechanical system: with its application in the LHD design , 2013 .

[10]  Chuck Zhang,et al.  Modulus prediction of buckypaper based on multi-fidelity analysis involving latent variables , 2015 .

[11]  Ben Wang,et al.  Calibration and adjustment of mechanical property prediction model for poly(vinyl alcohol)-enhanced carbon nanotube buckypaper manufacturing , 2017 .

[12]  Heeyoung Kim,et al.  Adaptive combined space-filling and D-optimal designs , 2015 .

[13]  Markus J Buehler,et al.  In silico assembly and nanomechanical characterization of carbon nanotube buckypaper , 2010, Nanotechnology.

[14]  V. R. Joseph,et al.  Statistical Adjustments to Engineering Models , 2009 .

[15]  Jye-Chyi Lu,et al.  Initial Experimental Design Methodology Incorporating Expert Conjecture, Prior Data, and Engineering Models for Deposition of Iridium Nanoparticles in Supercritical Carbon Dioxide , 2013 .

[16]  Li Wang,et al.  Cross-Domain Model Building and Validation (CDMV): A New Modeling Strategy to Reinforce Understanding of Nanomanufacturing Processes , 2013, IEEE Trans Autom. Sci. Eng..

[17]  Mei Zhang,et al.  Sign Change of Poisson's Ratio for Carbon Nanotube Sheets , 2008, Science.

[18]  Raja Ram Mohan Roy Muddada,et al.  Towards resilient supply chain networks , 2010 .

[19]  Qiang Zhang,et al.  The feasibility of producing MWCNT paper and strong MWCNT film from VACNT array , 2008 .

[20]  Douglas C. Montgomery,et al.  Introduction to Linear Regression Analysis, Solutions Manual (Wiley Series in Probability and Statistics) , 2007 .

[21]  Shreyes N. Melkote,et al.  A statistical approach to the optimization of a laser-assisted micromachining process , 2011 .

[22]  Jye-Chyi Lu,et al.  A Framework for Initial Experimental Design in the Presence of Competing Prior Knowledge , 2013 .

[23]  Ben Wang,et al.  Alignment and properties of carbon nanotube buckypaper/liquid crystalline polymer composites , 2012 .

[24]  M. R. Ghomashchi,et al.  Squeeze casting: an overview , 2000 .

[25]  Jianjun Shi,et al.  Quantitative characterization and modeling strategy of nanoparticle dispersion in polymer composites , 2012 .

[26]  D. Madigan,et al.  Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window , 1994 .

[27]  W. H. Ip,et al.  On Petri net implementation of proactive resilient holistic supply chain networks , 2013 .