Dual response surface optimization with hard‐to‐control variables for sustainable gasifier performance

Dual response surface optimization of the Sasol-Lurgi fixed bed dry bottom gasification process was carried out by performing response surface modelling and robustness studies on the process variables of interest from a specially equipped full-scale test gasifier. Coal particle size distribution and coal composition are considered as hard-to-control variables during normal operation. The paper discusses the application of statistical robustness studies as a method for determining the optimal settings of process variables that might be hard to control during normal operation. Several dual response surface strategies are evaluated for determining the optimal process variable conditions. It is shown that a narrower particle size distribution is optimal for maximizing gasification performance which is robust against the variability in coal composition. Copyright Journal compilation (c) 2008 Royal Statistical Society.

[1]  Robert Tibshirani,et al.  An Introduction to the Bootstrap , 1994 .

[2]  J. Cornell.  Experiments with Mixtures: Designs, Models and the Analysis of Mixture Data , 1982 .

[3]  C. Viljoen,et al.  The estimation of knock-points of fuels by a weighted mean square error criterion , 2006 .

[4]  Shaun S. Wulff,et al.  RESPONSE SURFACE APPROACHES TO ROBUST PARAMETER DESIGN , 2006 .

[5]  Dennis K. J. Lin,et al.  Optimization of multiple responses considering both location and dispersion effects , 2006, Eur. J. Oper. Res..

[6]  Dennis K. J. Lin,et al.  Dual Response Surface Optimization: A Fuzzy Modeling Approach , 1998 .

[7]  G. Derringer,et al.  Simultaneous Optimization of Several Response Variables , 1980 .

[8]  James M. Lucas,et al.  How to Achieve a Robust Process Using Response Surface Methodology , 1994 .

[9]  R. H. Myers,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[10]  R. Coetzer,et al.  Robustness studies on coal gasification process variables , 2004 .

[11]  R. H. Myers,et al.  Response Surface Alternatives to the Taguchi Robust Parameter Design Approach , 1992 .

[12]  Loon Ching Tang,et al.  A unified approach for dual response surface optimization , 2002 .

[13]  Dennis K. J. Lin,et al.  Dual-Response Surface Optimization: A Weighted MSE Approach , 2004 .

[14]  Douglas C. Montgomery,et al.  Experimental Design for Product and Process Design and Development , 1999 .

[15]  G. Geoffrey Vining,et al.  Combining Taguchi and Response Surface Philosophies: A Dual Response Approach , 1990 .

[16]  M. J. Keyser,et al.  Experimental design and statistical evaluation of a full-scale gasification project , 2003 .

[17]  Wanzhu Tu,et al.  Dual response surface optimization , 1995 .

[18]  P. Rosin.  The Laws Governing the Fineness of Powdered Coal , 1933 .

[19]  Raymond H. Myers,et al.  Response surface methodology in quality improvement , 1991 .

[20]  M. Keyser,et al.  Robustness studies on coal gasification process variables RLJ , 2004 .

[21]  Douglas C. Montgomery,et al.  A Nonlinear Programming Solution to the Dual Response Problem , 1993 .