Integrating the TRIZ and Taguchi's Method in the Optimization of Processes Parameters for SMT

SMT is an assembly technology for core circuit board parts. Unless process parameters are effectively controlled, poor solderability may result in a decline in product quality. This study looks at an SMT manufacturing process in a multinational company. First, the TRIZ contradiction matrix is revised to investigate the association between the 39 parameters in the contradiction matrix and 13 parameters that influence the unevenness of solder paste in the solder paste printing process. Expert verification is then used to screen the key factors affecting the quality of SMT, which are then combined with Taguchi's method to identify the optimal parameter set influencing the thickness of SMT solder paste. Results. TRIZ identifies squeegee pressure, ejection speed, squeegee speed, and squeegee angle as the four parameters with the greatest influence on SMT solder paste thickness. Taguchi's method is used to identify the optimum levels set for the experimental factors and carry out confirmation experiments. The S/N ratio improved from 21.732 db to 26.632 db, while the mean also improved from the current 0.163 mm to 0.155 mm, close to the target value of 0.15 mm. The results show that applying TRIZ and Taguchi's method for the purpose of product improvement is feasible.

[1]  Wolfgang W. Osterhage,et al.  IT Quality Management , 2015, HMD Praxis der Wirtschaftsinformatik.

[2]  W. Marsden.  I and J , 2012 .

[3]  Manabu Sawaguchi.  A study of systematic innovation based on an analysis of “Big Hits” , 2011 .

[4]  Chien-Wen Hong,et al.  Using the Taguchi method for effective market segmentation , 2012, Expert Syst. Appl..

[5]  Kiran Solanki,et al.  Multi-objective optimization of vehicle crashworthiness using a new particle swarm based approach , 2012 .

[6]  A. R. Zinsmeister,et al.  Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building, by G. E. P. Box, W. G. Hunter, and J. S. Hunter , 1981 .

[7]  Han Tong Loh,et al.  Automatic classification of patent documents for TRIZ users , 2006 .

[8]  G. S. Altshuller,et al.  40 principles : TRIZ keys to innovation / by GenrichAltshuller , 2005 .

[9]  Ali Riza Yildiz,et al.  A new design optimization framework based on immune algorithm and Taguchi's method , 2009, Comput. Ind..

[10]  Ali R. Yildiz,et al.  Optimization of cutting parameters in multi-pass turning using artificial bee colony-based approach , 2013, Inf. Sci..

[11]  Bjørn Andersen,et al.  Root Cause Analysis: Simplified Tools and Techniques , 1999 .

[12]  L. N. Harris,et al.  Taguchi techniques for quality engineering, Philip J. Ross, Mcgraw-hill book company, 1988 , 1989 .

[13]  Chao-Ton Su,et al.  Optimization of the Cu wire bonding process for IC assembly using Taguchi methods , 2011, Microelectron. Reliab..

[14]  Kazuhiro Saitou,et al.  Topology Synthesis of Multicomponent Structural Assemblies in Continuum Domains , 2011 .

[15]  Altshuller.  Creativity As an Exact Science , 1984 .

[16]  Yi-Shao Lai,et al.  Optimal design towards enhancement of board-level thermomechanical reliability of wafer-level chip-scale packages , 2007, Microelectron. Reliab..

[17]  Taho Yang,et al.  A neural network-based prediction model for fine pitch stencil-printing quality in surface mount assembly , 2005, Eng. Appl. Artif. Intell..

[18]  J. S. Hunter,et al.  Statistics for experimenters : an introduction to design, data analysis, and model building , 1979 .

[19]  Genichi Taguchi,et al.  Taguchi's Quality Engineering Handbook , 2004 .

[20]  Ali R. Yildiz,et al.  Hybrid Taguchi-Harmony Search Algorithm for Solving Engineering Optimization Problems , 2008 .

[21]  Ali R. Yildiz,et al.  Comparison of evolutionary-based optimization algorithms for structural design optimization , 2013, Eng. Appl. Artif. Intell..

[22]  Tim Stapenhurst,et al.  Taguchi Methods , 1990 .

[23]  James R. Evans,et al.  The management and control of quality , 1989 .

[24]  Stanley B. Davis,et al.  Quality Management , 2005 .

[25]  İsmail Durgun,et al.  Structural Design Optimization of Vehicle Components Using Cuckoo Search Algorithm , 2012 .

[26]  A.B. Dumont,et al.  Quality in Engineering , 1950, Proceedings of the IRE.

[27]  Ali R. Yildiz,et al.  A new hybrid particle swarm optimization approach for structural design optimization in the automotive industry , 2012 .

[28]  Ali R. Yildiz,et al.  A new hybrid artificial bee colony algorithm for robust optimal design and manufacturing , 2013, Appl. Soft Comput..

[29]  Ali R. Yildiz,et al.  Hybrid Taguchi-differential evolution algorithm for optimization of multi-pass turning operations , 2013, Appl. Soft Comput..

[30]  G. S. Alʹtshuller,et al.  40 Principles: TRIZ Keys to Technical Innovation , 1998 .

[31]  T. R. Bement,et al.  Taguchi techniques for quality engineering , 1995 .

[32]  Messias Borges Silva,et al.  Molecular assay optimized by Taguchi experimental design method for venous thromboembolism investigation. , 2011, Molecular and cellular probes.

[33]  Chun-Chin Hsu,et al.  Optimization of the Optical Whiteness Ratio for Flexible Display by Using Taguchi's Dynamic Approach , 2012, IEEE Transactions on Semiconductor Manufacturing.

[34]  Wen-Pai Wang,et al.  Evaluating new product development performance by fuzzy linguistic computing , 2009, Expert Syst. Appl..

[35]  Tsung-Nan Tsai,et al.  Modeling and optimization of stencil printing operations: A comparison study , 2008, Comput. Ind. Eng..

[36]  Yi-Wei Lin,et al.  OPTIMIZATION OF THE EXTRUSION PROCESS FOR MAGNESIUM ALLOY SHEETS USING THE FUZZY- BASED TAGUCHI METHOD , 2009 .

[37]  Victor E. Kane,et al.  Process Capability Indices , 1986 .

[38]  Julie Z. Zhang,et al.  Surface roughness optimization in an end-milling operation using the Taguchi design method , 2007 .