Bayesian cross-product quality control via transfer learning

Quality control is essential for modern business success. The traditional statistical process control (SPC), however, lacks efficacy in current high-variety low-volume industrial practices since th...

[1]  Ronald J. M. M. Does,et al.  Guaranteed In-Control Performance for the Shewhart X and X Control Charts , 2017 .

[2]  William H. Woodall,et al.  The Difficulty in Designing Shewhart X̄ and X Control Charts with Estimated Parameters , 2015 .

[3]  Satish T. S. Bukkapatnam,et al.  The internet of things for smart manufacturing: A review , 2019, IISE Trans..

[4]  Ronald J. M. M. Does,et al.  The effect of continuously updating control chart limits on control chart performance , 2019, Qual. Reliab. Eng. Int..

[5]  Qingyu Yang,et al.  A new Bayesian scheme for self-starting process mean monitoring , 2020 .

[6]  Andrew Y. C. Nee,et al.  Digital twin-driven product design framework , 2019, Int. J. Prod. Res..

[7]  Sajid Ali,et al.  A predictive Bayesian approach to sequential time‐between‐events monitoring , 2019, Qual. Reliab. Eng. Int..

[8]  Marko Robnik-Sikonja Data Generators for Learning Systems Based on RBF Networks , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[9]  Charles P. Quesenberry,et al.  DPV Q charts for start-up processes and short or long runs , 1991 .

[10]  Andrew Kusiak,et al.  From data to big data in production research: the past and future trends , 2019, Int. J. Prod. Res..

[11]  Ronald J. M. M. Does,et al.  Correction factors for Shewhart and control charts to achieve desired unconditional ARL , 2016 .

[12]  Furong Gao,et al.  Process similarity and developing new process models through migration , 2009 .

[13]  Der-Chiang Li,et al.  A genetic algorithm-based virtual sample generation technique to improve small data set learning , 2014, Neurocomputing.

[14]  Alireza Faraz,et al.  An exact method for designing Shewhart and S2 control charts to guarantee in-control performance , 2018, Int. J. Prod. Res..

[15]  Daniel W. Apley,et al.  Posterior Distribution Charts: A Bayesian Approach for Graphically Exploring a Process Mean , 2012, Technometrics.

[16]  Jean-Yves Tourneret,et al.  Change Detection in Multisensor SAR Images Using Bivariate Gamma Distributions , 2008, IEEE Transactions on Image Processing.

[17]  Angappa Gunasekaran,et al.  Big data in lean six sigma: a review and further research directions , 2019, Int. J. Prod. Res..

[18]  Der-Chiang Li,et al.  Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge , 2007, Comput. Oper. Res..

[19]  Axel Gandy,et al.  Guaranteed Conditional Performance of Control Charts via Bootstrap Methods , 2011, 1111.4180.

[20]  Ulrich Menzefricke,et al.  ON THE EVALUATION OF CONTROL CHART LIMITS BASED ON PREDICTIVE DISTRIBUTIONS , 2002 .

[21]  Huaguang Zhang,et al.  A Small-Sample Wind Turbine Fault Detection Method With Synthetic Fault Data Using Generative Adversarial Nets , 2019, IEEE Transactions on Industrial Informatics.

[22]  Steven X. Ding,et al.  A Review on Basic Data-Driven Approaches for Industrial Process Monitoring , 2014, IEEE Transactions on Industrial Electronics.

[23]  Sofia Panagiotidou,et al.  A sequential monitoring Bayesian control scheme for attributes , 2018, Quality Technology & Quantitative Management.

[24]  Tomaso Poggio,et al.  Incorporating prior information in machine learning by creating virtual examples , 1998, Proc. IEEE.

[25]  Wilbert C.M. Kallenberg,et al.  Estimation in Shewhart control charts: effects and corrections , 2004 .

[26]  Charles W. Champ,et al.  Effects of Parameter Estimation on Control Chart Properties: A Literature Review , 2006 .

[27]  William H. Woodall,et al.  Another Look at the EWMA Control Chart with Estimated Parameters , 2015 .

[28]  Douglas C. Montgomery,et al.  Some Current Directions in the Theory and Application of Statistical Process Monitoring , 2014 .

[29]  Philippe Castagliola,et al.  Some Recent Developments on the Effects of Parameter Estimation on Control Charts , 2014, Qual. Reliab. Eng. Int..

[30]  Jean-Yves Tourneret,et al.  Bivariate Gamma Distributions for Image Registration and Change Detection , 2007, IEEE Transactions on Image Processing.

[31]  Ke Zhang,et al.  Statistical transfer learning: A review and some extensions to statistical process control , 2018 .

[32]  Anis Chelbi,et al.  Integrated production, statistical process control, and maintenance policy for unreliable manufacturing systems , 2018, Int. J. Prod. Res..

[33]  Zhibin Jiang,et al.  A conjugate Bayesian approach to control chart for multi-batch and low volume production , 2015 .

[34]  Zhonghua Li,et al.  Self-starting control chart for simultaneously monitoring process mean and variance , 2010 .

[35]  Philippe Bernardoff,et al.  Which multivariate gamma distributions are infinitely divisible , 2006 .

[36]  Nan-Jung Hsu,et al.  Joint modeling of laboratory and field data with application to warranty prediction for highly reliable products , 2016 .

[37]  Jieping Ye,et al.  A transfer learning approach for network modeling , 2012, IIE transactions : industrial engineering research & development.

[38]  Douglas M. Hawkins,et al.  A Bayesian Scheme to Detect Changes in the Mean of a Short-Run Process , 2005, Technometrics.

[39]  Claudio Moraga,et al.  A diffusion-neural-network for learning from small samples , 2004, Int. J. Approx. Reason..

[40]  Der-Chiang Li,et al.  Using past manufacturing experience to assist building the yield forecast model for new manufacturing processes , 2012, J. Intell. Manuf..

[41]  Douglas C. Montgomery,et al.  A review of statistical process control techniques for short run manufacturing systems , 1996 .

[42]  Stefan H. Steiner,et al.  An Overview of Phase I Analysis for Process Improvement and Monitoring , 2014 .