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7Epsilon - World Foundry Congress 2014 presentation

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Optimise your foundry process for defect/waste reduction using 7Epsilon Continual Improvement. Use in-process data to make small adjustments to your process in order to achieve continual process improvement.
7Epsilon projects satisfy the requirements of Clause 8 of ISO 9001:2008 quality standard. 7Steps of 7Epsilon refine Six Sigma's Measure, Analyse, Improve and Control steps.

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7Epsilon - World Foundry Congress 2014 presentation

  1. 1. Dr. HMd Roshan, Maynard Steel Casting, WI, USA Cinzia Giannetti, Swansea University, UK Dr. Meghana R. Ransing, p-matrix Ltd. Dr. Rajesh S. Ransing, Swansea University, UK A 7Epsilon Continual Process Improvement Case Study for Defect Reduction and Quality Control (Official UK Exchange Paper) 71st World Foundry Congress. Bilbao 2014
  2. 2. 71st World Foundry Congress. Bilbao 2014  7Epsilon term coined by Dr. Patricia Caballero, Tecnalia Spain.  7Steps of 7Epsilon to ERADICATE defects – introduced by Dr. Rajesh Ransing, Swansea University, UK
  3. 3. 71st World Foundry Congress. Bilbao 2014 Dr. Pedro Egizabal, Tecnalia, Spain Dr. HMd Roshan, Maynard Steel, USA Dr. Meghana Ransing P-matrix Ltd, UK Dr. Conny Gustavson, Swerea Swecast, Sweden Dr. Salem Saffeidine Swerea Swecast, Sweden Prof. Natalia Sobczak Foundry Research Institute, Poland Mr. Sham Arjunwadkar Institute of Indian Foundrymen, India
  4. 4. 71st World Foundry Congress. Bilbao 2014 Acknowledgements p-matrix LtdMaynard Steel Casting, WI, USA
  5. 5. 71st World Foundry Congress. Bilbao 2014  “If TI only knew what TI knows” – Jerry Junkins, the late chairman, president and CEO of Texas Instruments  Lew Platt, chairman of Hewlett –Packard echoed with “I wish we knew what we know at HP” “If only my foundry knew what it knows …”
  6. 6.  Challenges the global foundry industry faces today  Maynard Steel Casting Case Study using 7steps of 7Epsilon  Penalty Matrix Approach for rootcause analysis  Conclusion 71st World Foundry Congress. Bilbao 2014
  7. 7.  ISO 9001:2008 or similar quality accreditation  Problem solving & continuous improvement strategies in place  E.g. Physics based simulations, best practice principles, process stability, in-process data capture 71st World Foundry Congress. Bilbao 2014
  8. 8.  ISO 9001:2008 or similar quality accreditation  Problem solving & continuous improvement strategies in place  E.g. Physics based simulations, best practice principles, process stability, in-process data capture  Assumption – Variability in ALL measurable factors is robust. It does not influence process variation 71st World Foundry Congress. Bilbao 2014
  9. 9.  ISO 9001:2008 or similar quality accreditation  Problem solving & continuous improvement strategies in place  E.g. Physics based simulations, best practice principles, process stability, in-process data capture  Assumption – Variability in ALL measurable factors is robust. It does not influence process variation  7Epsilon challenges this assumption  discovers ranges of factors within current tolerance limits that can be associated with process response variations 71st World Foundry Congress. Bilbao 2014
  10. 10.  It is a methodology of simultaneously tweaking single or multiple process parameter settings to reduce the variation in response values. 71st World Foundry Congress. Bilbao 2014 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05 0.055 0 10 20 30 40 50 60 70 Observations No. %Zirconium Top 50% Bottom 50% Mean / Median
  11. 11. 71st World Foundry Congress. Bilbao 2014
  12. 12.  Maynard Steel Casting Foundry, Wisconsin, USA  Low alloy steel foundry  Continual process improvement in melting sub-process  Discover product specific process knowledge  Find new tolerance limits for melting parameters 71st World Foundry Congress. Bilbao 2014
  13. 13.  Requirement 0% fractured surface area with conchoidal nature  Fracture tests failing in conchoidal fracture  Rock candy fracture / intergranular fracture  Chemistry within specification but considered to play a significant role in incidence of conchoidal fracture GOAL: achieve reduction of conchoidal fracture by optimizing chemistry parameters in melting sub process 71st World Foundry Congress. Bilbao 2014
  14. 14. 1. Form a project team 2. Acquire team members knowledge about  processes, their factors, responses and causal relationships 3. Gather process knowledge codified using  Process maps, SIPOC diagrams and cause and effect diagrams 71st World Foundry Congress. Bilbao 2014
  15. 15.  Process knowledge is  The understanding that Y = f(Xs)  How variability in Xs affects variability in Ys  Foundries rely on experts for process knowledge  Generic knowledge comes from experience, published literature  Foundry knowledge needs to be systematically collected, recorded for reuse  Systematic research on process factors and how they affect response with written descriptions 71st World Foundry Congress. Bilbao 2014
  16. 16.  Knowledge discovery  in-process data routinely collected as part of ISO 9001:2008 implementation  Perform rootcause analysis and discover correlations using penalty matrix approach  Prioritise patterns using p-matrix software 71st World Foundry Congress. Bilbao 2014
  17. 17. 71st World Foundry Congress. Bilbao 2014 Response (Y) fract- Surface Carb on Drop Tap Temp eratur e,F Pourin g Tempe rature, F Arg on stir, mts %C %Mn %S %P %Si %Ni %Cr %Mo %Cu %Al %Ti Mn/S Ratio %Zr %Ca %Ca/% Al ratiox1 000 0 57 3039 2840 8 0.21 1.00 0.008 0.013 0.42 1.70 1.04 0.40 0.160 0.025 0.0009 125 0.0096 0.0012 48 0 62 2965 2830 3 0.21 1.07 0.008 0.011 0.54 1.61 1.17 0.42 0.170 0.033 0.0018 134 0.0166 0.0027 82 0 73 2971 2850 8 0.21 0.96 0.01 0.012 0.54 1.68 1.11 0.42 0.149 0.04 0.0013 96 0.0224 0.0023 58 3 33 2980 2850 4 0.2 0.94 0.007 0.01 0.51 1.76 1.05 0.45 0.147 0.043 0.0015 134 0.0201 0.0024 56 0 60 2955 2820 2 0.24 1.12 0.01 0.013 0.4 1.72 1.09 0.43 0.153 0.032 0.0010 112 0.0129 0.0029 91 5 84 2905 2836 2 0.19 1 0.01 0.01 0.48 1.71 1.04 0.4 0.135 0.041 0.0153 100 0.0029 0.0030 73 5 35 3007 2846 4 0.2 0.96 0.009 0.01 0.43 1.69 1.07 0.42 0.133 0.013 0.0094 107 0.0021 0.0006 46 0 50 2988 2858 4 0.2 1.06 0.011 0.013 0.5 1.63 1.12 0.4 0.182 0.02 0.0075 96 0.0017 0.0002 10 0 61 2960 2850 4 0.19 0.9 0.009 0.01 0.37 1.64 1.02 0.41 0.146 0.022 0.0102 100 0.0025 0.0007 32 5 64 2950 2852 4 0.18 0.97 0.01 0.009 0.48 1.63 1.06 0.41 0.179 0.026 0.0136 97 0.0037 0.0035 135 15 31 2948 2850 4 0.2 1.07 0.011 0.014 0.4 1.63 1.14 0.4 0.173 0.032 0.0135 97 0.0029 0.0038 119 3 42 2983 2860 8 0.2 0.95 0.013 0.015 0.41 1.67 1.05 0.41 0.150 0.035 0.0011 73 0.0125 0.0125 357 10 51 2915 2840 3 0.23 1.07 0.01 0.013 0.38 1.65 1.11 0.4 0.139 0.028 0.0160 107 0.0027 0.0017 61 10 56 2942 2850 6 0.21 1.1 0.011 0.015 0.39 1.67 1.17 0.41 0.145 0.037 0.0134 100 0.0044 0.0024 65 5 48 2957 2860 2 0.23 0.97 0.01 0.014 0.42 1.63 1.09 0.41 0.117 0.033 0.0114 97 0.0030 0.0018 55 3 58 2990 2860 12 0.19 0.99 0.009 0.014 0.43 1.73 1.09 0.4 0.120 0.046 0.0159 110 0.0042 0.0054 117 0 20 2943 2818 4 0.24 0.95 0.008 0.011 0.6 1.64 1 0.41 0.136 0.03 0.0090 119 0.0029 0.0002 7 3 47 2966 2850 3 0.21 1.02 0.01 0.009 0.5 1.65 1.08 0.41 0.124 0.031 0.0110 102 0.0029 0.0014 45 20 45 2938 2850 4 0.21 1.01 0.013 0.013 0.5 1.63 1.08 0.41 0.119 0.049 0.0150 78 0.0036 0.0027 55 5 68 2994 2850 4 0.18 0.95 0.012 0.014 0.47 1.65 1.06 0.41 0.106 0.046 0.0149 79 0.0041 0.0022 48 0 53 2892 2832 2 0.21 0.95 0.011 0.011 0.52 1.63 0.98 0.42 0.140 0.046 0.0143 86 0.0046 0.0026 57 10 14 2978 2855 4 0.23 0.99 0.012 0.011 0.48 1.62 1.08 0.44 0.153 0.032 0.0121 83 0.0050 0.0015 47 0 72 2959 2832 4 0.19 0.97 0.009 0.009 0.35 1.64 0.97 0.43 0.171 0.041 0.0091 108 0.0022 0.0016 39 0 40 3019 2850 4 0.19 1.05 0.011 0.012 0.4 1.63 1.11 0.41 0.135 0.024 0.0055 95 0.0030 0.0007 29 5 38 2942 2861 4 0.18 1.01 0.011 0.011 0.46 1.68 1.04 0.4 0.144 0.033 0.0109 92 0.0033 0.0019 58 10 26 2925 2875 2 0.21 1 0.01 0.011 0.48 1.6 1.09 0.41 0.140 0.035 0.0134 100 0.0038 0.0036 103 15 47 3028 2865 2 0.18 0.93 0.011 0.015 0.44 1.64 1.06 0.4 0.160 0.027 0.0121 85 0.0029 0.0013 48 30 13 3034 2850 15 0.22 0.93 0.012 0.015 0.41 1.68 1.01 0.43 0.149 0.018 0.0058 78 0.0015 0.0008 44 5 40 2913 2850 2 0.17 0.93 0.009 0.015 0.42 1.66 1.01 0.41 0.145 0.039 0.0125 103 0.0032 0.0037 95 20 58 2940 2855 6 0.2 1.02 0.011 0.014 0.48 1.63 1.12 0.41 0.153 0.034 0.0142 93 0.0030 0.0023 68 0 30 3020 2850 6 0.19 1.04 0.01 0.013 0.46 1.6 1.04 0.41 0.146 0.037 0.0135 104 0.0044 0.0023 62 10 39 2993 2850 5 0.22 0.96 0.01 0.013 0.41 1.67 1.02 0.41 0.117 0.039 0.0153 96 0.0039 0.0045 115 5 49 2944 2850 3 0.18 1.03 0.013 0.013 0.39 1.69 1.01 0.42 0.164 0.026 0.0090 79 0.0029 0.0003 12 3 37 3045 2870 12 0.23 1.18 0.013 0.015 0.52 1.64 1.13 0.42 0.127 0.029 0.0097 91 0.0032 0.0032 110 5 46 2933 2850 6 0.19 0.92 0.012 0.011 0.46 1.68 1.08 0.42 0.110 0.033 0.0109 77 0.0034 0.0024 73 Factors (X)
  18. 18.  Penalise variability in one or more process response values  0% given 0 penalty  10% and above given 100 penalty  Linear scaling for intermediate values 71st World Foundry Congress. Bilbao 2014 100 Penalty Values 0 Penalty Values Response Scatter Diagram Response Bubble Diagram
  19. 19. 71st World Foundry Congress. Bilbao 2014 Main Effects Bubble DiagramMain Effects Scatter Diagram Bottom 50%  Bubbles with smaller diameter correspond to 0 penalty (optimal)  Bubbles with bigger diameter correspond to 100 penalty (avoid)
  20. 20. 71st World Foundry Congress. Bilbao 2014 Penalty Matrix Main Effects Bubble Diagram
  21. 21. 71st World Foundry Congress. Bilbao 2014 Interactions Bubble Diagram Penalty Matrix Main Effects Bubble Diagram
  22. 22. 71st World Foundry Congress. Bilbao 2014  p-matrix analyses hundreds and thousands of penalty matrices among factors  Classifies factor settings as Optimal, Avoid or No Effect  Ranks them in order of importance  At end of analysis, a process engineer would get a list of top 15-20 matrices he/she needs to look at  Analyses discrete and continuous parameters together in one analysis  Up to 200 factors and 40 responses can be analysed at once.
  23. 23. 71st World Foundry Congress. Bilbao 2014  Findings need to be used as pointers for discussion  p-matrix discovers correlations based on data collected  Correlation does not mean Causation  Domain knowledge necessary to interpret results  Hidden causes may be found which require further investigation
  24. 24. 71st World Foundry Congress. Bilbao 2014  Knowledge Discovery and Reuse  Analyse p-matrix reports  Hypotheses on causation are established using knowledge acquired in Step 2  Hypotheses are potential solutions  New tolerance limits proposed and  corrective action plan is outlined or collect more in-process data or conduct one or more design of experiments
  25. 25. 71st World Foundry Congress. Bilbao 2014  Confirmation trials are carried out to validate the hypotheses and create new product specific process knowledge  Optimal ranges for all the process variables (X) are determined  New product specific process knowledge is created in the form of  list of values with their new specification ranges
  26. 26. 71st World Foundry Congress. Bilbao 2014 Sub-Process Process Variable (CTQ) New tolerance limits Frequency of data collection Melting and Pouring Carbon Drop (X1) 47-84 Every Heat Melting and Pouring % Sulfur (X7) 0.007-0.009 Every Heat Melting and Pouring %Titanium (X15) 0.0009-0.011 Every Heat Melting and Pouring Mn/S Ratio (X16) 104-134 Every Heat Melting and Pouring %Ca/%Al Ratiox1000 (X19) 6.67-57.5 Every Heat
  27. 27. 71st World Foundry Congress. Bilbao 2014  New knowledge obtained stored in knowledge repository in tabular form  This is specific for a given part and process  The new knowledge acquired contributes to devise preventive and corrective action plans to achieve desired response as required by ISO 9001:2008 standard
  28. 28. 71st World Foundry Congress. Bilbao 2014  Continually monitor performance so that continual improvement on the processes can be made to meet the requirement of ISO 9001:2008.  The foundry specific 7Epsilon process knowledge repository can also be used to train operators and process engineers. 7 Epsilon Knowledge repository
  29. 29. 71st World Foundry Congress. Bilbao 2014  7 Epsilon steps  Tolerance limit optimisation to reduce defects  Penalty matrix visualization to verify evidence in data  Establish causation using domain knowledge  Design corrective actions plan  Validate by implementing on shop floor  Update process knowledge, retain and reuse
  30. 30. 71st World Foundry Congress. Bilbao 2014  Visit the 7Epsilon website at www.7epsilon.org  One day training courses hosted by  Institute of Cast Metals Engineers, ICME, UK on 16th September 2014  On Demand Online course with American Foundrymen Society, AFS - by Dr. HMd Roshan, course instructor  Join Webinar with Dr. Meghana Ransing, p-matrix Ltd.  Write to info@p-matrix.com to book your next course

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