Abstract
This article addresses an approach based on Taguchi method for optimising the ingredients of green sand in a foundry. Permeability and compression strength were the important characteristics of green sand. Optimisation of these characteristics was done through the application of Taguchi method of experimentation. Three factors were identified and experimented in an L9(34) orthogonal array. Signal-to-noise ratio method was used to analyse the data and the best levels for these factors were selected. As a result of the experimentation, in addition to the identification of optimum levels for the ingredients, the proportion of Bentonite and coal dust were reduced considerably. This was leading to a large financial benefit for the company.
Keywords
References
- 1. (2010). ‘Quality engineering of a traction alternator by robust design’. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 223, 2, 297-304 Google Scholar
- 2. (2005). ‘Building the foundation for green sand’. Modern Casting. 95, 8, 26-29 Google Scholar
- 3. (1989). Taguchi Methods: Applications in World Industry. UK:IFS Publications Google Scholar
- 4. (1992). ‘Split-plot designs for robust product experimentation’. Journal of Applied Statistics. 19, 1, 3-25 Google Scholar
- 5. (1988). ‘An explanation and critique of Taguchi’s contributions to quality engineering’. Quality and Reliability Engineering International. 4, 2, 123-131 Google Scholar
- 6. (2000). ‘Quality improvement through design of experiments: a case study’. Quality Engineering. 12, 3, 407-416 Google Scholar
- 7. (2005). ‘Improving process capability of manufacturing process by application of statistical techniques’. Quality Engineering. 17, 2, 309-315 Google Scholar
- 8. (2003). ‘Quality improvement by reducing variation: a case study’. Total Quality Management & Business Excellence. 14, 9, 1023-1031 Google Scholar
- 9. (2008). ‘Quality in the construction industry: an application of DOE with goal programming’. Total Quality Management & Business Excellence. 19, 12, 1249-1255 Google Scholar
- 10. (1995). ‘A review of robust process design approaches’. Journal of Chemometrics. 9, 4, 239-262 Google Scholar
- 11. (2010). ‘Reducing variation in an existing process with robust parameter design’. Quality Engineering. 22, 1, 30-45 Google Scholar
- 12. (2009). ‘Design and analysis of computer experiments with branching and nested factors’. Technometrics. 51, 4, 354-365 Google Scholar
- 13. (1985). ‘Statistical design applied to product design’. Journal of Quality Technology. 17, 4, 210-221 Google Scholar
- 14. (1985). ‘Off-line quality control, parameter design, and the Taguchi method (with discussion)’. Journal of Quality Technology. 17, 4, 176-188 Google Scholar
- 15. (1987). ‘Performance measures independent of adjustment’. Technometrics. 29, 3, 253-285 Google Scholar
- 16. (1994). ‘How to achieve a robust process using response surface methodology’. Journal of Quality Technology. 26, 4, 248-260 Google Scholar
- 17. (1991). Design and Analysis of Experiments. 3rd ed., New York:John Wiley & Sons Google Scholar
- 18. (1992). ‘Taguchi’s parameter design: a panel discussion’. Technometrics. 34, 2, 127-161 Google Scholar
- 19. (1996). Robust Design and Analysis for Quality Engineering. London:Chapman & Hall Google Scholar
- 20. (1989). Quality Engineering using Robust Design. Englewood Cliffs, NJ:Prentice-Hall Google Scholar
- 21. (1991). ‘Top ten triumphs and tragedies of Genichi Taguchi’. Quality Engineering. 4, 2, 211-225 Google Scholar
- 22. (1947).
‘Factorial experiments derivable from combinatorial arrangements of arrays’.
Journal of Royal Statistical Society.
9,
128-139,
Series B Google Scholar - 23. (1996). Taguchi Techniques for Quality Engineering. New York:McGraw-Hill Google Scholar
- 24. (1988). ‘Better than Taguchi orthogonal tables’. Quality and Reliability Engineering International. 4, 2, 143-149 Google Scholar
- 25. (1991). ‘Economical experimentation methods for robust design’. Technometrics. 33, 4, 415-427 Google Scholar
- 26. (1998). ‘Noise factors, dispersion effects, and robust design’. Statistica Sinica. 8, 67-85 Google Scholar
- 27. (1986). Introduction to Quality Engineering – Designing Quality into Products and Processes. Tokyo:Asian Productivity Organization Google Scholar
- 28. (1988). System of Experimental Design, Volume 1 and 2. New York:UNIPUB and American Supplier Institute Google Scholar
- 29. (1979). Introduction to Off-Line Quality Control. Nagoya, Japan:Central Japan Quality Control Association Google Scholar
- 30. (2000). Robust Engineering – Learn How to Boost Quality While Reducing Costs and Time to Market. New York:McGraw-Hill Google Scholar
- 31. (1989). ‘An alternative view of the Taguchi approach’. Quality Progress. 22, 5, 46-52 Google Scholar
- 32. (2009). ‘Planning experiments, the first real task in reaching a goal’. Quality Engineering. 21, 1, 44-51 Google Scholar
- 33. (1990). ‘Computer experiments for quality control by parameter design’. Journal of Quality Technology. 22, 1, 15-22 Google Scholar
- 34. (2010). ‘Uncertainty in designed experiments’. Quality Engineering. 22, 2, 88-102 Google Scholar
- 35. (2000). Experiments – Planning, Analysis, and Parameter Design Optimization. New York:Wiley Google Scholar
- 36. (2000). Taguchi Methods for Robust Design. New York:The American Society of Mechanical Engineers Google Scholar
- 37. (2009). ‘Optimizing, tape-burnishing/wiping process of magnetic recording media through Taguchi method’. Quality and Reliability Engineering International. 25, 3, 345-354 Google Scholar