Taguchi method-process imp
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1. Taguchi methods focus on designing quality into products from the beginning rather than inspecting it in later. 2. Quality is measured by how much a product deviates from its target specifications, with the goal of minimizing deviation. Losses are calculated based on functional variation and harm. 3. The cost of quality problems should be measured as a function of deviation from standards across the whole system.
![Average quality loss
Q = k [( m - )2 + 2 ]
It consists of two components:
•Shift of process average ( ) from the
target value (m)
•Spread of the process ( 2)
S/N ratios are a log-modified form of
Average quality loss function](https://image.slidesharecdn.com/taguchi-method-processimp-140304024108-phpapp02/85/Taguchi-method-process-imp-6-320.jpg)
Taguchi method-process imp
- 1. By Genichi Taguchi in Japan in 1950’s 80% of the quality gains of Japan International Acceptance
- 2. Quality means different things to different people Following Taguchi, the quality of a product is measured in terms of the total loss to society due to functional variation and harmful effects. The loss would be zero for the ideal quality.
- 4. After process improvement and shifting the mean. Initial distribution m m m Resistance ( Ohms / Kilometre) Distribution of telephone cable resistance.
- 6. Average quality loss Q = k [( m - )2 + 2 ] It consists of two components: •Shift of process average ( ) from the target value (m) •Spread of the process ( 2) S/N ratios are a log-modified form of Average quality loss function
- 7. 1. 2. 3. Quality should be designed into the product and not inspected into it. Quality is best achieved by minimizing the deviation from a target. The product should be so designed that it is immune to uncontrollable environmental factors. The cost of quality should be measured as a function of deviation from the standard and the losses should be measured system-wide.
- 8. S/N ratio Maximizing S/N ratio is equivalent to reducing variance due to various noise factors and hence improves quality during manufacturing, customer usage and aging and simultaneously reducing cost substantially.
- 9. Identify various causes, known as noise factors, that degrade the product (process) performance variations in raw materials and components, machinery, workmanship, temperature, humidity, loading, etc. Eliminate the noise factors one by one
- 10. Eliminating noise factors always leads to increased costs Reduction in profitability or loss of market share in the face of global competition
- 11. New method of design optimization for performance, quality, & cost For existing processes, emphasis is on parameter design Smallest, affordable development cost
- 12. All engineering designs involve setting values of a large number of decision variables. Common approach is to study one variable at a time or by trial and error Either long and expensive time span for completing the design / premature termination of the design process
- 13. MATHEMATICAL Orthogonal arrays to study large number of decision variables with a small number of experiments NEW TOOL MEASURE OF QUALITY Signal to noise (s/n) ratio to predict the quality from the customer perspective
- 14. 1. To establish the best or the optimum condition for a product or a process. 2. To estimate the contribution of individual factors. 3. To estimate the response under the optimum conditions.
- 15. X NOISE FACTORS M Y SIGNAL FACTORS RESPONSE A1 A2 CONTROL Z FACTORS BLOCK DIAGRAM OF A PRODUCT/ PROCESS
- 16. Size
- 17. Many cos. Big or small, high-tech and lowtech have found the method valuable High quality at a low competitive price while maintaining profit margin
- 18. Upfront improvement of quality by design and process development. Measurement of quality in terms of deviation from the target (loss function). Problem solution by team approach and brainstorming.
- 19. Consistency in experimental design and analysis. Reduction of time and cost of experiments. Design of robustness into product/process. Reduction of variation without removing its causes. Reduction of product warranty and service costs by addressing them with the loss function.