Simultaneous optimization of multiple response variables using desirability function
In today’s world, quality has been the key issue to the success of many multinational organizations. They also perceived quality as a “competitive weapon”, and assumed it as part and parcel of long-term strategic planning. Response optimization is the target of much design of experiments which is on...
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2018
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| Online Access: | http://irep.iium.edu.my/67044/ http://irep.iium.edu.my/67044/ http://irep.iium.edu.my/67044/1/67044_Simultaneous%20Optimization%20of%20Multiple%20-%20edited.pdf |
| Summary: | In today’s world, quality has been the key issue to the success of many multinational organizations. They also perceived quality as a “competitive weapon”, and assumed it as part and parcel of long-term strategic planning. Response optimization is the target of much design of experiments which is one of the extremely essential tools in quality engineering. In the multiple response case, finding process operating conditions that simultaneously maximize all the responses is quite difficult or impossible. Desirability function technique is the most popular methods for the multiple responses optimization problem. This paper presents a robust desirability function for the multiple response robust optimizations, effective ways to make the trade-off. The aim of optimizing a multi-response is to find a setting combination of input controllable factors that would result in optimum values of all response variables at all signal levels affecting quality product. Here, the process parameters (inputs) were tool material, grit size and power rating of ultrasonic horn. Also, the main responses which should be simultaneously optimized were strength, weight, pinholes and thickness. Firstly, numbers of 24 experiments were conducted to collect data according to fractional factorial design. The obtained data were used to develop mapping relationship between inputs and responses using the composite desirability function (CDF). |
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