Enhancing the Structural Strength of an ODD Laptop via Six Sigma Approach

The conventional design of notebook PCs configured with an optical disk drive suffers from structural durability problems that are indicative of potentially high defect rates. Companies have been attempting to reduce the size of assembly parts to pursue compactness, but the elimination of these mate...

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Bibliographic Details
Published in:IEEE transactions on components, packaging, and manufacturing technology (2011) packaging, and manufacturing technology (2011), 2019-11, Vol.9 (11), p.2200-2209
Main Authors: Su, Chao-Ton, Su, Feng-Min, Chen, Tzu-Yu, Chen, Li-Fei
Format: Article
Language:English
Subjects:
Artificial intelligence
Compressive strength
Disk drives
Genetic algorithms
Genetic algorithms (GAs)
Neural networks
neural networks (NNs)
optical disk drive (ODD)
Optimization
Optimization techniques
Phase measurement
Redesign
response surface method (RSM)
Response surface methodology
Six Sigma
Structural stability
Structural strength
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Summary:The conventional design of notebook PCs configured with an optical disk drive suffers from structural durability problems that are indicative of potentially high defect rates. Companies have been attempting to reduce the size of assembly parts to pursue compactness, but the elimination of these materials might negatively affect structural stability, which is fundamentally important to all high-technology products. The Six Sigma methodology applied in this paper aims to improve quality performance and eliminate redesign waste and unnecessary handoffs according to customer requirements. This paper presents a case study using the define, measure, analyze, improve, and control (DMAIC) procedure. Several optimization techniques, such as response surface method (RSM) and computational intelligence, are adopted to optimize the significant factors that affect the module design and structural strength index during compression. Implementation results demonstrate that computational intelligence outperforms RSM. It shows computational intelligence reveals a good ability to solve the parameter optimization problems.
ISSN:2156-3950
2156-3985
DOI:10.1109/TCPMT.2019.2922728