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International Society of Science and Applied Technologies |
| Quality Evaluation and Smart Decision-Making Improvement Model for Mobile Assistive Devices | ||||
| Author | Kuen-Suan Chen
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| Co-Author(s) | Chun-Min Yu; Shui-Chuan Chen
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| Abstract | In the face of market competition in mainland China and Southeast Asia, Taiwan's manual wheelchair, are bound to develop into high-tech threshold and high-profit products. It is a relatively important topic to develop high-end composite materials and improve the process quality level of manual wheelchair products. Especially with the gradual maturity of the Internet of Things environment, the collection and analysis technology of production data is continuously improved, and the improvement of product process quality and safety performance can not only increase product value, but also prolong product life, and achieve the goal of energy-saving and waste-reducing green production. Therefore, this study use process capability indicators of important quality characteristics as evaluation tools for the manual wheelchair products. In addition, taking the carbon fiber wheel rims as an important component of manual wheelchairs as an example, an intelligent analysis, evaluation and improvement model of production data was proposed. First, we constructed the evaluation index of the important quality characteristics of the carbon fiber wheel rims to verify that each important quality characteristic can meet the requirements of the quality level. Then, based on the upper confidence limit of the evaluation index, the fuzzy decision index and fuzzy testing rules are established. In addition, the decision-making index is converted into the index observation value, and an intuitive fuzzy evaluation rule that is more convenient for practical application is established. Finally, we use an easy-to-use radar evaluation chart to assess whether the index falls into the improvement range and decide whether to improve. In conclusion, this study considers the need of businesses for quick response to facilitate various decisionmaking. Fuzz test design based on upper confidence bounds can incorporate past data experience. It can still maintain the accuracy of small sample size testing. At the same time, it can also help enterprises pursue the pace of intelligent manufacturing and management, and realize the business philosophy of sustainable development.
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| Keywords | Confidence interval; fuzzy testing, smart manufacturing and management; mobile assistive devices; radar evaluation chart | |||
| Article #: RQD28-205 | ||||
Proceedings of 28th ISSAT International Conference on Reliability & Quality in Design |