| Summary: | 碩士 === 元智大學 === 工業工程與管理學系 === 102 === Driven by reducing greenhouse effect and carbon dioxide emission, as well as the growing population of riding bicycles for traveling around suburban and countryside areas, the market of electric bikes (E-bikes) is rapidly expanding nowadays. A recent survey indicates that the global sales volume of E-bikes increases from 38,000,000 to 43,000,000 during the years of 2011 to 2013. The trend will continue, and is expected to be 58,000,000 in 2019. The business benefits of the E-bike products have attracted numerous industrial organizations to consider joining this market. This thesis aims to investigate in depth whether a worldwide famous notebook manufacturer should develop novel E-bike batteries and share the potentially remarkable market profit. The case company itself has a plentiful experience and technology in manufacturing batteries for electronic equipment.
The research presents a three-phase decision-making approach integrating quality function deployment (QFD) with several MCDM mechanisms such as fuzzy Delphi, gray relational analysis (GRA), and TOPSIS, to produce analyzing results for the case company to make a selection. In phase 1, a preliminary decision framework based on literature review and experts’ opinions was established, essential criteria using the max-min fuzzy Delphi method was screened and obtained, and the decision framework was finalized. In phase 2, HOQ (house of quality) was applied for aggregation of experts’ opinions to build the relationships between WHATs (criteria of customer needs) and HOWs (criteria of technical aspects). The criteria weights of technical aspects can then be calculated. The results indicate that the company should focus most on product safety and product life cycle when designing and producing the new battery. Finally, in phase 3, the TOPIS and the GRA were respectively employed to assess the performance of the proposed three alternatives for each technological criterion, and the total weighted scores of the three alternatives were aggregated. The outcome shows that both methods achieve the same alternative ranking: plan C (Polymer Li-ion battery with 36 volts), plan A (Cylindrical Li-ion battery with 36 volts), and plan B (Cylindrical Li-ion battery with 24 volts).
Keywords: Battery module, electric bike, quality function deployment, multiple criteria decision making, fuzzy Delphi, TOPSIS, gray relation analysis
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