| Summary: | 碩士 === 國立臺北科技大學 === 工業工程與管理系EMBA班 === 96 === Addressing the feature of small and medium-sized enterprises, the important factors that make them different from big-sized enterprises are their flexibility and quick responsive to the market’s need. In the production and marketing of dental equipments, those factors are still the unchangeable principles; and since most of the dental equipments suppliers are small and medium-sized enterprises, these factors become the truth. Additionally, the market of dental equipment is bound to time limitations, which reflects current customized consuming style. Therefore, service that able to provide quick estimation and specification becomes especially important.
Due to the fact that dental clinic is affected by the consuming behaviour, which recently tends to become M-style, the need of dental equipment changed from focusing on quantity and specification to customized design, which intends to suit the dental clinics’ style and orientation. Thus, the traditional way of providing quotation can no longer satisfy the need of current market. In order to increase the competiveness and respond to market’s needs, enterprises that manufacture dental equipments need a quicker way of providing quotation on customized products.
This research study firstly used a featured model and combined with Artificial Neural Networks in order to construct a new specification of dental equipment, which is a new way to estimate the cost. Also, in according to the product design, we organized and develop a format to estimate the cost and develop the product functions. The new specification in concept evolution can satisfy market and customers’ needs, it also enables the suppliers to quickly provide quotation; enhance the sales service in this industry. Lastly, we used the data of all the costs of the completed products as a way to develop interface of the product structures and cost estimation system. This can assist the responsible person to be able to quickly and accurately receive information on production time and cost of the new product.
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