摘要 群組技術( GT )是一種管理策略。它影響的層面擴及到大部分的公司,而且它對生產力的衝擊也是不能輕忽的。群組技術是用來改進製造系統生產力的一種製造哲學。為了成功執行生產的一個群組技術系統,人們必須理解它在系統表現方面的影響,將不同部門的功能整合,則會有助於這個系統執行的技術。如果將群組技術導入得好,便能夠導引經濟效應和工作的滿意。單元形成( CF ),是在設計單元製造系統時面對的最重要的問題之一,也是處理相似部分工件族群的有效方法。一個工件族是利用類似幾何學或是將需要一個類似的生產過程(方法)的一大群工件所聚集而成的。傳統的群組技術演算法,如分類編碼法與生產流程分析法等皆無法考慮其不確定性符號資料或者模糊的資料等。因此,在本文當中,我們提出處理這類資料的群組技術,特別在資料為混合型型態時使用新提出的混合型資料分類演算法來處理單元形成的問題,而獲得相當有效的結果。
Abstract Group Technology (GT) is a strategy in management. It affects a company on most areas. Its impact on productivity is so important that we can not underestimate it. It is also a manufacturing philosophy in improving the productivity for a manufacturing systems. To implement a GT system successfully, one has to understand its impact on the system performance, the different department functioning and the technologies that can assist the implementation. If it is used well, it can lead to economic benefits and job satisfaction. Cell formation (CF), one of the most important problems faced in designing cellular manufacturing systems, is to involve identifying families of similar parts. A part family is a group of parts presenting similar geometry and requiring a similar production process. Traditional schemes such as the classification on coding and the production flow analysis do not consider uncertainty, symbolic or fuzzy data. In this study, we use a mixed-type data clustering algorithm to cell formation. Some examples are demonstrated by applying the proposed method to the real data.