為滿足國際環保法規與客戶環保規範的要求，研究背景公司建置一套綠色產品管理系統GPMS，藉由GPMS管控產品料號的有害物質符合性，以確保產品所含之有害物質皆符合目前國際環保法規與客戶規範管制限值要求。隨著國際法規與客戶規範日趨嚴謹，管控的有害物質限值含量逐年降低，管制項目亦同步增加。本研究以產品料號、料號供應商與有害物質之關聯性作為研究主題，探勘出彼此之關聯性。藉由關聯規則FP-growth演算法，將產品組成結構與有害物質之含有量納入評估範疇，探勘出同類型的料號在不同供應商提供的情況下，有害物質含有量是否有明顯差異，進而納入供應商的選擇條件中，亦藉由探勘手法找出有害物質之間是否具其他關聯性，在未來管制條件變嚴苛之前，進行前瞻性的管制處理。
本研究根據產品料號特性，將原始資料劃分成五大類別分別進行料號、供應商、有害物質三方面的研究分析，找出需關注的重點供應商與有害物質存在的風險性以及有害物質彼此之間的關聯性。藉由分析結果改善現行管理模式有所欠缺的地方，在綠色供應鏈管理方面可作為供應商選擇的參考建議，在有害物質管理方面，關注有害物質彼此之關聯性具有更精確的管制成效以落實有害物質之風險管控。

Environmental protection is a critical issue in green supply chain management, and several regulations have been proposed to specify the thresholds of chemical substances that can be hazardous to human body. It is therefore important for managers to know the rela-tionships among the hazardous substances in products. For this purpose, this study ag-gregates the data for parts of products, suppliers, and hazardous substances to perform association analysis. Data are first divided into five categories based on the identification number of parts, and the FP-growth algorithm is applied on each one of the five categories to find association rules for parts, suppliers, and hazardous substances. Those rules pro-vide not only concrete results in choosing suppliers for parts to control hazardous sub-stances, but also the associations among hazardous substances in parts. These findings are useful in supplier selection and managing hazardous substances for parts to satisfy the requirements of the international regulations.

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