生產線上的資料創新應用—以視覺檢測為例

Abstract

隨著數位資料的爆炸性增長，大數據(big data)時代的到來。大數據資料的運用不只改變了科學研究的範例，也逐漸影響企業提升內部組織績效管理的運作模式。然而，大數據的應用隨著企業內部營運績效流程改善漸具成效後，企業經營者也開始思考如何擴大應用到客戶服務或產品服務及生產線上。本研究認為這些應用最終還是應該回歸根本思考如何為客戶創造價值出發。 因此，本研究將以生產線上之視覺檢測服務做為研究之範例，嘗試思考對於提供視覺檢測服務之企業可否利用日常客戶不斷累積資料，系統化尋找創新的商業模式？巨量資料除了對企業內外發展的協助外能否進而啓動新的商業模式驅動新一波成長？首先，藉由大數據的分析來探討這些生產線上之視覺檢測機台檢測過程中發現不良品的可能的原因，藉以做為調整生產機台以降低不良率的依據。其次，歸納出未來該產業可以發展之三種創新商業模式：增加設備維護內容及項目、提供平行設備商付費服務、形成跨界平台。

The explosive increase of digital data has driven the era of big data, which in turn not only impacts scientific researches but also the working pattern of internal performance management in a firm. As such, firms need to think how to apply big data to customer services, product services, and production lines, and value creation is central to all these possible directions. This thesis uses vision inspection services in a production line as a case to study how to use routine data to find new business models for firms providing such services. We show that big data not only helps a firm improve its management and decision performance, but also enables a firm to create a new business model for potential growth. First, we show how big data can be used to analyze the reasons of defective products when a vision inspection machine is operated. Next, three innovative business models in this industry are proposed. 1. Increasing the content and items of equipment maintenance; 2. Providing extra services for equipment dealer; 3. Building a cross-industries platform.