SMT 產業如何利用視覺化數據洞見提昇生產製造良率

Abstract

自從德國在2011 年提出的第四次工業革命，也就是所謂的工業4.0，或 者是稱作生產力4.0，主要是以一個創新的物聯網技術結合工業應用，利用現代的感知設備收集大量數據，進行整理分析，可以讓少量多樣的產品於生產環境中，相對提升產品的良率與提高生產效率，做到精準的生產，並且透過數據以調動現有的生產資源，減少多餘的成本與浪費，打造一個智慧工廠。 表面黏著技術(Surface Mount Technology, SMT)在相關的電子產業範疇 裡，佔據非常重要的角色，隨著電子產品的精緻及最小化，在電子產業上離不開SMT ，SMT 現階段也是電子工業最重要的生產製造的一個生態系統(Eco-System)。 現階段SMT 因應各種精密電子產品的要求，除了提昇整體生產量外，整 體的良率也必須達95% 以上，控制在5% 的不良率，讓整體企業獲利，並且追求未來的工廠達到一個智慧工廠，讓企業增加競爭力。 本論文主要探討一個個案研究，針對此SMT 工廠進行相關的製程良率的 數據收集，並且透過視覺化的工具洞見相關的數據內容，取代原本良率採用表格式的方法進行良率監控，讓相關的第一線現場設備人員，與第二線的品質管控人員能夠即時的監控產品生產良率，並且依據良率監控調整設備與調整流程，最佳化的生產效率。 SMT 工廠如何提昇良率增加市場的競爭優勢，經本研究深入了解，其工 廠必須具備幾個方向，其中包含數據的轉置、數據平台的建立及分析平台的建置，並且透過數據洞見的人員訓練等規劃。 關鍵字:工業4.0、生產力4.0、大數據、視覺化、SMT、智慧製造。Germany proposed the fourth industrial revolution in 2011 which we called as Industry 4.0 or Productivity 4.0. Industry 4.0 is mainly based on an innovative Internet of Things technology combined with industrial applications, using modern sensing devices to collect, organize and analyze the large amounts of data. We called it as cyber-physical system. In “Small-Volume/Multiple-Types of Products” production environment, it relatively improves the yield of product and the production efficiency and achieves the goal of precise production. At the end, Industry 4.0 controls the resource of production through the data, reduces unnecessary costs and waste, and builds a smart factory.

Surface Mount Technology (SMT) plays a very important role in the related electronics industry. With the miniaturization of electronic products, SMT is inseparable from the electronics industry. SMT is a manufacturing Eco-System which is the most important part in electronic industry at current stage. At this stage, SMT meets the requirements of various precision electronic products. In addition to improvement of the overall production volume, it also improves the overall yield which must be over 95%. Controlling the defective rate below 5% by SMT makes the whole company profitable and pursue the future smart factory that allows companies to increase their competitiveness. The purpose for this research paper is to discuss a SMT involved case study. We collect relevant process yield data for this SMT factory, and visualize the relevant data content through visual tools to replace the original yield using the tabular method for yield monitoring. These make the first-line field equipment personnel and the second-line quality control personnel can immediately monitor the yield of the product. Then, the related personnel can optimize the equipment and the process to maximize the production efficiency. After in-depth case study, we know how to increase the competitive advantage of the market by increasing the yield of product. The SMT factories must work in several directions, including the planning of data processing (Extract-Tansform-Load), platform establishment, analysis platform construction, and personnel training through data insights. Keywords: Industry 4.0, Productivity 4.0, Big Data, Visualization, SMT, Smart Manufacturing.