Resume in 2024.
I am an Smart Manufacturing Engineer specializing in industrial engineering, data science, machine learning, and data engineering. My career is marked by a commitment to excellence and a proven ability to enhance production processes.
AUO Advanced Manufacturing Center:
- Role: Develop and optimize decision-support systems.
- Focus: Leverage domain knowledge and advanced data analytics to improve yield and boost computational performance.
- Large-Scale Projects: Successfully handled multiple projects, creating efficient, data-driven solutions that save significant labor hours.
- Achievement: Improved operational efficiency and productivity.
- Quick comprehension and application of domain-specific knowledge.
- Expertise in complex problem-solving and algorithm development.
- Master’s Degree in Industrial Engineering and Management with a perfect GPA from National Yunlin University of Science and Technology.
- Participate in multiple industry-academia cooperation projects in the field of data analysis.
My dedication to pushing the boundaries of smart manufacturing technologies is evident in my continuous pursuit of innovation and excellence.
Master of Industrial Engineering and Management
- National Yunlin University of Science and Technology
- Aug. 2019 – Jul. 2021
- GPA: 4.0/4.0
- Thesis: Improve the Predicted Efficiency of Crowd Flow in Large Areas Based on the R-tree and the SPACE-MDL-LSTM
Bachelor of Industrial Engineering and Management
- National Yunlin University of Science and Technology
- Sep. 2015 – Jun. 2019
- Thesis: Optimization of machine dispatching in flexible production processes (use Genetic algorithm)
AUO Advanced Manufacturing Center
- Aug. 2021 - Present
- Key Responsibilities:
- Develop and optimize TFT-LCD Array decision-support projects
- Apply and refine machine learning algorithms
- Improve production processes, product/equipment yield, efficiency, and computational performance
- Participated in large-scale and medium-scale projects, saving significant labor hours
Academia Sinica GIS Center
- Feb. 2019 – Jul. 2019
- Project Highlight:
- National Address Database for Spatial Sampling
- Developed a cost-effective system for academic survey research
- Created an address normalization module and established a national address attribute database
- Awarded Best Student Paper at the 2019 Taiwan Geographic Information Society Academic Conference
- National Address Database for Spatial Sampling
| Scale | No. | Project | Description | Performance | Role |
|---|---|---|---|---|---|
| Large | 1 | Yield-Capacity Decision Support System | Recommended machine PM schedules through yield forecasting and capacity analysis | 20% reduction in model RMSE, 80% accuracy, saved 90 hours of labor per month | Project Owner, Data Engineer, Data Scientist, Front/Backend Engineer |
| 2 | Golden Path - Optimal Machine Combination Path Recommendation | Recommended best and worst path combinations affecting yield | Reduced defect counts by 1.43%, increased product yield by 1.62%, saved 60 hours of labor per month, implemented in 4 fabs | Data Engineer, Front/Backend Engineer | |
| 3 | Capacity Calculation Decision Support System | Automated checks to ensure production status meets demand requirements | Implemented in 4 process steps, saved 3 hours daily for manufacturing personnel | Data Engineer, Data Scientist | |
| Medium | 4 | Manufacturing Production Rule Decision Support System | Monitored production conditions to trigger rules for decision support | Implemented in 4 fabs, saved 300 hours of labor per month | Project Owner, Data Engineer, Front/Backend Engineer |
| 5 | Correlation Study Based on Field Data Application | Using interpretable models to enhance result interpretation ability. | Verified in 3 scenarios | Data Engineer, Data Scientist | |
| 6 | Optimization and Reconstruction of Key Factor System Modules | Increased computational speed through architecture optimization | Increased calculating efficiency by 80% | Data Engineer, Data Scientist | |
| 7 | Feasibility Study of LLM Model for Field Adaptive Monitoring | Connected LLM model to database using LangChain, designed prompts for process monitoring | Improved data analysis accuracy, enhanced decision-making and operational efficiency | System Architect, Prompt Designer, Feasibility Analyst |
| Category | Skills |
|---|---|
| Data Science | Python, SQL, Machine Learning, Data Processing |
| Web Development | Django, Streamlit, HTML, Javascript, CSS |
| API Development | RESTful APIs, FastAPI |
| Others | Git, Databricks / Delta Lake |
我是一名智慧製造工程師，專精於工業工程、數據科學、機器學習和數據工程。我的職業生涯以追求卓越為標誌，並且具備顯著提升生產流程的能力。
AUO 智慧製造中心:
- 角色: 開發和優化決策支援系統
- 重點: 利用領域知識和數據分析技術提升良率和計算性能
- 專案概述: 成功處理多個項目，創造高效、數據驅動的解決方案，節省大量工時
- 專案成就: 提高運營效率和生產力
- 快速理解和應用領域知識
- 專精於複雜問題解決和算法開發
- 國立雲林科技大學工業工程與管理碩士，GPA 4.0
- 參與多個數據分析領域的產學合作專案
我的職業生涯反映了我對推動智慧製造技術的持續追求，並展現了我在創新和卓越方面的不懈努力。
工業工程與管理碩士
- 國立雲林科技大學
- 2019年8月 – 2021年7月
- GPA: 4.0/4.0
- 論文: 基於R-tree與SPACE-MDL-LSTM提升大區域人流預測之效率
工業工程與管理學士
- 國立雲林科技大學
- 2015年9月 – 2019年6月
- 論文: 最佳化彈性生產流程之機台派工 (基因演算法)
AUO 智慧製造中心
- 2021年8月 - 至今
- 主要職責:
- 開發和優化TFT-LCD Array決策支援項目
- 應用和改進機器學習算法
- 改善生產流程、產品/設備的良率、效率和計算性能
- 參與7項大型和中型項目，節省大量工時
中央研究院 GIS 中心
- 2019年2月 – 2019年7月
- 項目亮點:
- 全國地址數據庫應用於空間抽樣
- 開發一個具有成本效益的學術調查研究系統
- 創建了地址正規化模組並建立了全國地址屬性資料庫
- 獲得2019年台灣地理資訊學會學術研討會最佳學生論文獎
- 全國地址數據庫應用於空間抽樣
| 規模 | 編號 | 項目 | 描述 | 表現 | 角色 |
|---|---|---|---|---|---|
| Large | 1 | Yield-Capacity Decision Support System | 通過良率預測和產能分析推薦機台PM計劃 | 模型RMSE降低20%，準確率達80%，每月節省90小時工時 | Project Owner, Data Engineer, Data Scientist, Front/Backend Engineer |
| 2 | Golden Path - Optimal Machine Combination Path Recommendation | 推薦影響良率的最佳和最劣路徑組合 | 缺陷數量減少1.43%，產品良率提高1.62%，每月節省60小時工時，已在4個廠域導入 | Data Engineer, Front/Backend Engineer | |
| 3 | Capacity Calculation Decision Support System | 自動檢查生產狀態以確保滿足需求要求 | 導入4個生產流程，每天為製造人員節省3小時工時 | Data Engineer, Data Scientist | |
| Medium | 4 | Manufacturing Production Rule Decision Support System | 監控生產條件以觸發決策支持規則 | 導入4個廠域，每月節省300小時工時 | Project Owner, Data Engineer, Front/Backend Engineer |
| 5 | Correlation Study Based on Field Data Application | 使用可解釋性模型提升結果解釋能力 | 已在3個場景驗證 | Data Engineer, Data Scientist | |
| 6 | Optimization and Reconstruction of Key Factor System Modules | 通過架構優化提高計算速度 | 計算效率提高80% | Data Engineer, Data Scientist | |
| 7 | Feasibility Study of LLM Model for Field Adaptive Monitoring | 使用LangChain將LLM模型連接到數據庫，設計Prompt以進行流程監控 | 改進了數據分析準確性，提高了決策和運營效率 | System Architect, Prompt Designer, Feasibility Analyst |
| 類別 | 技能 |
|---|---|
| Data Science | Python, SQL, Machine Learning, Data Processing |
| Web Development | Django, Streamlit, HTML, Javascript, CSS |
| API Development | RESTful APIs, FastAPI |
| Others | Git, Databricks / Delta Lake |