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所在平台: Udemy |
课程主页: https://www.udemy.com/course/six-sigma-statistic-with-minitab-time-series-plot/
课程评论：没有评论
**课程名称：** Minitab 中的趋势与季节性分析 - Tabtrainer 工具 **课程概述：** 本课程是 Tabtrainer® 认证系列的一部分，专注于工业分析和数据驱动的质量策略。您将使用 Minitab® 软件，结合 Smartboard 公司 20 年的真实生产数据，掌握时间序列分析。课程内容包括： * **数据清洗与提炼：** 清理和精炼历史废品数据，排除周末、节假日以及 2017 年 1 月 1 日之前的不可靠数据。学习如何过滤和优化原始数据，创建更准确、更有用的新工作表。 * **趋势可视化：** 创建和优化时间序列图，识别废品率随时间变化的趋势和模式，理解季节性波动，并分离影响生产质量的关键因素。 * **季节性分析：** 探索由于假期（如暑假、圣诞节）和临时工导致废品率升高的模式。通过识别这些低效率，学习如何提出可行的改进建议，以减少浪费并优化工作流程。 * **结果展示：** 将可视化图表和工作表信息导出到 PowerPoint，以便进行清晰的文档记录和报告。确保能够有效地向关键利益相关者和决策者传达分析结果和建议的解决方案。 **课程目标：** 通过本课程，您将学会如何提炼数据集，可视化趋势，并将统计洞察应用于解决质量管理中的实际问题。您将获得 Minitab 工具的实际操作经验，从而提高提取可操作信息和有效改进运营效率的能力。 **讲师：** Prof. Dr. Murat Mola，TÜV 认证的六西格玛专家，德国 2023 年度教授。 **目标学员：** 质量专业人士和生产分析师。
Welcome to the Tabtrainer® Certified Series - your expert platform for industrial analytics and data-driven quality strategies.In this course, you'll master time series analysis using Minitab®, working with 20 years of real production data from the Smartboard Company. You'll learn to clean and refine historical scrap data, build clear visualizations, detect seasonal inefficiencies, and present trends that support operational improvement.From excluding weekends and holidays to identifying summer and Christmas effects due to temporary staffing, this course shows how statistical clarity leads to strategic decision-making.Led by Prof. Dr. Murat Mola, TÜV-certified Six Sigma expert and Professor of the Year 2023 in Germany, this training equips quality professionals and production analysts with the tools to deliver measurable impact through clear, data-backed insights.In this course, participants learn how to manage, cleanse, and analyze large datasets using Minitab's time series plot. The dataset, spanning 20 years of production at Smartboard Company, focuses on scrap rates in skateboard manufacturing. Key skills include:Data Import and Cleansing: Extracting relevant data by removing non-production days (weekends, holidays) and unreliable data before January 1, 2017. Participants also learn to create new worksheets by filtering and refining raw data for better accuracy and usability.Trend Visualization: Creating and refining time series plots to identify chronological trends and tendencies in scrap rates. This includes exploring patterns over time, understanding seasonal variations, and isolating significant factors that influence production quality.Seasonal Analysis: Exploring patterns such as higher scrap rates during summer vacations and Christmas due to temporary staff. By identifying these inefficiencies, participants learn how to recommend actionable improvements to reduce waste and optimize workflows.Presentation: Exporting visualizations and worksheet information to PowerPoint for clear documentation and reporting. This ensures participants can effectively communicate insights and proposed solutions to key stakeholders and decision-makers.By the end of the course, participants will understand how to refine datasets, visualize trends, and apply statistical insights to address real-world challenges in quality management. They will gain hands-on experience with Minitab tools, enhancing their ability to extract actionable information and improve operational efficiency effectively. This combination of practical skills and analysis techniques prepares participants to drive impactful, data-driven decisions in their organizations.
