Pengantar Analisis Data untuk Memecahkan Masalah Kualitas

Unlock Insights for Quality Improvement with Data Analysis!

This course, "Introduction to Data Analysis for Solving Quality Problems," builds upon foundational knowledge from Industrial Engineering at Bina Nusantara University (ISYE6125 & ISYE6158). It's designed for both undergraduate and graduate students, as well as professionals seeking to enhance their data analysis skills for practical applications. This self-study material provides a comprehensive understanding of using data to identify and resolve quality issues.

The course is structured into 5 sections and 10 modules, covering key concepts:

• Introduction to Data Analysis for Process and Product Improvement: Learn fundamental data analysis techniques for problem-solving and explore essential quality tools for optimizing processes and products.
• Data and Measurement: Master data classification and understand different measurement scales – crucial for accurate analysis.
• Describing Variation to Identify Quality Problems: Develop skills in describing variation using both numerical methods and graphical methods to pinpoint the root causes of quality problems.
• Control Charts for Stability Analysis: Gain a solid understanding of process control and learn how to develop and interpret control charts for assessing process stability.
• Process Capability Analysis: Learn how to perform process capability analysis and utilize capability indices to identify potential quality problems and ensure processes meet specifications.

Upon completion of this course, you will be able to:

• Explain the fundamental concepts of data analysis for process and product improvement.
• Articulate a clear understanding of data classification and measurement scales.
• Apply basic methods for describing variation in data.
• Implement basic statistical process control techniques.
• Perform process capability analysis to identify quality issues.

To reinforce your learning, the course includes a final quiz to assess your comprehension of the material. Start your journey to data-driven quality improvement today!