Quality Basics

Concurrent Session

M37 - Grading: Uncover the Insight Hidden in Big Data

Primary Presenter(s)

• 

  Steve Wise

  Vice President Statistical Methods
  InfinityQS® International, Inc.
  Fairfax, Virginia

Moderator(s)

• 

  Imran Rana

  Corporate Quality Management Head
  Treet Corporation Limited
  Lahore, Pakistan

Level: Basic

In today’s world of automated data collection, manufacturers are looking for solutions that can process and analyze their mountains of shop-floor data and provide useful, actionable information. These companies want quick answers to all of their major quality problems and process improvement initiatives. What sites need the most attention? What lines generate the most quality issues? What products produce the highest levels of scrap? Are there certain features causing problems on an entire product line? Where is the low-hanging fruit or easy improvement opportunities? This session will discuss new ways of analyzing huge amounts of data, while still adhering to sound statistical principles. It will cover data organization, yield computations, grading, and roll-up techniques. Attendees will learn how to get instant insight out of their current big data repositories.

Learning Objectives:

• Learn the benefits of daily summary records for manufacturers monitoring multiple streams of quality data.
• Calculate yield potential and yield performance.
• Understand the new method of looking at data streams, known as “grading,” and how to calculate grades.
• Roll up grades across days, processes, and parts to generate global process improvement.
• Perform enterprise-wide grade analysis, taking a look at the whole quality picture and drilling down to where to prioritize quality efforts.