MBPS (Model-Based Problem Solving)

After developing Fail Model, what is the next? 

發展失敗模型後，下一步要做什麼？

• Validate the Model

• Develop problem statement.

• Implement CAPA

• Celebration

What is the core of MBPS?

MBPS的核心是什麼？

• Problem

• CA/PA

• Root cause

• Model

What is the method can help you to do “Problem characterization and Segmentation”?

什麼方法可以幫助你進行 “問題表徵和細分”？

• 5W2H and KT (IS, IS NOT)

• Fishbone

• Time chart

• All of them

How to write a healthy problem statement? Which one is correct (你如何撰寫一個健康的問題陳述?何者正確)

• Be clear and concise in describing the problem, ensuring that data supports your statement. (在描述問題時要清晰簡潔，確保數據支持您的陳述。)

• Align with the core team of people who will be working on this problem to make sure the team agrees that the problem statement is supported by data.(與將解決此問題的核心團隊保持一致，以確保團隊同意問題陳述的支持數據。

• Write your problem statement as specific as you can given what you know about your problem at that time. (根據您當時對問題的了解，盡可能具體地寫下您的問題陳述。)

• Problem statements should be as informative as possible in as few words as possible, but shouldn’t delve into minute details. (問題陳述應盡可能少地提供信息，但不應深入研究細節。)

• All of the above

Clarify the problem can used Is/Is not List to support, what is its main purpose? Which of the following is correct.

澄清問題可以用Is/Is not List來支持，它的主要目的是什麼？ 以下哪項是正確的。

• Establishes points of comparison (建立比較)​

• Leads to a more complete problem description (更完整的問題描述)​

• Provides a test base for root cause (為根本原因提供測試基礎)​

• Gives you a fingerprint of the problem (為您提供問題的線索)​

• All of the above

  (以上皆是)

What kind of elements we should have before we start to develop models?

在開始開發模型之前我們應該具備哪些要素？

• Symptoms

  症狀

• Problem statement

  問題描述

• Suspect causes

  懷疑原因

• All the above

  以上皆是

If testing a model reveals both supporting evidence & conflicting evidence, shall we classify that model as invalidated?

如果測試模型同時顯示支持證據和相互矛盾的證據，我們是否應該將該模型歸類為無效？

• Yes

• No, we may have found a key contributing factor.

  不，我們可能已經找到了一個關鍵的影響因素

Which is NOT the benefit while we keep collect validated models?

當我們不斷收集經過驗證的模型時，哪一項不是好處？

• Workload reduction

  減少工作量

• Accelerate learning curve

  加快學習曲線

• Repeat historical trouble

  重蹈歷史覆轍

• Prevent incorrect rule of thumb

  防止錯誤的經驗法則

• Eliminate the loading from trial-and-error

  消除反複試驗帶來的負載

About exercise GDM case, which problem statement is more suitable?

關於練習GDM案例，哪一種問題陳述是比較合適的？

• 140S Z41C/Z42M 5030-49 SPACER NITRIDE DRY ETCH suffer 49 resistance high binep worse by L2KFL62200

• Start from 1/28, Z41C/Z42M 140S 5030-49 SPACER NITRIDE DRY ETCH suffered binep worse issue on L2KFL62200

• Start from 1/28, Z41C/Z42M 140S 5030-49 SPACER NITRIDE DRY ETCH L2KFL62200 suffer binep worse issue suspect cause by Qtime