SPC concept

SPC基本觀念整合
適合全數檢驗的條件：
[1]. 批量太少，失去抽樣檢驗的意義時。 [2]. 檢驗手續簡單，不致大量浪費人力時間及經費時。 [3]. 不允許不良品存在，該不良品對製品有致命的影響
時。 [4]. 工程能力不足，其不良率超過規定，無法保証品質
時。
SPC基本觀念整合
隨機抽樣之原則 [1]、 不讓製造者執行抽樣檢驗。 [2]、 抽樣時可會同責任者在場。 [3]、 使抽樣人員與生產人員明瞭抽樣的目的。 [4]、 抽樣應在送驗批移動中為之。
SPC基本觀念整合
製程能力是說明當製程系統在統計的管制狀態下時，其符 合規格的能力。
製程系統的四種狀況：
製程系統狀況
應採取對策
在管制下且能力足夠
理想的狀況應予維持
在管制下且能力不足夠 共同原因的變異必須降低
不在管制下且能力足夠 特殊原因必須矯正
不在管制下且能力不足夠 特殊原因必須矯正且共同原因的變異必須降低
共同原因：製程系統有許多不明的變異原因，但隨時間的不 同而穩定的存在。以SPC的觀點為製程系統的分配隨時間的 不同是固定的，稱為在統計的管制狀態下；或簡稱管制狀態 下(Under Control)。若製程系統僅有共同原因存在，則其成品 特性的分配是可預測的。
特殊原因：有些變異的原因不常存於製程系統中，若其出現 於製程系統會導致製程系統不穩定。以SPC的觀點為製程系 統的分配隨時間的改變而不是固定的，稱為不在統計的管制 狀態下；或簡稱不在管制狀態下(Out of Control)。若製程系統 存有特殊原因，則其成品特性的分配是不可預測的。
而不是用指數來評核。
企業降低成本基本架構
降 • 降低購入價格
低 • 提高材料使用率(降低庫存成本)

15
Suggests the process has undergone a permanent change (+ or -) and is now becoming stable. Often requires that you recompute the control lines for future interpretation efforts. 过程趋向稳定
c
u
③ 单位缺陷数控制图（u图）；
④ 缺陷数控制图（c图）；
np
p
Control chart／控制图
Chart图 Description描述 Chart points do not form a particular pattern AND lie within the upper and lower chart limits. 上下限，没有形成独特模型 Example #1案例 Example #2 Interpretation备注 The process is stable, not changing. Doesn’t necessarily mean to leave the process alone. May be opportunities to improve the process and enjoy substantial benefits. 过程稳定
LCL 10
LCL 10
Run 运行
Chart points are on one side of the center line. The # of points in a run is called the length of the run. 中心线一侧形成趋势
UCL 20

UCL
CL
LCL
7
1.5 管制界限 Control Limit
1. 若某一組數據是常態分佈, 根據經驗法則, 只有 0.27% 的數據點會超出其平均值 正負三個標準差 的範圍 2. 管制圖的管制界限定義為 : 管制上限(UCL) = 平均值 + 3 標準差 管制下限(LCL) = 平均值 - 3 標準差 3.數據點超出管制界限的範圍時, 表示已有特定誤差產生 管制界限至少每半年review一次(SMIC每季review一次)
Statistic Process Control
Instructor: QE/SPC
1
1.1 SPC 的定義 Statistical (统计) Process (工艺/制程) Control (管制)
自工艺中收集资料，加以统计分析，并从分析中发觉 异常原因，采取改正行动，使工艺恢复正常，保持稳定 ，并持续不断提升工艺能力的方法。
20
创建统计制程控制图（SPC chart）
1. 选择需要建立管制图的制程(PIE, TCP) 2. 确定抽样方法和计划(PIE, EDC Plan) 3. 测量和收集原始数据 4. 计算适当的统计量(Xbar, RS)
5. 决定管制界限，管制规则等(Xbar/RS control,
WECO Rule)
SMIC: WECO1 is at least for all SPC charts, Xbar and RS charts should add at least one other rule.
19
1.7 控制图的种类
WECO rule 2~5 is only for Xbar and RS chart
UCL(+3x)

SPC Basic Training ManualIntroductionWelcome to the SPC (Statistical Process Control) Basic Training Manual. This manual is designed to provide you with a fundamental understanding of SPC and how it can be applied to improve process and product quality.Chapter 1: What is SPC?SPC is a methodology for controlling and improving the quality of processes and products. It involves the collection and analysis of data to identify and reduce variation in a process. By understanding and controlling variation, organizations can increase efficiency, reduce defects, and ultimately improve customer satisfaction.Chapter 2: Key SPC ConceptsIn this chapter, we will introduce you to the key concepts of SPC. These concepts include: - Variation: Understanding the different types of variation in a process. - Control charts: Learning how to create and interpret control charts to monitor process performance. - Process capability: Assessing the capability of a process to meet customer requirements. - Sampling: Understanding the importance of sampling techniques in data collection.Chapter 3: Tools and TechniquesIn this chapter, we will explore the various tools and techniques used in SPC. These include: - Pareto analysis: Identifying and prioritizing the most significant contributors to process variation. - Cause and effect diagrams: Investigating and understanding the root causes of process problems. - Histograms and scatter plots: Analyzingdata distributions and relationships. - Six Sigma: Applying the principles and methods of Six Sigma to improve process performance.Chapter 4: Implementing SPCIn this chapter, we will discuss the steps involved in implementing SPC in an organization. These steps include: 1. Define the process: Clearly define the process to be monitored and improved. 2. Collect data: Identify the appropriate data points and collect data over a period of time. 3. Analyze the data: Use statistical analysis techniques to identify patterns and trends in the data. 4. Implement control charts: Create control charts to monitor the process and identify out-of-control conditions. 5. Take corrective actions: When an out-of-control condition is detected, take appropriate corrective actions to bring the process back into control. 6. Continuously improve: Use the information gathered from SPC to make continuous improvements to the process.Chapter 5: SPC Case StudiesIn this final chapter, we will present real-life case studies that demonstrate the successful implementation of SPC in various industries. These case studies will highlight the benefits and the practical applications of SPC.ConclusionIn conclusion, SPC is a powerful methodology for improving process and product quality. By implementing SPC techniques, organizations can reduce defects, increase efficiency, and enhance customer satisfaction. This training manual serves as a foundation for your understanding of SPC and its applications. We encourage you to apply the knowledge gained from this manual to your own processes and make continuous improvements. Good luck on your SPC journey!。