mkyeong91 / inklesswafermap.md

Created January 26, 2026 06:25

Inkless Wafer Map

An inkless wafer map is a digital method for identifying and tracking good and bad dies on a semiconductor wafer without physically marking them with ink. It replaces traditional ink-based binning with electronic mapping, enabling cleaner, more automated, and traceable wafer sort and assembly processes.

🧠 What Is an Inkless Wafer Map?

Traditional method: Dies that fail wafer sort are physically marked with ink to prevent them from being packaged.
Inkless method: Instead of ink, a digital wafer map records pass/fail status and bin codes for each die.
Format: Typically a standardized file (e.g., WID, KLARF, XML) shared between wafer sort and assembly/test equipment.

mkyeong91 / cassandrar.md

Created January 26, 2026 04:55

Data management and analytics: Cassandra & R

Cassandra and R come from different but complementary domains in data management and analytics.

🗄️ Apache Cassandra

Definition: Cassandra is an open-source, distributed NoSQL database designed to handle massive amounts of data across many servers with high availability and no single point of failure.
Key Features:
- Scalability: Can scale horizontally by adding more nodes without downtime.
Fault tolerance: Data is automatically replicated across multiple nodes and data centers.

mkyeong91 / aifields.md

Created January 26, 2026 04:47

Difference between AI, Machine Learning and Deep Learning

🌐 Artificial Intelligence (AI)

Definition: The broad field of creating systems that can perform tasks requiring human-like intelligence (reasoning, learning, problem-solving).
Scope: Includes rule-based systems, expert systems, machine learning, robotics, natural language processing, and more.
Analogy: AI is the “umbrella” term covering all intelligent systems.

mkyeong91 / pat.md

Last active January 26, 2026 04:44

Part Average Test (PAT)

🔑 What is Part Average Test (PAT)?

Definition: PAT is a statistical screening method used in semiconductor testing to identify outlier devices by comparing each part’s test results against the average of its peer group.
Purpose: To catch subtle defects or marginal parts that may still pass standard test limits but are abnormal compared to the rest of the lot.
Origin: Widely adopted in automotive and high-reliability semiconductor industries to improve quality and reduce field failures.

mkyeong91 / rulebasedanalytics.md

Created January 26, 2026 04:14

Rule-based analytics

Rule-based analytics is a method of analyzing data by applying predefined rules or conditions to identify patterns, anomalies, or actionable insights. Instead of relying on machine learning or statistical models, it uses explicit “if-then” logic crafted by domain experts to guide decision-making.

🔑 Core Idea

Rules = Expert Knowledge: Analysts or engineers define rules based on domain expertise (e.g., “If wafer temperature > 200°C, flag as abnormal”).
Deterministic Outcomes: The system produces consistent results because rules are fixed and transparent.
Actionable Alerts: When data violates a rule, the system triggers alarms, reports, or corrective actions.

mkyeong91 / industry4.md

Created January 26, 2026 03:52

Industry 4.0

Industry 4.0, also called the Fourth Industrial Revolution, is the digital transformation of manufacturing and industry through technologies like IoT, AI, robotics, and cloud computing. It enables smart factories that are highly connected, data-driven, and capable of real-time decision-making.

🌐 Overview of Industry 4.0

Definition: Industry 4.0 refers to the integration of advanced digital technologies into industrial processes to create smarter, more efficient, and interconnected systems.
Origin: The term was first introduced in 2011 at the Hannover Fair in Germany as part of a national initiative to modernize manufacturing.
Goal: To revolutionize how products are designed, manufactured, and distributed by leveraging automation, connectivity, and data.

mkyeong91 / cloudcomputing.md

Created January 26, 2026 03:50

Cloud Computing

Cloud computing

Cloud computing is the delivery of computing services—like servers, storage, databases, networking, software, and analytics—over the internet (“the cloud”), allowing users to access resources on-demand without owning physical infrastructure. It enables scalability, flexibility, and cost efficiency by using pay-as-you-go models.

🌐 Key Concepts of Cloud Computing

On-demand access: Users can instantly provision computing resources without waiting for hardware installation.
Pay-per-use pricing: Costs are based on actual usage, reducing upfront capital expenditure.
Scalability: Resources can be scaled up or down depending on demand.
Accessibility: Services are available anywhere with an internet connection.

mkyeong91 / fdc.md

Created January 26, 2026 03:13

Fault detection and Classification (FDC) in semiconductor manufacturing

Fault Detection and Classification (FDC)

In the semiconductor supply chain, FDC stands for Fault Detection and Classification. It is a critical process control system that continuously monitors equipment and process parameters to detect abnormalities early, classify the type of fault, and prevent defective wafers from moving further down the line. Together with Test, Assembly, and Characterization, FDC forms part of the broader yield management and quality assurance ecosystem.

🔑 Role of FDC in Semiconductor Manufacturing

Fault Detection (FD): Identifies abnormal conditions in tools or processes (e.g., plasma density drift, gas flow irregularities, chamber leaks).
Fault Classification (FC): Categorizes the detected issue (e.g., RF power supply failure vs. contamination) to guide engineers toward root cause analysis.
Real-time monitoring: Uses thousands of sensors across fab equipment to continuously track parameters.
Yield protection: Stops or adjusts processe

mkyeong91 / awsefs.md

Created January 21, 2026 15:16

Amazon Elastic File System (EFS)

Amazon Elastic File System (EFS) is AWS’s fully managed, serverless file storage service that automatically scales up or down as you add or remove files. Unlike EBS, which attaches to a single EC2 instance, EFS can be mounted simultaneously by thousands of EC2 instances across multiple Availability Zones, making it ideal for shared workloads.

🔹 What is Amazon EFS?

Definition: A serverless, elastic file system that grows and shrinks automatically with your data.
Protocol: Uses NFSv4.0 and NFSv4.1, so it feels like a traditional network file system.
Access: Multiple EC2 instances (Linux or macOS) can mount the same file system at once.
Durability & Availability: Designed for 11 nines durability (99.999999999%) and 99.99% availability.

mkyeong91 / awsebs.md

Created January 21, 2026 15:11

Amazon Elastic Block Store (EBS)

Amazon Elastic Block Store (EBS) is AWS’s block storage service for EC2 instances, and EBS snapshots exist as point‑in‑time backups of your volumes. Snapshots are incremental, stored in Amazon S3, and can be used to restore or replicate volumes for disaster recovery or migration.

🔹 What is AWS EBS?

Definition: Amazon Elastic Block Store (EBS) provides scalable, high‑performance block storage for Amazon EC2 instances.
Usage: Works like a virtual hard drive. You can:
- Store files
Install applications

MK mkyeong91