Semiconductor Semiconductor

Semiconductor

Solution for Storage and Management of Production Line Inspection Data

Background of the Solution
Customer Challenge
Our Solutions
Customer Value
Success Stories

Background of the Solution

The intelligent transformation of semiconductor manufacturing faces new challenges in managing massive quality inspection data on production lines

With the explosive growth of global demand for artificial intelligence (AI) and high-performance computing (HPC), as well as the recovery of demand in consumer electronics markets such as smartphones, personal computers, servers, and automobiles, the semiconductor industry will usher in a new wave of growth. With the gradual recovery of the terminal market, AI chips are in short supply. As an important part of the semiconductor manufacturing industry, the construction and operation of smart factories are particularly important, especially as "smart manufacturing" brings about the generation of massive data on manufacturing production lines, such as product defect detection data in the quality control process. These massive production line quality inspection data have become the core assets of manufacturing enterprises. In production line quality inspection, the time-consuming quality traceability retrieval, difficult data dispersion management, and limited storage space have become the core pain points faced by semiconductor manufacturing enterprises.

Customer Challenge

Is it difficult to manage scattered quality inspection data on the production line and slow to retrieve quality traceability data?

Quality management: The quality analysis and traceability cycle is lengthy, time-consuming, and labor-intensive

Quality management: The quality analysis and traceability cycle is lengthy, time-consuming, and labor-intensive

When quality engineers conduct quality analysis or traceability, they need to search through massive amounts of data. Traditional methods can only search layer by layer according to the directory, with a single dimension and low efficiency.

The semiconductor field, especially related to automotive chips, requires data retention for at least 15 years. The cost of traditional NAS solutions is too high.

The detection data needs to be compared with the statistical data of MES and other systems, and manual statistics and comparison methods are primitive and inefficient.

Process management: Long data acquisition time and low efficiency for process problem analysis

Process management: Long data acquisition time and low efficiency for process problem analysis

Positioning analysis requires multiple dimensions, such as multiple machines on a production line, multiple production lines in the same factory, and even multiple factories within an enterprise. The current mode is manual search one by one, which is inefficient.

The amount of data involved in location analysis is enormous, and exporting existing pattern data takes too long, seriously affecting problem localization.

Global analysis involves cross factory data calling, and the existing methods mainly involve packaging, downloading, uploading, or copying media. Some also require process approval, which is very cumbersome and inefficient.

Machine management: There are too many focus points in the management process, which is cumbersome and inefficient

Machine management: There are too many focus points in the management process, which is cumbersome and inefficient

The testing machine involves multiple suppliers, with complex types and large quantities. It is mainly managed by walking and following up one by one, which makes the overall process cumbersome and inefficient.

The storage space of the machine server is limited, and it is necessary to frequently transfer the hard disk detection data to other media. Data loss may occur through methods such as FTP.

The management of inspection machines is mostly managed by one operator for multiple machines. If there are a large number of machines and problems or malfunctions occur, it is difficult to detect and follow up on them in a timely manner, which affects the normal operation of the production line business.

Our Solutions

Build a unified storage and management platform for production line data

Faced with the massive production line quality inspection data in the semiconductor industry, SandStone provides an Inspection Data Management System (IDM), which provides an efficient and unified management platform for images, logs, and other data of machine inspection equipment on multiple production lines. It helps semiconductor enterprises achieve efficient collection and aggregation of massive data, high-performance storage, intelligent data processing, and convenient data retrieval, effectively solving the problems of storage, management, and application of production line inspection data in the semiconductor industry.

Build a unified storage and management platform for production line data

Customer Value

The management of production line data has been greatly improved, and the efficiency of quality traceability has been increased by a hundred times

Quality traceability/manual review data retrieval efficiency increased by a hundred times

Quality traceability/manual review data retrieval efficiency increased by a hundred times

Manual review is faster: searching 100 billion level files in seconds can increase efficiency by hundreds of times.

Quality traceability is more timely: data is packaged, downloaded, and transmitted at lightning speed, resulting in shorter waiting times for business operations.

More precise process improvement: flexible labeling strategy, more accurate positioning of process problems, and more targeted analysis.

Automatic collection and unified management of data on the scale of 10000 level machines, making operation and maintenance management more worry free

Automatic collection and unified management of data on the scale of 10000 level machines, making operation and maintenance management more worry free

Machine management is more worry free: with a scale of tens of thousands, automatic discovery, unified monitoring, unified deployment/upgrade, automatic data collection and upload, saving time and effort.

More agile data management: automatically stratify detection data to the tape library, store metadata in the hot temperature layer, and achieve fast retrieval.

Clearer permission management: fine-grained permission management mechanism, flexible customization according to job positions, effective data sharing, and secure isolation.

Quickly adapt to multiple businesses: efficiently collaborate and connect with business systems such as YMS, MES, AI analysis and re evaluation.

Automatic data compression and tiered storage, significantly reducing TCO

Automatic data compression and tiered storage, significantly reducing TCO

Lower storage costs: Image compression conversion can reduce size by 90%, saving storage costs by over 60%.

Work is more valuable: Automation replaces tedious manual labor, reducing inefficient investment in quality/equipment management by 90%, and making work more focused.

Less investment in operation and maintenance: Centralized operation and maintenance of 10000 level machines can reduce a large amount of on-site manpower and save more than 30% of operation and maintenance costs.

More cost-effective investment: Unified management of the entire lifecycle of hot and cold pool data, without the need for separate deployment of backup systems, resulting in lower total investment costs.

Success Stories

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The storage and management of production line inspection data

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