最後更新：2026.06.22
February 11, 2026 | Author: Chi-Tang Cheng
SPC
CMM Integration
Precision Components
Overseas Deployment
About This Case
Thailand’s Longyi Industrial adopted MiDFUN’s SPC statistical process control system and achieved automatic data integration with its ZEISS coordinate measuring machine (CMM). After adoption, QC staff freed up 60% to 70% of their data-handling time, the process anomaly response time was shortened from hours to minutes, and quality management successfully shifted from “after-the-fact inspection” to “real-time prevention.”
Customer Profile: Thailand’s Longyi Industrial
Longyi Industrial Co., Ltd. of Thailand is a precision-component manufacturer with many years of deep roots in Thailand, primarily supplying critical components to high-tech industries. With superb machining craftsmanship and stringent quality requirements, Longyi Industrial holds an important position in the global supply chain.
Facing increasingly demanding international customer specifications, Longyi Industrial places great importance on controlling product dimensional accuracy and has long relied on German ZEISS coordinate measuring machines (CMM) for high-precision inspection. However, as capacity expanded and quality control requirements rose, the traditional data-handling process became a bottleneck for improving production line efficiency.
Challenges Faced
Before adopting MiDFUN’s SPC system, Longyi Industrial faced the following quality management pain points:
| Category | Problem Description |
|---|---|
| Efficiency and Manpower | ZEISS CMM data had to be manually entered into Excel spreadsheets by QC staff, which was labor-intensive and inefficient. Report output was delayed, and QC staff spent most of their time on data entry rather than analysis. |
| Data Accuracy | When transcribing or copying and pasting data manually, numerical mis-entries or field errors easily occurred, distorting SPC analysis results and potentially triggering wrong process decisions. |
| Lack of Timeliness | Manual handling made real-time SPC monitoring impossible, so process drift or anomalies were often not discovered until hours or even days later, resulting in large quantities of nonconforming products. |
| Poor Traceability | Linking CMM measurement data with specific work orders, machines, and times required manual cross-checking, which was time-consuming, labor-intensive, and error-prone, making it hard to quickly pinpoint the source of quality problems. |
Implementation Solution and Key Results
MiDFUN’s SPC system, paired with the automatic CMM integration module, brought Longyi Industrial the following key improvements:
Data Source Automation: Freeing 60-70% of Data-Handling Time
Through the automatic CMM data acquisition module, MiDFUN’s SPC system extracts the designated key measurement values directly from the standardized files produced by the ZEISS CMM—in real time and without human intervention. This automated integration thoroughly eliminated manual entry errors, ensured the accuracy of SPC analysis data, and freed over 60% to 70% of QC staff’s data-handling time, allowing them to focus on anomaly analysis and process optimization.
Real-Time Process Monitoring: Anomaly Response Time Shortened to Minutes
After the CMM completes a batch of measurements, the data fully enters MiDFUN’s SPC system within minutes and the control charts are automatically updated. When data points begin trending continuously toward the control limits (run rule violations), the system immediately issues an alert to the product owner, allowing engineers to make machine fine-tuning before products exceed specification. Anomaly response time was shortened from the previous several hours to minutes, achieving the shift from after-the-fact inspection to upfront prevention.
Faster Decisions: Precisely Pinpointing the Cause of Anomalies
Based on the process characteristics of each part number, MiDFUN’s SPC system establishes dedicated OOC/OOS eight detection rules. The alert message clearly indicates which part, which feature, and on which machine the anomaly occurred, and automatically notifies the relevant engineers and supervisors. Engineers can use the control charts and trend analysis provided by the system to quickly pinpoint the cause of process anomalies (such as tool wear, temperature drift, etc.), greatly reducing the product scrap rate.
Digital Quality Records: Strengthening Trust in Customer Audits
MiDFUN’s SPC system automatically links every CMM measurement with production information (work order number, operator ID, machine ID, etc.) and stores it in a database, building a complete digital quality record. During a customer quality audit or when a specific batch needs to be traced, Longyi Industrial can retrieve all related raw CMM measurement data and SPC analysis reports within a short time, greatly strengthening the trust and transparency of quality control.
Summary of Implementation Results
| Improvement Item | Before Adoption | After Adopting MiDFUN SPC |
|---|---|---|
| CMM Data Handling Method | Manual transcription into Excel | Automatic acquisition, zero manual intervention |
| QC Staff Data-Handling Time | Most of working hours | 60-70% freed, focused on analysis and optimization |
| Anomaly Discovery Time | Hours to days | Alert notification within minutes |
| Quality Traceability Method | Manual cross-checking of paper records | System auto-linking, one-click retrieval of quality records |
| Quality Management Mode | After-the-fact inspection | Real-time preventive monitoring |
Conclusion
By adopting MiDFUN’s SPC system and successfully connecting it to a ZEISS CMM, Longyi Industrial not only solved the efficiency and accuracy problems of traditional data handling, but also elevated its quality control capability to a digital level of “real-time prevention.” The automatic CMM integration capability of MiDFUN’s SPC system compressed the time from measurement output to control chart analysis down to minutes, allowing QC staff to be freed from tedious data entry work and devote their energy to more valuable anomaly analysis and process optimization. This systematic upgrade in quality management laid a solid quality foundation for Longyi Industrial in the highly competitive precision manufacturing market.
Key Terms
| CMM | Coordinate Measuring Machine. A high-precision measuring device that uses a probe to contact the workpiece surface to measure dimensions and geometric features in three-dimensional space. |
| SPC | Statistical Process Control. Monitors process stability in real time through control charts and statistical methods to detect abnormal trends early. |
| Cp/Cpk | Process capability indices. Cp measures process precision (spread), while Cpk takes both precision and accuracy (degree of offset) into account; higher values indicate a more stable process. |
| OOC / OOS | Out of Control / Out of Specification. OOC refers to an abnormal state on the control chart that triggers a detection rule; OOS refers to a measurement that exceeds the upper or lower specification limit. Both trigger real-time alerts in MiDFUN’s SPC system. |
Source: AIAG SPC Reference Manual, ZEISS Metrology
Frequently Asked Questions
Q: Can MiDFUN’s SPC system connect automatically with a ZEISS coordinate measuring machine?
A: Yes. MiDFUN’s SPC system has a built-in automatic CMM data acquisition module that supports automated integration with ZEISS coordinate measuring machines. Once a CMM measurement is complete, the data is automatically imported into the SPC system and the control charts are updated within minutes, completely replacing manual transcription or file transfers and thoroughly eliminating manual entry errors.
Q: After adopting SPC + CMM integration, roughly how much time can QC staff save?
A: Based on the real-world case of Thailand’s Longyi Industrial, QC staff freed up 60% to 70% of their data-handling time. The work of manually transcribing CMM data into Excel is now fully automated by the system, so QC staff can spend their time on more valuable anomaly analysis and process optimization.
Q: Can the SPC system automatically catch a process that is about to go wrong?
A: Yes. MiDFUN’s SPC system has built-in detection methods such as the eight detection rules and can detect anomaly patterns such as data points trending continuously toward the control limits and consecutive rising or falling points. Once an abnormal trend is triggered, the system immediately issues an alert to the owner, allowing engineers to intervene and adjust before the product exceeds specification—turning “finding out after the fact” into “preventing it in advance.”
Q: When a customer comes to audit, can the SPC system’s quality records be retrieved directly?
A: Yes. MiDFUN’s SPC system automatically links every CMM measurement with production information such as work order number, operator, and machine ID, building a complete digital quality record. During a customer audit or when a specific batch needs to be traced, all CMM raw data and SPC analysis reports can be retrieved quickly.
Q: What should a precision-component plant prepare before adopting SPC + CMM integration?
A: Based on Longyi Industrial’s adoption experience, there are three main preparation points: (1) Confirm the CMM equipment’s data output format—MiDFUN’s SPC system CMM auto-acquisition module supports the standardized output files of mainstream brands such as ZEISS; (2) Inventory the existing quality management processes, especially which measurement data is still entered manually, and prioritize automating these data sources; (3) Establish control specifications for each part number along with the eight detection rule parameters. The more solid the preparation, the more pronounced the benefits after adoption—after adoption, Longyi Industrial’s QC staff saved 60-70% of their data-handling time. To evaluate the feasibility of adoption, you are welcome to contact MiDFUN for an on-site consultation.
About MiDFUN
MiDFUN has been deeply engaged in manufacturing quality management software since 1993, with extensive hands-on experience in measurement equipment data integration, supporting automatic data integration with CMM coordinate measuring machines from international brands such as ZEISS. From precision components to automotive electronics, MiDFUN has helped many manufacturing plants at home and abroad complete the digital transformation of quality management. The product line covers
SPC Statistical Process Control,
FMEA Failure Mode Analysis,
MSA Calibration Management,
SQM Supplier Quality Management, and ten major quality systems in total.
