Manufacturing has become a vital pillar of the global economy. With the deepening of globalization, competition in the manufacturing industry has become increasingly fierce. Inevitable quality fluctuations in the production process may lead to a rise in product defect rates, affecting customer satisfaction and corporate reputation. To ensure that product quality is controlled and high-quality, and to maintain the stability of production processes, most manufacturing enterprises are carrying out refined management reforms, relying on technological means to improve management efficiency, optimize production processes, and maintain market competitiveness.
Among them, Statistical Process Control (SPC) provides enterprises with a powerful tool to achieve statistical management and safe and efficient production management, and has been widely used in various industries.
SPC applies statistical techniques to analyze data collected at each stage of the process and make corresponding adjustments. Focusing more on prevention, SPC implements preventive quality management by monitoring the changing trends of product quality characteristics and makes corrections before defects occur, thereby greatly reducing waste caused by rework and scrap and lowering quality costs.
The self-developed SW-LIMS by Sunway Data is equipped with a dedicated SPC Quality Control Analysis Module, which can help users conduct real-time monitoring of production processes, distinguish between random and abnormal fluctuations in product quality during production, issue early warnings for abnormal trends in the production process, and prompt the adoption of relevant measures to eliminate abnormalities, restore process stability, and improve and control product quality.
The SPC Quality Control Analysis Module of SW-LIMS enables real-time monitoring of production process data, helping users judge whether the production process is stable. Users can evaluate whether the production operation or management process is in a controlled state through control charts. If not, they can observe the variation trend through the system's control charts, conduct traceability analysis on abnormal data, identify the causes of variation, and formulate corresponding measures based on the causes to prevent the occurrence of non-conforming products and thus improve product quality.
The SPC Quality Control Function Module of SW-LIMS supports commonly used control chart tools, including Individual-Moving Range, Xbar-R (Mean-Range), Xbar-S (Mean-Standard Deviation) control charts, etc. The system can automatically count inspection data and draw various control charts such as Xbar-R, Xbar-S, X-mR, and Histogram. It can also obtain the trend of Mean-Range Chart, Mean-Standard Deviation Chart, Individual-Moving Range Chart, etc. for a single analysis item over a period of time through data statistics.
The quality control charts provided by the SPC Quality Control Analysis Module of SW-LIMS support users to customize chart types, control limits, product limits, etc. It allows users to set custom USL (Upper Specification Limit), LSL (Lower Specification Limit), UCL (Upper Control Limit), CL (Center Line), LCL (Lower Control Limit) for each analysis and testing item, as well as custom RUCL, RCL, RLCL values. Meanwhile, the system supports users to set the center value.
SW-LIMS allows users to select corresponding stability and abnormality judgment principles for various quality control charts. The system supports the eight commonly used Western Electric Rules for SPC, such as 14 consecutive points alternating up and down, 6 consecutive points increasing or decreasing continuously, etc. It also features customizable judgment conditions. After users select the corresponding abnormality judgment principles, the system will issue quality trend abnormality warnings when abnormal data trends appear.
The SPC Quality Control Analysis Module of SW-LIMS supports process capability analysis and can automatically calculate key data indicators such as Cp (Process Capability Index), Cpk (Process Capability Index for Actual Performance), deviation, kurtosis, skewness, etc. Users can analyze production conditions based on these automatically calculated key indicators and take relevant measures accordingly. The system can automatically calculate and count the maximum value, minimum value, average value, standard deviation, CPK, CP, CA, etc. of data over a period of time by inspection and analysis item.
SW-LIMS also supports the statistical calculation of CPK process capability index on a daily, weekly, monthly, quarterly basis, etc., to evaluate and analyze the process stability of production equipment. It helps managers adjust production processes in a timely manner, assists enterprises in assessing the stability and consistency of the production process, and provides directions for process improvement.
Advantages of SW-LIMS SPC Quality Control Analysis Module
1. The application of the SW-LIMS SPC Quality Control Analysis Module helps users monitor and detect abnormal conditions in the production process in a timely manner, facilitating early warning and correction of potential quality problems, thus ensuring the stability and consistency of product quality and improving product quality.
2. The application of the SPC Quality Control Analysis Module provides enterprises with real-time production data and trend analysis, helping them formulate more effective production plans, optimize resource allocation and production arrangements, meet customer needs to the maximum extent, and improve production efficiency and market competitiveness.
3. The application of the SPC Quality Control Analysis Module helps users analyze production data, identify bottlenecks and unnecessary process obstacles in the production process, thereby optimizing production processes, reducing adverse consequences such as scrap, rework and losses, and improving production efficiency while lowering costs.
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