In the production process, quality control is a critical link that determines an enterprise's competitiveness. Its core value lies not only in ensuring that finished products fully meet quality standards but also in continuously meeting or even exceeding customers' core needs through precise whole-process management. This helps enterprises establish a reliable brand image, reduce after-sales costs, and stabilize customer cooperative relationships. Currently, when factories implement quality control, they need to focus on the principles of "clarity, implementability, and strong guarantee". Among them, the standardized implementation of the quality technology application level is particularly crucial, which can be specifically refined into the following five core points to safeguard production quality:
1. Cultivation of Personnel's Quality Literacy: Building the "First Line of Defense" for Quality Control
Establish a systematic training system for personnel in quality-related positions (including quality inspection, production operation, technical research and development, etc.). The training content should cover quality concepts (such as "zero defect" awareness and customer-oriented thinking), quality standards (industry regulations and enterprise internal control requirements), and post quality responsibilities. This ensures that every employee involved in production and quality management can integrate quality awareness into daily work, transforming from "passive execution" to "active control", and avoiding quality risks caused by human factors from the source.
2. Accurate Identification of Key Control Points: Targeting the "Core Focus" of Quality Management
Comprehensively sort out and clarify the links that require key management and control based on product characteristics and production processes. Specifically, the following should be clearly defined:
- Control Objects: Clarify whether the focus is on finished products (such as appearance, performance, and dimensions) or production processes (such as raw material proportioning, processing temperature, and assembly procedures);
- Control Indicators: Clearly list the quality characteristics (such as product qualification rate and performance parameter deviation range) and process parameters (such as production equipment speed and processing duration) that need to be controlled. This ensures that quality management is "targeted" and avoids wasting resources on non-critical links.
3. Standardized Construction of Measurement Systems: Ensuring "Authenticity and Reliability" of Quality Data
- Formulate Scientific Measurement Methods: For the identified quality characteristics and process parameters, clearly define measurement steps and judgment standards (such as qualified/unqualified thresholds) to avoid data deviations caused by inconsistent measurement methods;
- Select Appropriate Measuring Instruments: According to the requirements of measurement accuracy, select calibrated and qualified instruments (such as vernier calipers and electronic detectors) to ensure that the performance of the instruments meets the measurement needs;
- Conduct Measurement System Evaluation: Regularly verify the stability and accuracy of the measurement system through methods such as Gage Repeatability and Reproducibility (GR&R) analysis. This eliminates "misjudgments" caused by measurement errors and provides reliable data support for quality decision-making.
4. Standardization of Sampling and Inspection Plans: Achieving "Efficient Compliance" in Quality Verification
Formulate a reasonable sampling plan (such as using standards like GB/T 2828.1 to determine sampling proportion and sample size) based on product batch size and quality risk level (such as key components/non-key components). This avoids inefficiency caused by "100% inspection" or quality omissions caused by "insufficient sampling". At the same time, uniformly incorporate information such as sampling rules, inspection items, and requirements for recording judgment results into the Inspection Operation Guidance Document. This ensures that inspectors operate in a standardized manner, reduces the impact of human subjective judgment, and realizes "rule-based and traceable" quality verification.
5. Formulation of Preliminary Response Plans for Quality Anomalies: Improving "Rapid and Efficient" Risk Handling
Formulate preliminary response processes in advance for potential quality anomalies (such as out-of-tolerance measurement data and unqualified products found in sampling): clarify the responsible persons for anomaly reporting (e.g., team quality inspector → quality supervisor), emergency handling measures (e.g., suspending production of the process, isolating suspicious products), and directions for cause investigation (e.g., equipment failure, raw material problems). This prevents the expansion of quality problems due to delayed anomaly handling, minimizes quality losses, and ensures the stability of the production process.
