Quality control plays a crucial role in the success and longevity of apparel manufacturing. It not only guarantees that customers receive products aligning with their expectations but also enhances operational efficiency, cost-effectiveness, and the overall triumph of the brand in a competitive market.
Let’s discuss two strategies we could use for quality management.
(Graph 1) Example of SPC Chart
Let's consider an example related to the production of women's bras.
Scenario: Monitoring the Length of Bra Straps
Objective: Ensure that the length of bra straps produced in a manufacturing process remains within specified limits.
1. Enter AQL Level:
Let’s discuss two strategies we could use for quality management.
Statistical Process Control (SPC).
One of the effective methods to monitor and control quality is to use Statistical Process Control (SPC). This involves using statistical methods to monitor and control a process to ensure it operates efficiently and consistently. One common tool used in SPC is the control chart.
(Graph 1) Example of SPC Chart
Let's consider an example related to the production of women's bras.
Scenario: Monitoring the Length of Bra Straps
Objective: Ensure that the length of bra straps produced in a manufacturing process remains within specified limits.
Steps for Implementing SPC
1. Data Collection:Regularly measure the length of bra straps during the production process. For our example, let's say this is done hourly.
2. Data Analysis:
2. Data Analysis:
Record the measurements and calculate the mean (average) and standard deviation for each set of measurements. The mean represents the central tendency, and the standard deviation indicates the variability.
3. Control Chart Creation:
3. Control Chart Creation:
Create a control chart with time (hourly measurements) on the x-axis and the length of bra straps on the y-axis. Plot the mean and upper and lower control limits based on the calculated standard deviation.
4. Control Limits:
4. Control Limits:
Establish control limits based on the acceptable range for the length of bra straps. Typically, control limits are set at ±3 standard deviations from the mean.
5. Monitoring:
5. Monitoring:
Regularly update the control chart as new measurements are taken. If a data point falls outside the control limits or shows a significant trend, it indicates a potential issue with the process.
6. Interpretation:
6. Interpretation:
A point outside the control limits may suggest a special cause variation, such as a machine malfunction or a change in materials. Investigate and address the root cause. If points show a consistent trend or pattern within the control limits, it may indicate common cause variation, suggesting the process is stable and predictable.
Regularly updating and interpreting the control chart allows the production team to identify issues early, take corrective actions, and maintain the quality of bra straps within the specified limits. This example illustrates how SPC can be applied to monitor and control various aspects of a manufacturing process.
The AQL is determined through a balance between the manufacturer's desire for higher quality (lower AQL) and the cost of inspection and production. AQL always depends on factors such as the complexity of the design, the materials used, and the brand's quality standards.
Typically, companies will set their AQL based on their quality control policies and customer expectations. Common AQL levels used in the industry might range from 0.1% to 4%, meaning that, for example, 95% or more of the products should be defect-free, and only a limited percentage (0.1% to 4%) of products would be allowed to have defects.
Regularly updating and interpreting the control chart allows the production team to identify issues early, take corrective actions, and maintain the quality of bra straps within the specified limits. This example illustrates how SPC can be applied to monitor and control various aspects of a manufacturing process.
Acceptable Quality Level (AQL)
The Acceptable Quality Level (AQL) is a standard used in quality control to define the maximum number of defective items acceptable in a sample from a production batch. The AQL is usually expressed as a percentage or a ratio. The specific AQL for a product can vary based on the brand, manufacturer, and industry standards.The AQL is determined through a balance between the manufacturer's desire for higher quality (lower AQL) and the cost of inspection and production. AQL always depends on factors such as the complexity of the design, the materials used, and the brand's quality standards.
Typically, companies will set their AQL based on their quality control policies and customer expectations. Common AQL levels used in the industry might range from 0.1% to 4%, meaning that, for example, 95% or more of the products should be defect-free, and only a limited percentage (0.1% to 4%) of products would be allowed to have defects.
AQL calculator
Tetra Inspection has published an AQL calculator on its website which is designed based on the above AQL tables and standards (Inspection type, Inspection level and AQL level). You can use that AQL calculator online if you need to determine these parameters for an inspection and quality audit.
- Sample Size,
- Accept points and
- Reject Points
Step-by-step explanation of how an AQL sample calculator works:
Start by entering the desired AQL level into the calculator. AQL represents the maximum acceptable percentage of defects in the production lot.
2. Enter Lot Size:
2. Enter Lot Size:
Input the total number of items in the production lot. This is the quantity of products you want to inspect.
3. Select Inspection Level:
3. Select Inspection Level:
Choose the appropriate inspection level (I, II, or III) based on the desired level of scrutiny. Inspection levels are defined by international standards like ISO 2859-1, and they vary in terms of the sample size and acceptance criteria.
4. Select Code Letter:
4. Select Code Letter:
The inspection level and lot size together determine a code letter (e.g., A, B, C, etc.). This code letter is used to find the sample size and acceptance criteria in standard AQL tables.
5. Retrieve Sample Size and Acceptance Criteria:
5. Retrieve Sample Size and Acceptance Criteria:
Using the code letter and the AQL table associated with the chosen inspection level, find the corresponding sample size (usually denoted as "n") and the acceptance number (c), which is the maximum allowable number of defects in the sample.
6. Conduct Inspection:
6. Conduct Inspection:
Inspect a random sample of items from the production lot according to the specified sample size. Record the number of defective items found in the sample.
7. Determine Acceptance or Rejection:
7. Determine Acceptance or Rejection:
Compare the number of defects found in the sample to the acceptance number (c). If the number of defects is equal to or less than the acceptance number, the lot is accepted. If it exceeds the acceptance number, the lot may be rejected.
Sources:
Conclusion:
The AQL sample calculator ensures that you have a statistically valid sample size for inspection, and it helps in making decisions about accepting or rejecting the entire production lot based on the findings from the sample. Keep in mind that the specific AQL tables and calculations may vary depending on the standard used (e.g., ISO 2859-1) and the industry requirements. Always refer to the relevant standard or use industry-specific calculators provided by quality control organizations.Sources: