In the age of digitization and industry 4.0, the use of printed formats for quality data collection is not an efficient way. Data capturing on papers and filling printed formats by quality checkers while checking garments become an age-old technique. By using quality control applications (either on mobile or tablet), you can save time in data capturing with many additional benefits.
In this article, I will brief you about the Statistical Quality Control (SQC) application used by garment factories. And SQC solution designed for the apparel manufacturing sector. I have implemented one such application in a couple of garment factories. There are a couple mobile-based SQC applications, available for the garment manufacturing industry which will be shown in the next article.
Benefits of using Real-time and mobile application for Quality Checking
The major benefits of using a mobile application in roving quality control and end-of-line quality checking in garment manufacturing included the following.- Improve the process of quality control and faster decision making
- Eliminate repeat data entry (in present scenario - first you capture data on the paper format and then entering data to excel sheet and then again making quality reports with data)
- You get quality data on real-time
- Capturing an image of the defect and storing the same for future reference and for discussion
- Quality KPIs ready for quality management
- Identifying the training need of the operators for making a quality garment
- In-depth data capturing without spending much time
- In-depth data analysis for finding root causes of quality issues
- You can follow up the quality performance of a factory remotely.
How does this application work?
The roving SQC tool is an android application. You need tablets to use this application. Each quality checker needs a user login. A user needs to open the application and need to login to the SQC application.You decide how you like to use the SQC application – you can use the same application for roving quality checking, inline checking but in a fixed checkpoint, or end-of-line quality checking. The same application can be used for different types of checking in a production line.
When a checker starts checking garment quality in a line (let us say in-line quality checking), they can check garments by sewing operators or by bundle number.
Quality checking by sewing operator:
The system, I am talking about is integrated with the Shop Floor Control system. So, when the quality checker decides to check garment by sewing operator, he needs to enter the sewing operator number. The device will automatically pick the bundle number on which the operator is currently working. It will identify the operation name (and operation code) and the number of garments available in that bundle (bundle quantity).In quality checking, one most important factor is sample size – the number of pieces you are checking from a lot (or number pieces need to be checked per operator per visit).
Here, the application will show the sample size – full bundle qty by default (or as defined by the factory, like in percentage of bundle quantity). In case you are not checking the full bundle quantity, you can change the sample size manually. Let us say you checked 7 pieces out of 20 pieces bundle. Here sample size is 7 pieces.
When you check garments, your aim is to find if there are any defects in the checked garments. The application will show you a pre-defined list of defects that normally occurs in your products. (See the below example).
Screen-1: List of defects when entering defects (Source: BlueCherry Roving SQC App)
Digital Reports
Assume that checker founds 3 defects (seam puckering, jump stitch, and broken stitch) in the 7 checked pieces. For capturing defects data, the checker needs to select defect types from the list (dropdown menu) that he found in those 7 garments. Enter the number of defects found in each defect type. The quality checker needs to enter data defect type wise (one after another). After adding defect-counts by defect type, the checker needs to enter the number of defective pieces found in those 7 pieces. Let us say, checker found these 3 defects in 2 garments. This means the checker got 2 defective garments. Then submit the data.
By submitting data, the system captures operator number, bundle number, style and order number, sample size (checked garment quantity), defective units, defect types, and the number of defects. All these data are captured by date, by line number, and by checker number (name). You can track when the checking is performed and when the defect is generated (with the date and time stamp).
By submitting data, the system captures operator number, bundle number, style and order number, sample size (checked garment quantity), defective units, defect types, and the number of defects. All these data are captured by date, by line number, and by checker number (name). You can track when the checking is performed and when the defect is generated (with the date and time stamp).
Checking garments by bundle number.
If you miss checking of a bundle in one specific operation when an operator working on it, not to worry, you can check garments by the bundle. To start checking the bundle, enter the bundle number. Check the garments and when you find some defects and identify operations where you get the defects. The defect can be operation-specific or non-specific (stain, fabric defects).
Next step – the checker needs to select the operation in which he found the defect and then select the defect type from the list and enter the number of defects found for the selected defect type. If needed checker can capture the image of the defects. When an operation is selected, the system identifies the operator number who stitch the garment for that specific operation.
So, whether you check garment and capture quality data by bundle number or by operators, you know the source of the defect, employees who performed the defects. This much in-depth data capturing is not possible by manual data capturing for garment quality checking and inspection.
Next step – the checker needs to select the operation in which he found the defect and then select the defect type from the list and enter the number of defects found for the selected defect type. If needed checker can capture the image of the defects. When an operation is selected, the system identifies the operator number who stitch the garment for that specific operation.
So, whether you check garment and capture quality data by bundle number or by operators, you know the source of the defect, employees who performed the defects. This much in-depth data capturing is not possible by manual data capturing for garment quality checking and inspection.
Data analysis and Reports:
After capturing defects data on the tablet, you can see the checker’s performance on the application. You can view quality issues in the line. The system has some standard reports on the tablet and web application. You can see defects data hour wise.- You can prepare Line wise, Date wise DHU reports
- You can prepare a Pareto chart of defects for each line and each style.
- You can make custom reports the way you want to see the quality performance.