The Application of Barcode Technology in Electronic Factory Material Management - A Deep Dive into Chapter 25: Barcode Quality - ANSI/ISO Grading |
Executive Summary (Chapter 25 Preview) |
A barcode that cannot be read is not just an inconvenience - it is a production-stopping failure. In electronics manufacturing, where speed and accuracy are paramount, the quality of every barcode label is a critical parameter. This chapter explores the science and practice of barcode quality verification, focusing on the ANSI/ISO grading standards that provide an objective measure of print quality. We will examine how barcode verifiers measure parameters such as symbol contrast, modulation, defects, and decodability, and assign a grade from 'A' (excellent) to 'F' (failure). We will explain the minimum grade 'C' standard commonly enforced in electronics manufacturing and the quality control actions triggered by failing grades. Real-world examples from Lumileds, Interpower, and Stratix Corporation will illustrate how American and global electronics manufacturers deploy barcode verification to ensure reliable reads, reduce 'no-read' events, and maintain supply chain integrity. |
|
Chapter 25: Barcode Quality - ANSI/ISO Grading |
25.1 The Hidden Defect That Stops Production |
A barcode label in an electronics factory looks simple - a pattern of black bars on a white background. But its readability depends on a complex interplay of factors: print contrast, edge sharpness, dimensional accuracy, and the integrity of the quiet zones. A label that looks perfectly fine to the human eye may be completely unreadable to a scanner. It might have insufficient contrast, where the bars are not dark enough relative to the background. It might have excessive 'defects' - voids in the bars or spots in the spaces that confuse the decoding algorithm. It might have been printed with incorrect dimensions, where the bars are too narrow or too wide. |
These defects are not hypothetical. In the LED manufacturing facility of Lumileds in Penang, Malaysia, the company faced a significant challenge with barcode quality. The materials used for LED production came from various suppliers and countries, each using a different grade of laser marker to imprint 2D codes, resulting in variable print quality. The types of ceramics used were also different, further compounding the problem. Due to the miniature sizes of the components, each 2D code typically measured less than two millimeters. In addition, LEDs were put through an oven process reaching approximately 300 degrees Celsius, which sometimes caused distortion to the codes. The manufacturer's existing barcode scanning system could not deliver a 100 percent successful read rate due to these challenges . |
This is the problem that barcode quality verification solves. By measuring the print quality of barcodes against standardized criteria, verifiers can identify labels that are likely to fail in the field before they enter the supply chain. This prevents 'no-read' events that stop production, cause manual data entry errors, and lead to inventory discrepancies. |
|
25.2 What Is Barcode Verification |
It is important to distinguish between barcode reading and barcode verification. A barcode reader provides only a go/no-go indication - it either decodes the barcode or it does not. A barcode verifier, by contrast, follows a specified standard to not only give a finer indication of the quality of the code relative to an ideal code but is also able to give more information on why the quality is suffering . |
Verification is a proactive quality control measure. It is performed on printed labels before they are applied to components or shipped to customers. By catching quality issues at the source, the factory prevents downstream failures. Verification tells you how good the barcode is, not just whether it is readable today, but whether it will remain readable through the handling, shipping, and environmental stresses it will encounter. The primary goal of barcode verification is to ensure the broad acceptability and successful scanning of barcodes, regardless of where they were produced or are being scanned . |
|
25.3 The ANSI/ISO Grading Standards |
The ANSI/ISO grading standards are the international framework for barcode quality assessment. These standards define the methodology for measuring specific attributes of barcode symbols and deriving an overall assessment of symbol quality . |
25.3.1 ISO/IEC 15416: Linear Barcodes |
ISO/IEC 15416 specifies the methodology for the measurement of specific attributes of barcode symbols, defines a method for evaluating these measurements and deriving an overall assessment of symbol quality, and gives information on possible causes of deviation from optimum grades to assist users in taking appropriate corrective action . It applies to linear (1D) symbologies intended to be read using linear scanning methods. |
25.3.2 ISO/IEC 15415: 2D Barcodes |
For two-dimensional symbologies like Data Matrix and QR Code, ISO/IEC 15415 provides the relevant quality specifications . This standard includes parameters such as symbol contrast, modulation, fixed pattern damage, and axial non-uniformity. |
25.3.3 ISO/IEC 29158: Direct Part Marking |
For direct part marking (DPM) applications, where codes are laser-etched or dot-peened directly onto components, ISO/IEC 29158 provides specialized quality test specifications. It establishes alternative illumination conditions, new terms and parameters, modifications to the measurement and subsequent grading of certain parameters, and the reporting of the grading results. |
|
25.4 The Grading Parameters |
When a verifier analyzes a barcode, it measures several specific parameters. Each parameter is assigned a grade (A, B, C, D, or F), and the overall symbol grade is the lowest of the individual parameter grades - this is the 'weakest link' principle . |
25.4.1 Symbol Contrast (SC) |
Symbol contrast is the difference between the maximum and minimum reflectance values along the scan. If the SC is greater than 70%, this parameter is graded A. An SC measurement below 20% receives a grade of F . This parameter ensures there is sufficient difference between the dark bars and the light spaces for the scanner to distinguish them. |
25.4.2 Modulation (MOD) |
Modulation is the ratio of the minimum edge contrast to the symbol contrast. If the value is greater than 0.70, the parameter is given a grade of A, while a value less than 0.40 receives a grade of F . Modulation accounts for variation in contrast across the symbol - a barcode may have high overall contrast but poor contrast in certain areas, leading to reading errors. |
25.4.3 Defects |
Defects in the barcode result in ripples in the intensity measurements within a bar or space, measured as Element Reflectance Non-uniformity (ERN). The Defects measurement is the ratio of the maximum ERN in the scan to the Symbol Contrast. A Defects value below 0.15 is graded A, while a value greater than 0.30 receives an F . This parameter catches printing defects such as voids in bars or spots in spaces. |
25.4.4 Decodability |
Decodability is a measurement of the margin between the actual element widths and the maximum allowed element width variance. It indicates how much 'padding' is available before a scanner mis-categorizes a bar or space width. Values over 0.62 receive a grade of A, while those below 0.25 are graded F . This is a critical parameter for high-speed scanning, where precise timing is essential. |
25.4.5 Decode |
The scan reflectance profile is passed to the decode algorithm to see if it can read the code using the methods specified in the symbology specification. If the code cannot be read, this step is given a grade of F . |
|
25.5 The Grading Scale: From 'A' to 'F' |
Each parameter is graded on a letter scale, which corresponds to a numeric grade: |
A (4.0 to 3.5): Excellent - the barcode meets the highest quality standards. The A grade symbol is appropriate for systems when the barcode reader crosses the symbol only once or is limited to a single path, meaning that there is only a single chance to read the barcode with no opportunity to re-scan such as on high-speed conveyer systems . |
B (3.5 to 2.5): Good - the barcode is readable but may have minor issues. |
C (2.5 to 1.5): Passing - the barcode is considered acceptable and 100% scannable . A rating of C means that a barcode will scan on virtually any machine . |
D (1.5 to 0.5): Poor - the barcode is barely readable and may fail in some environments. |
F (0): Failure - the barcode cannot be decoded. |
The overall symbol grade is the lowest of the individual parameter grades. This is the 'weakest link' approach - a barcode is only as good as its worst parameter . |
|
25.6 The Minimum Grade 'C' Standard |
In electronics manufacturing, the minimum acceptable grade is typically 'C' (1.5). As Interpower's quality system demonstrates, each barcode label is checked by an analyzer that ensures they meet current national and international ISO (ANSI) parameters. If a label falls below the standard, it is rejected and reprinted . |
The 'C' standard is used because it provides a balance between quality and practicality. A grade 'C' barcode is readable by most scanners and will survive the typical handling and environmental stresses of the electronics supply chain. Anything below 'C' is considered unreliable and must be reprinted. |
|
25.7 Verification Equipment: Class A vs. Class B |
Barcode verifiers are classified according to their capabilities and accuracy . |
Class A systems are better suited for use in Quality Control labs rather than on the plant floor. They provide a much higher range of measurement accuracy and reporting depth. They often also include multiple optical, lighting, and aperture settings to allow a wider range of operating conditions and increased measurement accuracy. The computation time for the parameters reported by these systems is often quite long, though this is usually not a problem in laboratory applications . |
Class B systems are generally used on the plant or press floor. They include only a single lens, light, and aperture combination, though some provide simple plug-in scanners to allow changing these for different conditions. The information measured and reported by Class B systems is usually limited to the barcode grade along with measurements useful to the press operator for varying his equipment . |
|
25.8 Real-World Example: Lumileds - Verifying Small, Distorted 2D Codes |
The Lumileds case provides a compelling example of barcode verification in a challenging electronics manufacturing environment. Lumileds, an LED manufacturer based in Penang, Malaysia, produces 800 million units annually. The company faced significant challenges with the readability of 2D codes laser-etched on LED strips . |
25.8.1 The Quality Challenges |
The materials that are used for LED production come from various suppliers and countries. Each supplier uses a different grade of laser marker to imprint its 2-D codes, resulting in variable print quality. The types of ceramics used may also be different, further compounding the problem. Due to the miniature sizes of the components, each 2-D code typically measures less than two millimetres . |
In addition, LEDs are put through an oven process where electrical component leads are joined to the board via individual pad connections located on the board surface. The heat applied (approximately 300 degrees Celsius) to dry the soldered connections sometimes causes distortion to the codes . |
The manufacturer's existing barcode scanning system could not deliver a 100 percent successful read rate due to these challenges. Part of the problem can be attributed to the fact that some of the scanners initially deployed were handheld readers, which were not designed for high-speed barcode reading on fast-moving production lines . |
Whenever a 'no read' occurred, operators had to manually enter information which is disruptive to the entire manufacturing process. Furthermore, with the ramping up of production volume over time, the need for a reliable solution that could handle high speed volumes started to become increasingly apparent . |
25.8.2 The Verification-Driven Solution |
The manufacturer deployed DataMan barcode readers with advanced decoding algorithms. The readers had to be deployed at different production stages, and the implementation team worked with equipment suppliers like Siemens to mount the readers on the machines. The implementation team experimented with different levels of magnification, trained the software to read the small 2D codes, and tested different configurations for light intensity, exposure values, and lens distance . |
Some of the key features of the DataMan 300 barcode reader that was chosen for this application are its high resolution (1.3 megapixel) and flexible lighting options. The environment for this application required high resolution images for success, since barcodes were small. In addition, blue lighting was used for the application to ensure optimal read rates. The DataMan barcode reader enables users to control light intensity and has a bank of lighting that can be configured to be turned on bi-directionally, unidirectionally or from all directions . |
25.8.3 The Results |
After fine-tuning, the resulting image was of a better quality and had the strong contrast that was needed. This improved the overall performance of the reading operation from 90 percent to 100 percent. The production yield went up, and waste was significantly reduced . While Lumileds primarily deployed readers rather than verifiers, the case illustrates the importance of barcode quality for achieving high read rates in demanding environments. |
|
25.9 Real-World Example: Interpower - In-House Barcode Verification |
Interpower, a manufacturer of power system components, provides an example of how barcode verification is integrated into a quality management system. Interpower offers custom labeling services, including barcode labels, with quality checks performed by an analyzer . |
25.9.1 The Quality Check Process |
Each barcode label is checked by a quality system with an analyzer. The analyzer inspects the barcodes to ensure that they meet current national and international ISO (ANSI) parameters. The analyzer can determine contrast, modulation, decodability (deciphers the barcode itself), and checks for defects and blemishes. This ensures the barcode meets the requirements needed for global use and distribution . |
25.9.2 Grading and Reporting |
Each barcode label is graded with an A, B, C, D, or F. The best grade is an A which is the grade aimed for all barcodes. An A means the label will pass in all of the areas (contrast, modulation, decodability, no defects or blemishes). A scan analysis print out is available if the customer wants to see how the label is rated . The application standard used is ISO/IEC 15415/15416 . |
25.9.3 Customer Assurance |
Interpower's verification process provides assurance to customers that the barcode labels they receive will be readable in their own scanning systems. As Jeanie Norton, Interpower's MTO (Made-to-Order) Supervisor, states, 'Quality checks ensure that the labels meet the standard and the customer requirements' . |
|
25.10 Real-World Example: Stratix Corporation's Xaminer Pro |
Stratix Corporation, a leading provider of Managed Mobility Services in the United States, offers the Xaminer series of barcode verifiers. The Xaminer Pro, launched in 2024, represents the state of the art in barcode verification technology . |
25.10.1 Key Features |
The Xaminer Pro is a point-and-shoot verifier that can handle both one and two-dimensional barcodes in a single unit. It features an LED display of ANSI grade and Bar Tolerance, N.I.S.T. traceability, element detail analysis, ANSI/ISO and traditional grading, and one-touch hot keys for help, print, and UPC magnification . |
25.10.2 Compliance and Standards |
The Xaminer Pro complies with ISO/IEC 15416 and 15426. It also includes a corrugated option that adjusts symbol contrast per Fibre Box Association guidelines, making it suitable for a wide range of applications . All Xaminer Pro verifiers come equipped with expandable firmware to enable future upgrades . |
25.10.3 Industry Leadership |
'Our founders literally wrote the book on barcode verification when Stratix started in 1983. It's in our DNA, and we're proud that more than 40 years later, we're still the leader in the field,' said Gina Daniel-Lee, Stratix Vice President of Strategic Alliances and Partnerships. 'With the new Xaminer Pro, we're helping our customers meet all their verification needs for today and tomorrow' . |
|
25.11 The Role of Decoding Algorithms in Verification |
One of the key factors in successful verification is the use of advanced decoding algorithms. These algorithms are optimized to read barcodes that are damaged, low-contrast, or distorted. In the Lumileds case, the DataMan readers' ability to read small 2D codes was critical to achieving a 100 percent read rate . |
The importance of algorithms is particularly evident in the Context Mode features used by Cognex and other manufacturers. These features allow the system to 'memorize' the properties of codes, such as module and pixel sizes, effectively optimizing read-rate performance . This is a form of machine learning that improves performance over time. |
|
25.12 Verification in the Supply Chain Context |
Barcode verification is not just a factory-floor activity. It extends throughout the supply chain. Suppliers of components to electronics manufacturers are often required to meet specific barcode quality standards. If a supplier's labels fail verification, they may be rejected at receiving, causing delays and additional costs. |
The verification process ensures that labels are compliant from the point of origin. As Interpower demonstrates, a quality check at the time of printing can catch defects before they are shipped to customers . This prevents downstream problems in the factory and throughout the supply chain. |
|
25.13 The Future of Barcode Verification |
The future of barcode verification is moving toward even greater automation and intelligence. |
AI-Powered Verification: Machine learning algorithms will improve the accuracy and speed of verification, enabling real-time quality assessment on high-speed lines. |
Integrated Verification and Reading: The line between verification and reading is blurring. Smart cameras can now both verify and read barcodes in a single pass, providing both a quality grade and the decoded data. |
Predictive Quality Management: Verification data can be used to predict when a printer or marker is degrading, triggering maintenance before quality drops below the 'C' threshold. |
|
Detailed Summary of Chapter 25 |
This chapter has provided a comprehensive examination of barcode quality verification in electronics manufacturing, focusing on the ANSI/ISO grading standards that ensure reliable barcode readability. |
We began by establishing that a barcode that appears perfect to the human eye may be unreadable to a scanner due to print quality issues such as insufficient contrast, excessive defects, or incorrect dimensions. The Lumileds case illustrated this: variable print quality from different suppliers, combined with heat distortion from the oven process, caused read rates to drop below 100 percent . |
We distinguished between barcode reading (go/no-go) and barcode verification (detailed quality assessment). Verification follows specified standards to provide a fine indication of quality relative to an ideal code and to identify why quality is suffering . |
We explained the ANSI/ISO standards: ISO/IEC 15416 for linear 1D barcodes, ISO/IEC 15415 for 2D codes, and ISO/IEC 29158 for direct part marking (DPM) applications . We described the key grading parameters: symbol contrast, modulation, defects, decodability, and decode . Each parameter is graded from A to F, and the overall symbol grade is the lowest of the individual grades - the 'weakest link' principle . We explained the minimum grade 'C' standard commonly used in electronics manufacturing . |
We discussed verification equipment, distinguishing between Class A systems (high accuracy, for lab use) and Class B systems (for plant floor use) . We profiled real-world examples. The Lumileds case (Malaysia, with global impact) demonstrated how deploying advanced barcode readers with high-resolution imaging and flexible lighting improved read rates from 90% to 100% in a challenging LED manufacturing environment with variable print quality, miniature 2D codes, and heat distortion . Interpower (U.S.) showed how barcode verification is integrated into quality management, with each label graded A-F against ISO/IEC 15415/15416 and A being the target grade . Stratix Corporation (U.S.) launched the Xaminer Pro verifier in 2024, which supports both 1D and 2D barcodes and complies with ISO/IEC 15416 and 15426 . |
We also discussed the role of advanced decoding algorithms and Context Mode features that enable high-performance reading of damaged or difficult codes . We noted that barcode verification extends throughout the supply chain, with customers often requiring compliance from their suppliers . |
|
Finally, we looked to the future of AI-powered verification, integrated verification and reading, and predictive quality management. |
The bottom line is that barcode quality verification is an essential quality control practice in electronics manufacturing. By measuring print quality against standardized criteria and enforcing a minimum grade 'C' standard, factories can prevent 'no-read' events that stop production, cause manual data entry errors, and lead to inventory discrepancies. As the examples from Lumileds, Interpower, and Stratix demonstrate, both American and global manufacturers recognize that investing in barcode quality is investing in operational reliability and supply chain integrity. |
cs@easiersoft.com