Introduction to DataMatrix Codes

In a world where legal requirements for product liability and quality assurance are becoming increasingly stringent, the unique identification and traceability of components and products, also known as traceability, is becoming increasingly important. The DataMatrix code (DMC) plays a crucial role here, as it is a proven method for marking and tracking components. Originally developed for the automotive industry, the DataMatrix code has now established itself as a versatile tool in various industries.

Structure and encryption of a DMC

The DataMatrix code consists of square or rectangular fields with matrix-like points or squares for encrypting the information. This encryption technique enables a high density of information in a very small space. An important aspect is error detection and correction, which is ensured by additional data words. The number of correctable reading errors is limited not by the number of incorrectly read points, but by the number of incorrectly read data words. This property of the code makes it robust against reading errors, especially when marking components directly on metal.

The global standard today is encryption using the Reed Solomon algorithm with the code ECC 200 (Error Checking and Correction level 200). This code is also used by BORRIES as the default setting.

When encrypting alphanumeric information (127 different possible characters, letters, numbers and special characters), a ‘data word’ of 8 bits, i.e. 1 byte in length, is used for each character. If only digits are used as characters, 2 digits are encrypted in one data word. This means that, for the same code size, significantly more purely numerical characters can be encrypted than with an alphanumeric character set.

Error correction for data matrix codes

The ‘useful redundancy’ for error detection and correction is achieved by inserting and using additional data words. It should be noted that the often-cited statement ‘up to 25% of reading errors can be corrected’ is slightly misleading, as it refers to individual bits and not to data words. However, certain errors in engraved codes on metal are conducive to the special properties of the code. Due to the geometrically close proximity of the points in a data word, there is a greater probability that neighbouring points in a data word will be disturbed, which leads to effective error detection and correction.

Areas of application and advantages of the Data Matrix code

The use of Data Matrix codes for component traceability offers numerous advantages, including efficient marking and traceability of components, high information density and robustness against reading errors. These characteristics make the DataMatrix code an ideal solution for demanding applications in various industries, including the automotive industry, electronics industry and medical technology. GS1 standards for labelling and readability are supported by DataMatrix and ensure globally uniform coding.

Conclusion

The use of data matrix codes for component identification and traceability offers numerous advantages in terms of efficiency, reliability and compliance with legal requirements. By adapting to specific requirements for needle-punched codes and using specialised verifiers and readers, stable and reliable systems can be implemented that enable seamless traceability and quality assurance.