Legibility of machine readable codes used for gas turbine part tracking

Abstract

Gas turbines are comprised of many parts, which are often expensive and required to survive a harsh environment for significant periods (with or without reconditioning). To differentiate between parts, and facilitate keeping accurate historical records, they are often given a unique identification number. However, manually recording and tracking these is difficult. This has led to increased adoption of machine readable codes to help reduce or eliminate many of the issues currently faced (mostly human error). The harsh environment of a gas turbine means that typical methods of applying machine readable codes, such as printed adhesive labels, are simply not durable enough. Direct part marking (DPM) is necessary to ensure the desired longevity of the code over the part's useful life. The research presented in this thesis was approached in two main phases. Firstly, the author sought to investigate the technical solutions available for the elements required of a part tracking system (encoding, marking and scanning). This included identifying the characteristics of each and their compatibility with one other (across elements). In conjunction with Alstom, criteria were identified that were used as a basis for comparison so that the preferred technical solutions could be determined. The outcome of this process was enhanced by the author developing a number of industrial contacts experienced in implementing part tracking systems. The second phase related to the legibility of the codes. The harsh environment of a gas turbine results in surface degradation that may in turn reduce the legibility of any machine readable codes present. To better understand why read failures occur, the author _rst looked to the scanning process. Data Matrix symbols (marked via dot peen) require the scanner to capture an image for processing. Image capture is typically achieved using a charge-coupled device (CCD), each pixel of which induces a charge proportional to the incident illumination. This illumination is received via reflection from the surface of the part and hence the Data Matrix marked on it. Several surface features were identified that govern the way in which the part surface will reflect light back to the scanner: surface roughness, dot geometry and surface colour. These parameters are important because they link the degradation mechanisms occurring { broadly categorised as deposition, erosion or corrosion { with the scanning process. Whilst the degradation mechanisms are distinctly different in their behaviour, their effect on surface reflectivity is common in that they can all be characterised via the surface parameters identified. This was deduced theoretically and so the author completed tests (utilising shot blasting to change the surface roughness and oxidation to change its colour, independently) to show that these surface parameters do indeed change with the introduction of surface degradation and that there is a commensurate change in symbol legibility. Based on the learning derived with respect to Data Matrix legibility, the author has proposed a framework for developing a tool referred to as a Risk Matrix System. This tool is intended to enhance the application of part tracking to gas turbine engines by enabling symbol durability to be assessed based on the expected operating conditions. The research presented is the first step in fully understanding the issues that affect the legibility of symbols applied to gas turbine parts. The author's main contribution to learning has been the identification of knowledge from various other sources applicable to this situation and to present it in a coherent and complete manner. From this foundation, others will be able to pursue relevant issues further; the author has made a number of recommendations to this effect.