In this work, the efficiency of the LUMBA UVES pipeline for processing of spectroscopic observations is tested by use on 23 high-resolution spectra of the open star cluster M67. An abundance trend discovered by Gavel et al. (2019) concerning iron abundances of giant and sub-giant stars of that cluster is examined. An initial run for a set of ”Gaia FGK benchmark stars”, as described in Blanco-Cuaresma et al. (2014) and Heiter et al. (2015) helps inspect the structure, method and output of the pipeline. Through Python language programming, processes are greatly automatized and the pipeline is run for a total of 460 weak and strong iron lines of our 23-star sample. The line fitting and efficiency of the pipeline is appreciated by statistically analyzing the results and looking into individual discrepant ones. The abundance trend is reproduced while using FeI lines, unlike runs using FeII lines. Trends in abundance over line strength plots also hint at bias through the Gaia-Eso Survey (GES) microturbulence relation. Using internal Data Release 6 (iDR6) and LUMBA-derived starting parameters, log(g) - Teff plots of our sample stars agree with a previously established 4.3 Gyr cluster age. An alternate run is performed for those stars, using LUMBA-derived starting parameters. The choice of starting parameters does impact abundance derivation, but is not the primary source of persistent systematic discrepancies.