###### Abstract
Standard operating procedures are often time consuming, require environmentally problematic solvents and agents, and therefore new alternatives are sought. For example, the Spectro FDM Q600 Fuel Sniffer (Fuel Dilution Meter) was developed in collaboration with the US Navy to determine the dilution of motor oil with petrol, diesel and other hydrocarbons. This device uses a built-in surface acoustic wave sensor to measure the concentration of fuel vapours present in the atmosphere above the oil sample [22]. Different types of sensors are also designed to monitor viscosity [23; 24]. A simple, inexpensive and reliable capacitive sensor as an indicator of the end of life of motor oils was proposed by [PERSON] et al. [25]. This sensor measures the permittivity of the oil samples used, which correlates with their oxidation, nitration and sulfation. An overview of lubricant condition sensors for online machine condition assessment was published by [PERSON] et al. [26]. [PERSON] et al. [1] designed laboratory test equipment suitable for monitoring the efficiency of oil filters and evaluating the technical life of motor oils. Differential FTIR spectroscopy is currently commonly used for the purposes of OCM-monitoring the thermal and oxidative degradation of motor oil, reducing the content of additives and the penetration of contaminants into the oil filling. With the development of information technology and the expansion of spectrometer software with multivariate mathematical and statistical software, predictive models have recently begun to develop from which several quality parameters of crude oil [27; 28], lubricating oils [29] and fuels [30; 31] can be obtained from a single spectrum, which can have both chemical and physical nature (e.g., viscosity, viscosity index, density, octane number, cetane number, etc.). The most common multivariate methods for evaluating entire spectral regions include Principal Components Analysis (PCA) [32], Partial Least Square (PLS) [33], Interval-PLS (iPLS) and Principal Components Regression (PCR) [34]. Viscosity [5], Total Base Number (TBN) [35] and Total Acid Number (TAN) [36] are motor oil parameters that are evaluated for both new and used motor oils. For this reason, FTIR chemometric models have been proposed as an alternative to the standardized determination of TBN and TAN by potentiometric titration, which is time consuming and requires the preparation of reagents [37; 38; 39]. Another possibility for the determination of TBN and TAN is the thermometric determination according to ASTM D8045, therefore [PERSON] et al. [40] verified the possibility of an alternative determination of the thermometric determination of these parameters based on FTIR in combination with chemometrics. [PERSON] et al. [41] developed predictive models for the determination of TAN oils (SAE 50) used in aircraft turbine engines using IR data and PLS Regression, Projection Pursuit Regression (PPR), Support Vector Machines (SVM), Linear Models (LM) and Random Forest (RF). In the case of new lubricants for various applications, [PERSON] et al. [29] tested the possibilities of using advanced chemometric methods in conjunction with FTIR spectroscopy to determine their selected quality parameters. No multivariate method gave satisfactory results when predicting kinematic viscosity at 40 \({}^{\circ}\)C and 100 \({}^{\circ}\)C. [PERSON] et al. [42] achieved excellent results in the validation of the FTIR-PLS model in the range of 3000-600 cm\({}^{-1}\) for the prediction of kinematic viscosity from derived spectra of new lubricating oils intended for machine motors and machines. [PERSON] et al. [43] compiled and validated the FTIR-PLS model to determine the viscosity index of new lubricating oils from 81 different manufacturers/brands in Brazil. For the purpose of predicting the kinematic viscosity at 40 \({}^{\circ}\)C of used TURBO SAE 15W-40 motor oils, which are suitable for CI engines, [PERSON] et al.