Cleaning validation of pharmaceutical manufacturing equipment is required by legislation. Generally, wet chemical techniques are employed using swabbing and/or rinse sampling methods. These are generally either selective and time consuming, or less selective and give results in a shorter period. The infrared reflection absorption spectroscopy (IRRAS) technique explored here attempts to deliver accurate, selective surface contamination information in real time to complement current methods and reduce down-time. The IRRAS instrument used in this research is a Fourier transform infrared (FTIR) spectrometer coupled by an IR fibre-optic cable to a grazing-angle sampling head with a fixed incidence angle of 80°. The introduced flexibility permits collection of in situ spectra from contaminated surfaces. Calibration models are developed using the multivariate, linear partial least squares (PLS) statistical method. The research focuses on sodium dodecyl sulfate (SDS), a model cleaning agent, on metal (aluminium and stainless steel) and dielectric (glass, EPDM and silicone) surfaces. The effects of surface finish are investigated for SDS on stainless steel. Calibrations for SDS and paracetamol in the presence of each other on glass surfaces are examined, as well as a common industrial cleaner (P3 cosa® PUR80) on polished stainless steel. For the calibration sets in this thesis, RMSECV values were < 0.41 µg cm⁻², corresponding to conservative surface residues detection limits of better than ~0.86 µg cm⁻². However, RMSECV values depend on the calibration loading range, and the detection limits were typically ~0.2 µg cm⁻² for loading ranges 0-2.5 µg cm⁻². These are below visual detection limits, generally taken to be 1-4 µg cm⁻², depending on the analyte and substrate. This shows that IRRAS is a viable method for the real-time detection and quantification of surface contamination by surfactants and active pharmaceutical ingredients on metals and dielectrics.