Multi-phase Flows (MPFs) exist in various chemical engineering and industrial processes and the research on monitoring MPFs is of great importance. In this research, electromagnetic sensing techniques in the monitoring of two industrial processes with MPFs are studied, namely Clean-In-Place (CIP) and industrial oil-water separation. In multifunctional food and detergent production lines, accurate identification of ending point of the cleaning process for the previous product is crucial to ensure product integrity. In this research, an optimization method with dynamic references based on Tikhonov regularization is proposed and validated by monitoring a lab CIP circuit with a commercial Electrical Resistance Tomography (ERT) system. The results prove that the proposed method is capable of accurately identifying the ending point of CIP process. Moreover, the comparisons made with several conventional image reconstruction algorithms illustrate that significantly improved inverse calculation results are obtained when the background conductivity largely differs from the reference conductivity. Additionally, the feasibility of this novel approach is discussed. Liquid-liquid separation is an important process in many chemical engineering applications. The ability of monitoring this process, in particular with a non-contact method is of high value. In this research, a novel sensing approach which adopts a differential electromagnetic inductive sensor (DEMIS) and an FPGA-based (field-programmable gate array) impedance analyser is proposed and implemented to monitor the separation processes of an oil-in-water liquid system. The inductive sensor has a concentric cylinder structure with its coils arranged differentially. It is optimised to achieve a homogeneous sensitivity distribution in the sensing region. Electrical models of the oil-saline separation processes are established. Experiments under different oil and saline fractions, different agitation speeds and durations are conducted to validate the capability of the system. Both simulation and experimental results have proved that the proposed system is capable of monitoring oil/water separation process non-intrusively and non-invasively with a relatively lower cost, higher reliability and less complex structure, comparing to existing techniques.