A system comprising: at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of sound generated by a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs; at least one optical sensor configured to generate at least one image data signal indicative of the thermal spray system performing the process, wherein the at least one image data signal is real-time, near-real-time or continuous; and a computing device comprising: a transformation module configured to transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum; a machine learning module configured to determine, based on at least the plurality of control parameters, the frequency-domain spectrum, the at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning; and a control module configured to: determine, based on the relationship determined by the machine learning module, respective values of the plurality of control parameters configured to cause the thermal spray system to generate predetermined values of the plurality of process outputs, and control, based on the respective values of the plurality of control parameters, the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges by sending a control signal to the thermal spray system. at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of sound generated by a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs; at least one optical sensor configured to generate at least one image data signal indicative of the thermal spray system performing the process, wherein the at least one image data signal is real-time, near-real-time or continuous; and a computing device comprising: a transformation module configured to transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum; a machine learning module configured to determine, based on at least the plurality of control parameters, the frequency-domain spectrum, the at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning; and a transformation module configured to transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum; a machine learning module configured to determine, based on at least the plurality of control parameters, the frequency-domain spectrum, the at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning; and a control module configured to: determine, based on the relationship determined by the machine learning module, respective values of the plurality of control parameters configured to cause the thermal spray system to generate predetermined values of the plurality of process outputs, and control, based on the respective values of the plurality of control parameters, the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges by sending a control signal to the thermal spray system. determine, based on the relationship determined by the machine learning module, respective values of the plurality of control parameters configured to cause the thermal spray system to generate predetermined values of the plurality of process outputs, and control, based on the respective values of the plurality of control parameters, the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges by sending a control signal to the thermal spray system.