This thesis investigates sensors and sensor data fusion to enable dynamically reconfigurable mobile processing plant and machinery. The ensemble of machines is considered to constitute a cyber physical system (CPS). Two main issues are addressed: sensors and processing algorithms to determine the position and orientation of the mobile equipment and systems to improve productivity of the machines. A new concept and its implementation to determine the relative position and orientation of the mobile elements of the plant is presented. It is based on ultra-wideband (UWB) sensors; however, the newly developed configuration does not require the installation of stationary infrastructure. Additionally, a new computation approach is presented; it is characterized with respect to the uncertainties of the determined locations, distance measurement s = 18.8mm, positioning s = 64mm in an industrial environment. The redundancy of the configuration and the newly developed calibration procedures make the UWB suitable for use in industrial environments. Thermal imaging and tensor polynomial processing concepts were applied to detect the trapping of ferrous material in the magnetic field of the Eddy current separator. The timely detection is used to preempt possible damage to the transport media from overheating of the trapped particles. Visual imaging is also applied to determine momentary material-throughput on the equipment; this is used to improve overall efficiency. Additionally, results are presented of a selection of sensors and sensor concepts, most notably linear microphone arrays. The data from these arrays are processed using phased acoustic computation methods. The aim is to determine the locations of sources of sound emanating from particles trapped in the field of the eddy current separator.