(1) Background: A proposal for the automatic control of sugar cane honey factories based on simulation with real data is presented. (2) Methods: The P&ID diagram of the artisanal process is designed, as well as the measurement and control systems of the different process variables. A data acquisition and monitoring system is proposed with all the required equipment. Using GNU Octave software, the process was simulated, where the transfer functions and parameters of the different stages were determined. The transient responses of these systems are determined before step-jump type disturbances, as well as that of the controllers. (3) Results: A correct adjustment of the controllers is obtained, indicating those that work in a stable way before disturbance variations in the real ranges of plant work. (4) Conclusions: Simulation of controllers before different forcing functions in the ranges of the operating parameters allowed for establishing dynamic responses of each one, demonstrating that they are capable of adjusting the value of the variable of interest or the control, and determining control of the main operating variables.

A local data acquisition, processing and storage system were implemented by means of an open source micro-controlled development card. To continuously measure the variables of the cane honey production process, it was performed using five temperature sensors, pH sensor and a level sensor. Each sensor was associated with a component set with its respective upper and lower reference values, during the processing of a batch of product. The main objective was to determine the effectiveness of using sensors and wireless communication technology to monitor operational parameters, in real time. In general, the recorded temperature, pH and level data obtained from sensors corresponded closely to the changes that occurred in the process, and the wireless communication nodes developed successfully measured and monitored the temperature, pH and level readings in real time. The study also found that the temperature, pH and level readings obtained by the sensors began to standardize more closely within the upper and lower limits. Furthermore, operational parameters could be reasonably predicted by applying a statistical model to measure temperature, pH and level. The present study also found that the operational parameters analyzed showed variability with its consequent effect on the quality of the final product. The findings of this study should serve as the first step towards any future research and development that may take place in the field of agro-industrial process design