Graphical Interfaces for Dynamic Supervision for Failures Prognosis using the AI-PLC Combinatorial Approach: The Case Study of Cameroon Breweries Mill

Abstract

The increasing complexity of industrial systems and the increasingly severe operating constraints have forced specialists to design, specify and operate modern industrial processes. These evolutions thus imply the development of "intelligent" supervisory and prognostic systems, for the improvement of the control of the processes and the realization of the maintenance actions. This article presents our contribution in the study and the development of an interface of supervision and failures prediction of the Carbomill (malt mill) of the Breweries of Cameroon. The methodological approach is based on the design of a graphical interface made under Vijeo and controlled by an PLC, programmed on Unity Pro XL and the use of an ANFIS neuro-fuzzy network as a prediction tool. The expected results lead at the end of the learning on the evaluation by an RMSE cost function of 0.2142.

Contribution to the study of the hydro-chemical characteristics of the lake ecosystem Dayet Er-Roumi, Morocco

“…The study of physicochemical quality and the assessment of surface water's trophic level allows us to discriminate and determine the mineral elements that deteriorate water quality and threaten aquatic life [4,5], It is the concentration of these elements that defines and illustrates the quality of water [4] and whether it threatens aquaculture life or not. These mineral elements are diverse, in a dissolved or suspended state (bicarbonates, sulfates, magnesium, sodium, calcium, phosphorus, potassium, nitrogen, iron, and aluminium), they arrive from soil and subsoil, wildlife, and vegetation; also they come from precipitation and runoff, as well as physical, chemical, and biological processes occurring in the body of water itself.…”