Decision support system for technological maintenance of seeding machines

Abstract

In this paper, we consider information support for decisionmaking in technological maintenance of agricultural machines before and during technological operations that guarantee their high quality and contribute to improving production efficiency: increasing crop yields up to 30%; increasing shift productivity by 10⋯ 12%; reducing fuel consumption per unit of work performed by 5⋯ 8%; reducing downtime due to technical reasons up to 20%. The authors have developed an information and logical model for decision support that allows them to select the best option for carrying out technological maintenance of agricultural machines depending on the current state of machine's components and mechanisms and specified agro-technical requirements. To implement the information and logic model, the software environment of the CLIPS expert system is used, including a full-fledged object-oriented COOL language. The model was tested on the example of technological maintenance of seeding machines.