Proposals for reduction of the cost of ownership of agricultural machinery due to increase controllability and adaptability to diagnosis

¹ Federal Scientific Agro-Engineering Center VIM, 1 Institutsky proezd, 5, Moscow, 109428, Russia
² Russian State Agrarian University – Moscow Timiryazev Agricultural Academy, Timiryazevskaya str., 49, 127550, Moscow, Russia
³ Kaliningrad Research Institute of Agriculture, All-Russian Research Institute of Phypatothology (5 Institute Str., 143050, Bolshie Vyazemy, Odintsovsky district, Moscow region, Russia

^* Corresponding author: redizdat@mail.ru

Abstract

It is known that machinery in agriculture is used to perform work in optimal agricultural terms under difficult conditions, which requires constant improvement of approaches to determining the technical condition. Technical service is the main and most effective measure that ensures the maintenance of machines in working condition during the life cycle. At the same time, in order to objectively determine the technical condition of the machine, it is necessary to obtain an appropriate amount of data reliably describing this condition. Obtaining such data in the required volume will reduce the total cost of ownership and preserve the consumer properties of machines throughout the life cycle. As a result of the carried out research within the framework of the scientific topic "To develop a system of digital monitoring and diagnostics of the technical condition of agricultural machinery", projects were proposed to improve the controllability and adaptability to diagnostics to improve consumer qualities during the life cycle. The draft proposals are based on an analysis of the failure criteria for the complexity group, the existing Standards and Technical Documentation, as well as the capabilities of equipment manufacturers to carry out measures to manage reliability during the warranty and post-warranty periods of the life cycle equipment. During the study, special attention was paid to the possibilities of conducting non-selective diagnostics of components and assemblies using Predictive Maintenance Systems (PdM) to preserve the consumer properties of equipment.