In:
Journal of Industrial Engineering and Management, Omnia Publisher SL, Vol. 13, No. 3 ( 2020-10-08), p. 514-
Abstract:
Purpose: to reduce operating costs when performing agricultural mechanized work.Design/methodology/approach: The development of the desired economic and mathematical model of the optimal MTA distribution by type of work is based on the above condition it is necessary to plan the work of not tractor brands indicating their number, but each tractor individually.Findings: It is known that the availability of equipment varies during the season, so it was studied in dynamics. In this regard, to solve this problem, neural-network simulation was first used. As a result of the search, a network of the type of radial basis function was obtained that best describes these dependenciesResearch limitations/implications: the authors developed a fundamentally new mathematical model for optimizing the use of technology, which, unlike existing ones, allows to:- plan the operation of each tractor individually;- designate the so-called “mandatory tractors”, that is, those that the user, at his discretion, would like to assign to a particular operation or vice versa, would like the tractor operator not to work on this operation.Originality/value: Thus, the scientific novelty of the work performed are:- a technique for operational planning of work and increasing the efficiency of using the MTA, taking into account the technical condition of the tractors, the specific conditions for their functioning and the work experience of the machine operator.- a mathematical model for solving the problem of the optimal distribution of MTA by type of work and the mathematical apparatus for its implementation;- a technique for adjusting the performance of the MTA, taking into account the experience of the tractor driver, the service life and technical readiness of the tractor.
Type of Medium:
Online Resource
ISSN:
2013-0953
,
2013-8423
Language:
Unknown
Publisher:
Omnia Publisher SL
Publication Date:
2020
detail.hit.zdb_id:
2495074-9
SSG:
3,2
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