Methodology of the simulation modeling of maintenance technological processes
DOI:
https://doi.org/10.31734/agroengineering2024.28.233Keywords:
algorithm, technique, maintenance, operation, parameter, durationAbstract
The proposed technique takes into account various structural features of TP maintenance, such as restrictions on the sequence of operations and the arrangement of work areas within the service facility.
The modeling process establishes conditions for ensuring: 1. the implementation of key theoretical principles regarding the interdependence of different parameters involved in maintenance operations, including the maintenance front (f), the number of workers (u), and the equipment types (Kr). It also considers the interdependence of various indicators related to maintenance efficiency, such as the duration of the technological process (TT.P) and the utilization coefficients for labor (ƞu) and equipment (ƞr); 2. automated calculation of parameters and performance indicators related to maintenance efficiency and technical-economic metrics; 3. the generation of initial data required for synthesizing parametric series of production structures with varying productivity levels, thereby determining maximum and optimal productivity.
An automated design system has been developed within the NetBeans IDE environment for simulating the maintenance and repair of cars, tractors, mobile machinery, and their hydraulic systems. The initial data for modeling include the number of maintenance tasks (ETOs) and their characteristics, the work areas where these tasks are conducted, types of equipment, time norms for operations, and the priority of executing specific tasks. The aim is to find the minimum time (TT.P) required to complete N operations, given a distinct production and technological structure. This algorithm facilitates the creation of an operation schedule that minimizes the duration of the technological cycle while maximizing the utilization rates of workers and equipment. This scheduling must adhere to several constraints: first, only one operator and one type of equipment can perform an operation in a given work area at the same time, meaning that operations located within the same work area cannot be executed in parallel; second, the distribution of operations among performers and equipment must maintain the integrity of time and operational connections; and third, efforts should be made to minimize the loss of workers' time as they move around the site and between work areas.
The described algorithm is capable of conducting numerous random simulations to generate different solutions. Each solution varies because a uniform random variable generator is utilized to select the operations for execution.
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