Open AccessAN APPROACH TO PLAN THE PRODUCTION RESOURCES OF A MACHINE-BUILDING ENTERPRISE USING NEURAL NETWORKS
Author(s) -
Andrey A. Pertsev,
Aleksandr N. Podobriy,
Yuliya A. Radionova
Publication year - 2021
Publication title -
avtomatizaciâ processov upravleniâ
Language(s) - English
Resource type - Journals
ISSN - 1991-2927
DOI - 10.35752/1991-2927-2021-2-64-46-55
Subject(s) - artificial neural network , computer science , production (economics) , documentation , plan (archaeology) , sample (material) , industrial engineering , product (mathematics) , set (abstract data type) , software , resource (disambiguation) , manufacturing engineering , software engineering , database , artificial intelligence , systems engineering , data mining , engineering , operating system , programming language , history , computer network , chemistry , geometry , mathematics , archaeology , chromatography , economics , macroeconomics
Generally, this is the experience of production workers, economists, designers, etc. that used to get a preliminary assessment of feasibility of hardware manufacturing at an enterprise. For a preliminary assessment, it is enough to understand the complexity of the product and available analogues. At the same time, it is not always possible to calculate an accurate production time for the product due to the lack of a complete set of design and technological documentation. The article presents an approach to calculating the production time of hardware using neural networks based on existing data for previous periods and types of hardware using. This approach allows estimating the production time without using accurate data on the design and manufacturing technology. The article also describes the structure of neural networks and defines the training sample. Some experiments were conducted based on the sample data, which allowed determining the initial weight coefficients of the neural network. The software implementation is made in the form of an additional module for an interactive web resource and uses T-SQL.