ISSN 1991-2927
 

ACP № 3 (65) 2021

Author: "Andrei Alekseevich Pertsev"

Andrei Alekseevich Pertsev, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Head of a department of FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.A. Pertsev,

Aleksandr Nikolaevich Podobrii, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Deputy Chief of a department of FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.N. Podobrii,

Iuliia Aleksandrovna Radionova, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Lead Programming Engineer at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of automated workflow systems, intelligent technical documentation storage bases and systems for statistical analysis of supplier appraisal; research interests are in the field of electronic document management, archival depositories, statistical data analysis, decision support systems. e-mail: julia-owl@mail.ruI.A. Radionova

The calculation model of hardware and software system production period designed by developing companies65_9.pdf

It is relevant for a developer of hardware and software systems to assess the duration of development in advance and determine the main factors influencing on its success. Bulk production or bulk production with little changes can be assessed based on the experience. However, when making preliminary assessment, some factors that had not a great effect before may not be considered. The article describes an approach to calculate the duration of hardware and software system development based on analogues, statistics and factors effecting the production. At the same time, it should be noted this method provides only a preliminary assessment and its usage requires additional s.

Duration of production plan development, neural net, small-scale manufacturing, design production, machinery, production capacity, operation flow statistics.

2021_ 3

Sections: Computer-aided engineering

Subjects: Computer-aided engineering, Information systems.



Andrei Alekseevich Pertsev, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Head of a department of FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.A. Pertsev,

Aleksandr Nikolaevich Podobrii, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Deputy Chief of a department of FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.N. Podobrii,

Iuliia Aleksandrovna Radionova, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Leading Software Engineer at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of automated workflow systems, intelligent technical documentation storage bases and systems for statistical analysis of supplier appraisal; research interests are in the field of electronic document management, archival depositories, statistical data analysis, decision support systems. e-mail: julia-owl@mail.ruI.A. Radionova

An approach to plan the production resources of a machine-building enterprise using neural networks64_7.pdf

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.

Production plan formation, neural network, small-scale manufacturing, project manufacturing, mechanical engineering, production capacity, operation performance statistics.

2021_ 2

Sections: Artificial intelligence

Subjects: Artificial intelligence.



Andrei Alekseevich Pertsev, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Head of an department at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA. A. Pertsev

Aleksandr Nikolaevich Podobrii, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Deputy Chief of a department at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.N. Podobrii

Iuliia Aleksandrovna Radionova, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Lead Programming Engineer at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of automated workflow systems, intelligent technical documentation storage bases and systems for statistical analysis of supplier appraisal; research interests are in the field of electronic document management, archival depositories, statistical data analysis, decision support systems. e-mail: julia-owl@mail.ruI.A. Radionova

Material scheduling to provide manufacturing in machine industry63_5.pdf

The article describes an approach to the material scheduling to provide manufacturing by machinery designers. The approach is based on the statistics of material consumption over the last periods and on manufacturing sequence. The article considers information technology alternatives of production reserve planning. The authors propose the model of material support based on a time series analysis. They describe a study scheme and a database structure for calculating by the model developed. The algorithm steps of data analysis, modeling of time series and resulted VS test values comparison are described in details. The article defines an experimental calculation to test the model validity and diagrams to compare the time series of the main and auxiliary material sample pieces. The programmed calculations are given as an additional module for interactive web resource and are implemented through T-SQL.

Manufacturing plan formation, time series, critical path, scheduling network, material, resources, project manufacturing, mechanical engineering, capacity, statistics of operations fulfilled, shiftwork scheduling.

2021_ 1

Sections: Information systems

Subjects: Information systems.



Andrei Alekseevich Pertsev, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Head of department at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.A. Pertsev,

Aleksandr Nikolaevich Podobrii, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Deputy Chief of department at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the automated enterprise management system implementation. e-mail: mars@mv.ruA.N. Podobrii,

Iuliia Aleksandrovna Radionova, Candidate of Sciences in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Lead Programming Engineer at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of automated workflow systems, intelligent technical documentation storage bases and systems for statistical analysis of supplier appraisal; research interests are in the field of electronic document management, archival depositories, statistical data analysis, decision support systems. e-mail: julia-owl@mail.ruI.A. Radionova

The balanced production load of a machine-engineering organization62_6.pdf

The article deals with an approach to calculation of equipment, employee or work centers load during the production plan forming by machine engineering organizations. The calculations are based on the duration of manufacturing operations and the electronic structure of items, and provide the most balanced workload at the shortest time of production. The article describes the model of item production and the technique of production plan forming according to each work center with the set of calculation constraints. It also calculates the efficiency of an equipment load and time of production based on the current production plan. The calculation of load plan for work centers is provided by auxiliary software module of an interactive web-resource using the T-SQL.

Forming of production plan, critical path, network diagram, small-lot production, design production, machine manufacturing, capacity, statistics of operations flow, shiftwork scheduling.

2020_ 4

Sections: Information systems

Subjects: Information systems.



Andrei Alekseevich Pertsev, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, Candidate of Science in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Head of a department of Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’; an author of articles in the field of the implementation of management information and control system. [e-mail: mars@mv.ru]A. Pertsev,

Aleksandr Nikolaevich Podobrii, Federal Research-and-Production Center Joint Stock Company ‘Research-and-Production Association ‘Mars’, Candidate of Science in Engineering; graduated from the Faculty of Mechanics and Mathematics of Ulyanovsk State University; Chief Specialist at FRPC JSC ‘RPA ‘Mars’; an author of articles in the field of the implementation of management information and control system. [e-mail: mars@mv.ru]A. Podobrii

Production Planning of the Machine-building Enterprise 55_9.pdf

The article deals with an approach to the automated production planning of design organization that manufactures machine- building equipment calculating the assembly-unit manufacturing sequence based on the average duration performance of the technological operations and the electronic structure of the product. The manufacturing duration of all the assembly units is determined. The time margin of the technological operations implementation is calculated on the basis of the assembly unit critical-path method.A model of product manufacturing is described. An algorithm of work centers planning with a set of restrictions used in the calculations is presented. Operating rate is analyzed as well as production capacity of production departments is calculated on the basis of a statistical estimation of the manufacturing schedule in previous periods and product campaign. The software implementation of the plan is presented in the form of an interactive web resource, which uses the method of constructing summary tables.

Production planning, critical path, diagram network, small-scale production, project manufacturing, machine-building, production capacity, statistics of operation implementation, shift-day production planning.

2019_ 1

Sections: Computer-aided engineering

Subjects: Computer-aided engineering.



Vladimir Anatolevich Maklaev, Federal Research-and-Production Center Open Joint-Stock Company ‘Research-and-Production Association ‘Mars’, Candidate of Engineering; graduated from the Radio-Engineering Faculty of Ulyanovsk Polytechnic Institute; Director General of the Federal Research-and-Production Center Open Joint-Stock Company ‘Research-and-Production Association ‘Mars’; an author of articles in the field of CAD. [e-mail: mars@mv.ru]V. Maklaev,

Andrei Alekseevich Pertsev, Federal Research-and-Production Center Open Joint-Stock Company ‘Research-and-Production Association ‘Mars’, an external PhD student of the Computer Science Department of Ulyanovsk State Technical University; graduated from the Mechanics and Mathematics Faculty of Ulyanovsk State University; a department chief at FRPC OJSC ‘RPA ‘Mars’; an author of articles in the field of CAD. [e-mail: mars@mv.ru]A. Pertsev,

Petr Ivanovich Sosnin, Ulyanovsk State Technical University, Honored Worker of the Higher School of the Russian Federation, Doctor of Engineering, Professor; graduated from the Radio-Engineering Faculty of Ulyanovsk Polytechnic Institute; a head of the Computer Science Department at Ulyanovsk State Technical University; an author of numerous works in the field of conceptual design of computer-aided systems. [e-mail: sosnin@ulstu.ru]P. Sosnin

An Approach to a Personalized Designer Model Generation and Use 34_8.pdf

The paper presents tools for computer-aided generation of personalized designer models in an organization developing computer-aided system families. The implementation is oriented at design processes and an experience base is used for its information service.

Computer-aided design, experience base, personal job description, professional maturity.

2013_ 4

Sections: Artificial intelligence system

Subjects: Artificial intelligence, Computer-aided engineering, Information systems.


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