APPLICATION OF DEEP NEURAL NETWORK IN INTELLIGENT SYSTEM WITH PRODUCTION DASHBOARD

Tipo do ITEM

Artigo Ciêntifico

Título do Artigo

Descrição

The Lean Manufacturing process, also known as Lean Manufacturing, is a strategic methodology of action to reduce production waste, obtain product quality, reduce product delivery time to the customer and achieve the lowest number of defects. However, the company, in its electronic meter manufacturing process, does not have technologies that allow the implementation of this methodology, which brings the need for investment in this project, which has as main objective to develop an Intelligent System of Lean Manufacturing based on the requirements of a Manufacturing Execution Systems - MES, which allows or assists the decision-making process regarding Production Control and Management, through technologies such as: Artificial Intelligence, Internet of Things and Embedded Systems, aiming to reduce production costs and product quality. To achieve this objective, the following goals must be performed: Mapping of the requirements of the electronic meter production process, list the parameters of the manufacturing process to analyze and define the requirements for the Intelligent System that uses Artificial Intelligence algorithms, identify the bottlenecks of in such a way that it is possible to make improvements in the electronic meter manufacturing process, develop communication models using Program Application Interfaces - API together with Embedded Systems for data collection, develop the Intelligent System to transform data into real-time information with reports and scenario projections to identify failures or possible improvements with process statistics, validate the Intelligent System requirements to adapt the production control and management module in line with manufacturing and implement the system observing the test period. As an execution method, the PMBOK project management methodology will be used to guarantee deliveries in each phase, observing the incremental cycle for software development, for the development of the Intelligent System, the Django Pyhton framework will be used, in such a way that it meets the need accessibility and portability between different platforms, this framework will use the Front-End and Back-End stack Engines for data communication, three-layer design architecture and MVC pattern, encryption for sending and receiving data, Bootstrap for designing the interaction interfaces, Vue JS to create the interface events and Blade to integrate the models provided by the Back-End to the Front-End in an easy and productive way. The embedded systems for the electronic devices will be developed in C language through the VSCode environment, together with the communication interfaces. Finally, it is expected that the project meets the company's needs, that it improves the manufacturing process of the electronic meter by using the Intelligent System that uses Artificial Intelligence algorithms to generate results that determine viable solutions through previously programmed scenarios, which meet the demand to increase the maturity level of the process as it uses Industry 4.0 methods and technologies.

Abstract

The Lean Manufacturing process, also known as Lean Manufacturing, is a strategic methodology of action to reduce production waste, obtain product quality, reduce product delivery time to the customer and achieve the lowest number of defects. However, the company, in its electronic meter manufacturing process, does not have technologies that allow the implementation of this methodology, which brings the need for investment in this project, which has as main objective to develop an Intelligent System of Lean Manufacturing based on the requirements of a Manufacturing Execution Systems - MES, which allows or assists the decision-making process regarding Production Control and Management, through technologies such as: Artificial Intelligence, Internet of Things and Embedded Systems, aiming to reduce production costs and product quality. To achieve this objective, the following goals must be performed: Mapping of the requirements of the electronic meter production process, list the parameters of the manufacturing process to analyze and define the requirements for the Intelligent System that uses Artificial Intelligence algorithms, identify the bottlenecks of in such a way that it is possible to make improvements in the electronic meter manufacturing process, develop communication models using Program Application Interfaces - API together with Embedded Systems for data collection, develop the Intelligent System to transform data into real-time information with reports and scenario projections to identify failures or possible improvements with process statistics, validate the Intelligent System requirements to adapt the production control and management module in line with manufacturing and implement the system observing the test period. As an execution method, the PMBOK project management methodology will be used to guarantee deliveries in each phase, observing the incremental cycle for software development, for the development of the Intelligent System, the Django Pyhton framework will be used, in such a way that it meets the need accessibility and portability between different platforms, this framework will use the Front-End and Back-End stack Engines for data communication, three-layer design architecture and MVC pattern, encryption for sending and receiving data, Bootstrap for designing the interaction interfaces, Vue JS to create the interface events and Blade to integrate the models provided by the Back-End to the Front-End in an easy and productive way. The embedded systems for the electronic devices will be developed in C language through the VSCode environment, together with the communication interfaces. Finally, it is expected that the project meets the company's needs, that it improves the manufacturing process of the electronic meter by using the Intelligent System that uses Artificial Intelligence algorithms to generate results that determine viable solutions through previously programmed scenarios, which meet the demand to increase the maturity level of the process as it uses Industry 4.0 methods and technologies.

Língua do arquivo

inglês

Data da Publicação

Ano 2020

Palavra-chave

Lean Manufacturing

Manufacturing Execution Systems – MES

Intelligent Manufacturing Systems

Electronic Meters

Cyber-Physical Systems

Artificial Intelligence

Autores

Juarez da Silva Ramos Junior

Jandecy Cabral Leite

Marivan Silva Gomes

Railma Lima de Paula

Michael da Silva Carvalho

Ítalo Rodrigo Soares Silva

Paulo Oliveira Siqueira Junior

Ricardo Silva Parente

Luís Gabryel dos Santos Miranda

Local

ITEGAM - Manaus, 2022

Áreas de Conhecimento

Otimização de Processos Industriais

Turma

Turma 1

Item