Flexible production data generator for manufacturing companies

Ederson Carvalhar Fernandes, Lucas Iuri Dos Santos, Juliane Andressa Camatti, Liam Brown, Milton Borsato

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Advances in technology over last decades have been followed by many challenges of industrial competitiveness at different levels. Production planning and control generally demand too much time to data capture, and it makes it difficult to understand the analysis of the process flow and to obtain satisfactory results. These results can help operations managers make the best decisions and implement them. Companies that do not have tracking systems to automatically capture data from their machines, spend a lot of time trying to achieve a visual correlation which is consistent with the reality of their processes and goals. Companies without this technology can use data generator systems to simulate data variables in different sizes and previously identify suitable graphical correlations. Current's data generators work with several variables for a lot of situations. On the other hand, it can become confusing and error-prone due to excess of information. However, there is no automated data generator focused on process-flow data which has usability enough to meet the manufacturing company's needs. This study proposes a flexible production-oriented data generator for different physical arrangements in manufacturing companies, along with graphical correlations of production parameters to aid planning and decision making.

Original languageEnglish
Pages (from-to)1478-1484
Number of pages7
JournalProcedia Manufacturing
Volume51
DOIs
Publication statusPublished - 2020
Event30th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2021 - Athens, Greece
Duration: 15 Jun 202118 Jun 2021

Keywords

  • Data Generator
  • Data Visualization
  • Flexibility
  • Manufacturing

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