Improving Collaborative Robotic Complex Efficiency: An Approach to the Intellectualization of the Control System

Gorkavyy, M.A.; Ivanov, Yuriy; Sukhorukov, Sergei; Zhiganov, Sergey; Melnichenko, Markel A.; Gorkavyy, Alexander; Grabar, D. M.

doi:10.3390/engproc2023033018

Cited by 2 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Utilizing a control system, the product was assembled with an average assembly time of approximately 38 minutes, which is shorter than the study-determined design time, and an assembly accuracy of ±3mm. [11] In the contemporary environment of industrial automation and technological advancement, the problem warrants more examination. This subject has several benefits for industrial development and production methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Modular Intelligent Control System in the Pre-assembly Stage

Micieta,

Macek,

Binasova

et al. 2024

Preprint

View full text Add to dashboard Cite

This paper addresses the approach of fully automated intelligent control systems in production organizations, focusing on intelligent production systems research. The overview highlights a gap in control operations ahead of assembly as single-purpose control machines are frequently employed, which is precisely their drawback. Conversely, there are accurate multipurpose measurement centers that do not provide total quality control over the manufactured parts because of the cost and length of the measuring procedure. The study's primary objective was to create an intelligent modular control system, whose concept enables it to control various components. The purpose of the modular intelligent control system is to keep an eye on each module's quality during the pre-assembly phase. This system ensures exact control over the production process of modules by integrating sophisticated sensors, diagnostic tools, and intelligent control mechanisms. The technology makes it possible to monitor several parameters and important quality features. Integrated sensors and diagnostic technologies identify possible inaccuracies and disparities, guaranteeing prompt diagnosis of issues in specific modules. The system's intelligent control algorithms streamline the production process and guarantee synchronization between individual modules to achieve consistent quality and performance. One advantage of implementing the solution is that, on average, inspection time is reduced by 40 to 60% as compared to the prior manual inspection approach. In addition, full measurement data archiving was made available, and finally, the human element—which introduced a substantial error rate into this process—was removed. This system also helps to increase the project's overall efficiency, predictability, and safety while allowing for quick adjustments by standards and requirements.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Modular Intelligent Control System in the Pre-assembly Stage

Micieta,

Macek,

Binasova

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…By optimizing remanufacturing assembly systems through intelligent data-driven controls, industries can not only enhance their operational efficiency, but also contribute to sustainable production practices, aligning with the overarching goal of the discussed modular intelligent control system. Similarly, research by Gorkavyy et al [11] highlights the efficiency improvements achieved through the utilization of collaborative robots within intelligent manufacturing systems. Their study emphasizes the intellectualization of the control system, resulting in significant time and energy savings.…”

Section: Introductionmentioning

confidence: 98%

Modular Intelligent Control System in the Pre-Assembly Stage

Micieta,

Macek,

Binasova

et al. 2024

Electronics

View full text Add to dashboard Cite

This paper presents a novel approach to developing fully automated intelligent control systems for use within production-based organizations, with a specific focus on advancing research into intelligent production systems. This analysis underscores a prevailing deficiency in control operations preceding assembly, where single-purpose control machines are commonly utilized, thus presenting inherent limitations. Conversely, while accurate multipurpose measurement centers exist, they often fail to deliver comprehensive quality control for manufactured parts due to cost and time constraints associated with the measuring process. The primary aim in this study was to develop an intelligent modular control system capable of overseeing the production of diverse components effectively. The modular intelligent control system is designed to meticulously monitor the quality of each module during the pre-assembly phase. By integrating sophisticated sensors, diagnostic tools, and intelligent control mechanisms, this system ensures precise control over module production processes. It facilitates the monitoring of multiple parameters and critical quality features, while integrated sensors and diagnostic methods promptly identify discrepancies and inaccuracies, enabling the swift diagnosis of issues within specific modules. The system’s intelligent control algorithms optimize production processes and ensure synchronization among individual modules, thereby ensuring consistent quality and performance. Notably, the implementation of this solution reduces inspection time by an average of 40 to 60% compared to manual inspection methods. Moreover, the system enables the comprehensive archiving of measurement data, eliminating the substantial error rates introduced by human involvement in the inspection process. Furthermore, the system enhances overall project efficiency, predictability, and safety, while allowing for rapid adjustments in order to meet standards and requirements. This innovative approach represents a significant advancement in intelligent control systems for use in production organizations, offering substantial benefits in terms of efficiency, accuracy, and adaptability.

show abstract

Improving Collaborative Robotic Complex Efficiency: An Approach to the Intellectualization of the Control System

Abstract: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Cited by 2 publications

References 16 publications

Modular Intelligent Control System in the Pre-assembly Stage

Modular Intelligent Control System in the Pre-assembly Stage

Modular Intelligent Control System in the Pre-Assembly Stage

Contact Info

Product

Resources

About