Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Production Efficiency01:01

Production Efficiency

18.0K
Net production efficiency (NPE) is the efficiency at which organisms assimilate energy into biomass for the next trophic level. Due to low metabolic rates and less energy spent on thermoregulatory processes, the NPE of ectotherms (cold-blooded animals) is 10 times higher than endotherms (warm-blooded animals).
18.0K
Multimachine Stability01:25

Multimachine Stability

506
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
506

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Role of virtual reality exposure before elective day care surgery to reduce patient's distress.

Updates in surgery·2026
Same author

Giant Aneurysm in a Circumflex Coronary Sinus Fistula.

JACC. Case reports·2025
Same author

Occupational Health and Safety Training by Cross-Reality: Preliminary Results From SCISSOR Project.

Safety and health at work·2025
Same author

Transperineal Laser Ablation for Focal Therapy of Localized Prostate Cancer: 12-Month Follow-up Outcomes from a Single Prospective Cohort Study.

Cancers·2024
Same author

Editorial: Understanding cross-cultural differences through cognition and perception analysis: integrating neuroscience and cultural psychology, volume II.

Frontiers in psychology·2024
Same author

Comprehensive Evaluation of Multispectral Image Registration Strategies in Heterogenous Agriculture Environment.

Journal of imaging·2024

Related Experiment Video

Updated: Jan 1, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

308

Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing.

Marcello Fera1, Alessandro Greco1, Mario Caterino1

  • 1Department of Engineering, University of Campania Luigi Vanvitelli, via Roma 29, 81031 Aversa, Italy.

Sensors (Basel, Switzerland)
|December 28, 2019
PubMed
Summary

This study introduces a framework using Industrial Internet of Things (IoT) wearable sensors and simulation to optimize manufacturing production lines. It enables continuous monitoring and balancing of performance for increased productivity and reduced costs.

Keywords:
Internet of Things—IoTmethodological frameworkproduction line performancesimulationwearable devices

More Related Videos

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

7.0K
Multimodal 3D Printing of Phantoms to Simulate Biological Tissue
05:11

Multimodal 3D Printing of Phantoms to Simulate Biological Tissue

Published on: January 11, 2020

8.0K

Related Experiment Videos

Last Updated: Jan 1, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

308
Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

7.0K
Multimodal 3D Printing of Phantoms to Simulate Biological Tissue
05:11

Multimodal 3D Printing of Phantoms to Simulate Biological Tissue

Published on: January 11, 2020

8.0K

Area of Science:

  • Industrial Engineering
  • Manufacturing Systems
  • Industry 4.0 Technologies

Background:

  • Production process optimization is crucial for manufacturing competitiveness.
  • Industry 4.0 technologies enable enhanced data collection and analysis for better decision-making.
  • Interconnecting resources and production chains is key to modern manufacturing control.

Purpose of the Study:

  • To propose a methodological framework for analyzing production line performance.
  • To leverage Industrial Internet of Things (IoT) wearable sensors and simulation tools for continuous monitoring.
  • To adapt line balancing and performance to varying production demands.

Main Methods:

  • Utilized Industrial Internet of Things (IoT) devices, specifically wearable sensors, for data acquisition.
  • Integrated simulation tools with experimental data for comprehensive analysis.
  • Applied the framework to a case study involving a manual task on a manufacturing production line.

Main Results:

  • Demonstrated the framework's applicability in analyzing production line performance parameters.
  • Showcased the effectiveness of combining experimental and numerical data.
  • Enabled continuous monitoring of line balancing and performance under dynamic production demands.

Conclusions:

  • The proposed framework effectively supports the continuous monitoring and optimization of manufacturing production lines.
  • The integration of IoT wearable sensors and simulation tools provides valuable insights for improving productivity and reducing costs.
  • The methodology is effective for adapting production lines to changing market demands.