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Production Loss Analysis in Mobile Multi-skilled Robot Operated Flexible Serial Production Systems.

Kshitij Bhatta1, Chen Li1, Qing Chang1

  • 1Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA 22904, USA.

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|September 21, 2022
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Summary
This summary is machine-generated.

Flexible manufacturing systems (FMS) can adapt to rapid demand changes using data-enabled modeling with mobile robots. This study introduces a novel method to evaluate FMS performance, minimizing production loss.

Keywords:
FMSFlexible Manufacturing SystemMulti-skilled robotsOpportunity WindowPermanent Production Loss

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Area of Science:

  • Industrial Engineering
  • Operations Research
  • Robotics

Background:

  • Modern supply chains face unpredictable demand fluctuations, as seen during the COVID-19 pandemic.
  • Flexible Manufacturing Systems (FMS) are crucial for adapting production volumes to market dynamics.
  • Effective modeling is needed to enhance FMS responsiveness and minimize disruptions.

Purpose of the Study:

  • To propose a novel data-enabled method for modeling Flexible Manufacturing Systems (FMS).
  • To evaluate the dynamic performance of an FMS utilizing mobile multi-skilled robots.
  • To introduce metrics for assessing and attributing permanent production loss in FMS.

Main Methods:

  • Development of a data-enabled model for FMS.
  • Simulation and analysis of FMS performance using mobile multi-skilled robots.
  • Derivation of mathematical expressions for permanent production loss evaluation and attribution.

Main Results:

  • The proposed data-enabled model effectively captures the dynamic behavior of FMS.
  • The method allows for accurate evaluation and attribution of permanent production loss.
  • Case studies demonstrate the practical applicability and validation of the model.

Conclusions:

  • Data-enabled modeling with mobile robots enhances FMS adaptability to demand volatility.
  • The developed performance metrics provide valuable insights for optimizing FMS operations.
  • This approach offers a robust framework for improving manufacturing system resilience.