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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.
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Distributed Loads: Problem Solving01:21

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Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
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Operation of the Collaborative Composite Manufacturing CCM System
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A Predictive Approach for Disassembly Line Balancing Problems.

Iwona Paprocka1, Bożena Skołud1

  • 1Department of Engineering Processes Automation and Integrated Manufacturing Systems, Faculty of Mechanical Engineering, Silesian University of Technology, Konarskiego 18A Str., 44-100 Gliwice, Poland.

Sensors (Basel, Switzerland)
|May 28, 2022
PubMed
Summary
This summary is machine-generated.

Predicting disassembly operation times and joint conditions is crucial for efficient resource utilization in selective disassembly. This study develops a method to estimate these factors, improving planning for remanufacturing, recycling, and reuse.

Keywords:
disassembly line balancingdisassembly time estimationproduct recoveryremanufacturingreusingreverse logistics

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Area of Science:

  • * Industrial Engineering
  • * Operations Research
  • * Sustainable Manufacturing

Background:

  • * Efficient resource utilization is critical in modern manufacturing and product lifecycle management.
  • * Selective disassembly planning requires accurate prediction of operation times and joint conditions for effective recycling, reuse, and remanufacturing.
  • * Current methods lack robust estimation techniques for disassembly times tailored to different end-of-life scenarios.

Purpose of the Study:

  • * To investigate a disassembly system incorporating predicted operation times and joint quality.
  • * To balance line smoothness, minimize line time factor, optimize line efficiency and profit, and reduce ex post errors.
  • * To develop and validate a method for estimating disassembly operation times for remanufacturing, recycling, and reuse.

Main Methods:

  • * Estimation of disassembly times for remanufacturing, recycling, and reuse, based on historical disassembly time data and joint quality assessments.
  • * Analysis of the impact of predicted times and joint conditions on key performance indicators like line smoothness and efficiency.
  • * Integration of estimation methods into selective serial disassembly sequence planning.

Main Results:

  • * A novel method for estimating disassembly operation times, enhancing the reliability and efficiency of task balancing in disassembly lines.
  • * Demonstrated ability to predict joint conditions and their influence on disassembly duration.
  • * Improved accuracy in planning disassembly operations, leading to better resource management and economic outcomes.

Conclusions:

  • * The developed estimation method significantly increases the reliability and efficiency of disassembly line balancing.
  • * Accurate prediction of disassembly times and joint quality is essential for optimizing remanufacturing, recycling, and reuse processes.
  • * The approach provides a foundation for more sustainable and profitable product end-of-life management.