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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Modeling and Balancing for Disassembly Lines Considering Workers With Different Efficiencies.

Kaipu Wang, Xinyu Li, Liang Gao

    IEEE Transactions on Cybernetics
    |May 25, 2021
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    Summary
    This summary is machine-generated.

    This study addresses disassembly line balancing by accounting for worker efficiency differences. It introduces a new model and algorithm to optimize workload, cost, and risk for sustainable manufacturing.

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    Area of Science:

    • Industrial Engineering
    • Sustainable Manufacturing
    • Operations Research

    Background:

    • Sustainable manufacturing relies on efficient end-of-life product disassembly for recycling and remanufacturing.
    • Disassembly line balancing is crucial but often overlooks worker efficiency variations, leading to unbalanced workloads.
    • Existing models fail to account for factors like environment and skill affecting worker performance.

    Purpose of the Study:

    • To develop a disassembly line balancing model that incorporates diverse worker efficiencies.
    • To optimize disassembly operations considering workload smoothness, worker costs, and disassembly risks.
    • To introduce the bucket brigade model into disassembly lines for improved efficiency.

    Main Methods:

    • Established a novel disassembly line balancing model considering heterogeneous worker efficiencies.
    • Integrated the bucket brigade model to manage workflow across stations.
    • Developed a discrete flower pollination algorithm for optimization.
    • Validated the algorithm against 11 other algorithms.

    Main Results:

    • The proposed model effectively balances workloads among stations despite varying worker efficiencies.
    • The discrete flower pollination algorithm demonstrated superior performance in finding high-quality solutions.
    • The study provided multiple practical disassembly schemes for television recycling.

    Conclusions:

    • Accounting for worker efficiency differences is essential for effective disassembly line balancing.
    • The proposed model and algorithm offer a robust approach to optimize sustainable disassembly processes.
    • This research provides valuable insights for decision-makers in managing disassembly operations.