December 4, 2025Manufacturing & Service Operations Management

Human-Centric Order Picking: Performance Prediction and Robot Assignment at a Robotic Fulfillment Center

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Improving picker productivity by 7.5% enhances order-picking efficiency in automated centers, addressing workload concerns.
Simulation results indicate a 14.2% reduction in unfulfilled items, improving overall fulfillment accuracy.
The proposed distributionally robust human-centric picking performance prediction model leverages covariance and forecasting models for accuracy.
Automation in order-picking is crucial for improving pickers' health issues and increasing income through effective e-commerce solutions.

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Implication

Computational analysis shows order-picking methods improve productivity and reduce health issues in e-commerce settings, indicating the benefits of robotic systems.

Cite This Study

Wu et al. (2025) studied this question.

synapsesocial.com/papers/6930dc9eea1aef094cca2e59 https://doi.org/10.1287/msom.2023.0644

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Implication

Computational analysis shows order-picking methods improve productivity and reduce health issues in e-commerce settings, indicating the benefits of robotic systems.

Human-Centric Order Picking: Performance Prediction and Robot Assignment at a Robotic Fulfillment Center

Key Points

Discussion

Implication

Cite This Study

Human-Centric Order Picking: Performance Prediction and Robot Assignment at a Robotic Fulfillment Center

Key Points

Discussion

Implication

Cite This Study

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