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W. P. Neumann

Researcher at Ryerson University

Publications -  8
Citations -  596

W. P. Neumann is an academic researcher from Ryerson University. The author has contributed to research in topics: Order picking & Relevant cost. The author has an hindex of 7, co-authored 8 publications receiving 452 citations.

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Incorporating human factors in order picking planning models: framework and research opportunities

TL;DR: In this paper, a conceptual framework for integrating human factors into planning models of order picking activities is proposed, and the authors hypothesize that doing so improves the performance of an OP system and workers' welfare.
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Incorporating human fatigue and recovery into the learning–forgetting process

TL;DR: In this paper, a learning-forgetting-fatigue-recovery model is presented to address possible issues relating to workers' capabilities and restrictions in manufacturing environments, and numerical examples are solved to address some research questions regarding the model optimization and its constraints.
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Modelling worker reliability with learning and fatigue

TL;DR: A mathematical model is developed that estimates the human error rate while performing an assembly job under the influence of learning–forgetting and fatigue–recovery and is able to dynamically measure the humanerror rate and reliability with time.
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Modelling worker fatigue and recovery in dual-resource constrained systems

TL;DR: A mixed-integer linear programming (MILP) model is presented that describes fatigue and recovery in a DRC system with one worker performing n tasks (flexibility level) within m cycles and suggests that short rest breaks after each task, short cycle times and faster recovery rates improve the system's performance.
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An integrated cost and worker fatigue evaluation model of a packaging process

TL;DR: The results of the numerical analysis show that smaller box sizes are less sensitive to changes in the maximum permitted fatigue level and that they lead to lower total relevant cost for low wage cost and larger boxes are recommended for higher wage cost.