Influence of workload imbalances on the need for worker flexibility

This research applies Agent Based Modeling (ABM) to study volume flexibility in a Dual Resource Constrained (DRC) assembly flow shop environment. The simulation experiment evaluated System and Human Effects of varying DRC system staffing levels according to Design (i.e., Workforce, Distance and Buffer Capacity), Sensitivity (i.e., Coefficient of Variation) and Operating (i.e., When-rule and Where-rule) factors. Results showed that the rule by which workers are assigned to workstations affects WIP and Flow Time performances more than production rates. Furthermore per-worker productivity was found to increase, compared to the fully staffed system, particularly where the Downstream movement rule was applied. Using the Downstream rule when changing stations after completing current tasks reduced Flow Time (-15%) and WIP (-10%). If another Where-rule is chosen then it may be preferable for workers to move only after completing all jobs in the station (Decentralized rule). For Utilization rates and Mean hourly Switching of work (Human Effects), the model shows complex relationships depending on almost all evaluated factors. The novel ABM approach used here enabled the evaluation of emergent system behaviors and showed potential to help firms understand both human and performance effects of operational choices in efforts to achieve volume flexibility

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“…Staffing levels are consistent with the literature (Kannan and Jensen 2004;Davis, Kher, and Wagner 2009. ) …”

Section: Design Factors Under Considerationsupporting

confidence: 88%

Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance

Sammarco

Fruggiero

Neumann

et al. 2013

International Journal of Production Research

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“…There are studies in which workers are modelled in such a way that they are skilled for and most efficient in their 'own' or 'home' department and are also skilled for a second or even third department in which they are less efficient (see e.g. Nelson 1970, Hogg et al 1977, Bobrowski and Park 1993, Malhotra and Kher 1994, Yang 2007, Davis et al 2009). When this is combined with a where-rule that assigns workers to their most efficient department, this resembles the modelling of worker preferences.…”

Section: Worker Related Issues When Constraining the Work In Processmentioning

confidence: 99%

The impact of the amount of work in process on the use of cross-training

Bokhorst

2011

International Journal of Production Research

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“…The objective of this model is to minimize net present cost, which includes initial training costs, incremental training costs necessary to complete tasks and meet customer demand, inventory costs, and cost of poor quality. Another study by Davis et al, (2009) contents that workload imbalances give rise to worker flexibility and current work center capacity influences the extent to which worker flexibility can be utilized to counter the workload imbalances.…”

Section: Literature Review and Backgroundmentioning

confidence: 99%

Artificial neural networks based predictive model for worker assignment into virtual cells

Mural¹,

Puri²,

Prabhakaran³

2010

Int. J. Eng. Sci. Tech

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Virtual cellular manufacturing systems (VCMS) have come into existence, replacing traditional cellular manufacturing systems (CMS), to meet highly dynamic production conditions in terms of demand, processing times, product mix and processing sequence. While cell formation phase of VCMS has been dealt quite voluminously, worker assignments phase has gained momentum recently after researchers started realizing the importance of workers' role during implementation of cell-based manufacturing. In the past, worker assignments have been analyzed with development of various heuristics/mathematical models in order to achieve reduced worker costs, improved productivity and quality, effective utilization of workforce and providing adequate levels of worker flexibility. In this paper, a new approach based on artificial neural networks (ANNs) has been proposed to assign workers into virtual cells since ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively. A framework of multilayered perceptron with feed forward (MLP-FF) neural network has been formulated on worker assignment for VCMS under dual resource constrained (DRC) context and its performance under two cell configurations with different time periods is analyzed. A worker assignment model has been developed and applied with cell formation solutions available in the literature in order to generate simulated datasets that drive the training process of proposed ANN framework.

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Influence of workload imbalances on the need for worker flexibility

Cited by 22 publications

References 16 publications

Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance

Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance

The impact of the amount of work in process on the use of cross-training

Artificial neural networks based predictive model for worker assignment into virtual cells

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