Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics
By G. Fragapane, Dmitry A. Ivanov, M. Peron, Fabio Sgarbossa, Jan Ola Strandhagen. Annals of Operations Research, 2020
386 citations recorded by the source corpus.
Manufacturing flexibility improves a firm’s ability to react in timely manner to customer demands and to increase production system productivity without incurring excessive costs and expending an excessive amount of resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems. We develop and test an analytical model for a throughput analysis and use it to reveal the conditions under which the autonomous mobile robots (AMR)-based flexible production networks are more advantageous as compared to the traditional production lines. Using a circular loop among workstations and inter-operational buffers, our model allows congestion to be avoided by utilizing multiple crosses and analyzing both the flow and the load/unload phases. The sensitivity analysis shows that the cost of the AMRs and the number of shifts are the key factors in improving flexibility and productivity. The outcomes of this research promote a deeper understanding of the role of AMRs in Industry 4.0-based production networks and can be utilized by production planners to determine optimal configurations and the associated performance impact of the AMR-based production networks in as compared to the traditionally balanced lines. This study supports the decision-makers in how the AMR in production systems in process industry can improve manufacturing performance in terms of productivity, flexibility, and costs.
Subfields: Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/7e0facc242c1da22875e67e41293325044c6f0b5
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In Industrial and Manufacturing Engineering
Citations in the corpus
- The Industry 5.0 framework: viability-based integration of the resilience, sustainability, and human-centricity perspectives (2022, background): “The orange cluster is devoted to intelligence – i.e. intelligent manufacturing and intelligent transportation (Fragapane et al. 2020, Frazzon et al. 2021).”
- Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic (2020, methodology): “…utilized in SC resilience research (Baryannis et al. 2019; Dubey et al. 2019b; Ivanov et al. 2019b; Queiroz et al. 2019; Ivanov and Dolgui 2020a; Fragapane et al. 2020) pointing to the contributions of digital technology to SC viability in the areas of improving demand forecasting by data…”
- A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 (2020, positive): “Among various perspectives (Liao et al. 2017; Strozzi et al. 2017; Tang and Veelenturf 2019; Fragapane et al. 2020; Ghadge et al. 2020), a particular concern has been focused on how digitalisation and data analytics capabilities can be manifested in predicting future and identifying real-time…”