Design and implementation of a distributed part-routing algorithm for reconfigurable transportation systems

Carpanzano, Emanuele; Cesta, Amedeo; Orlandini, Andrea; Rasconi, Riccardo; Suriano, Marco; Umbrico, Alessandro; Valente, Anna

doi:10.1080/0951192x.2015.1067911

Cited by 14 publications

(8 citation statements)

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“…8 h), while the rate of parts entering the system from the load station is kept constant. A complete and exhaustive description of such experiments can be found in [51]. The experiments have been carried out in two phases to (i) evaluate RTS throughput and parts lead time while considering different layouts (first phase), and (ii) assess the benefits of the distributed approach when changes occur in the RTS (second phase).…”

Section: Experiments Results and Analysismentioning

confidence: 99%

“…A failure leads to a temporary unavailability of the corresponding module, thus triggering the generation of a new RTS layout corresponding to the new reality of the system, and allowing to resume the production of new routing policies until the original layout is (possibly) restored. The interested reader can find further details in [51]. Additional tests have been carried out to evaluate the knowledge processing mechanism and the capability of a single GECKO agent to build a consistent abstraction of the production context and synthesize timeline-based models accordingly.…”

Section: Experiments Results and Analysismentioning

confidence: 99%

“…The transportation modules of a RTS are designed as mechatronic devices equipped with standard interfaces that allow modules to connect each other and embed logic controllers for actuators/motors and sensors. A central problem of RTSs is the Online Part Routing Problem (OPRP) addressing the formalization and synchronization of RTS mechatronic modules to transport all the parts in the manufacturing system according to their destinations [51]. A solution for the OPRP must ensure that all the parts are properly worked, the routings must be collision-free and routings must be efficient.…”

Section: Developed Methodologies and Toolsmentioning

confidence: 99%

“…In the context of RTS, the routing problem-as the main problem to be solved-is addressed within the optimization component as a multi-agent problem where a set of agents interact and share information in order to transport pallets (or parts) to their final destination within a RTS. Specifically, a distributed auction-based algorithm for part routing has been developed that coordinates the transport modules [51]. Such algorithm, denominated Planning Framework, establishes the assignment (i.e.…”

Section: Optimization Componentmentioning

confidence: 99%

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Knowledge Based Modules for Adaptive Distributed Control Systems

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et al. 2019

Factories of the Future

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Modern automation systems are asked to provide a step change toward flexibility and reconfigurability to cope with increasing demand for fast changing and highly fragmented production-which is more and more characterising the manufacturing sector. This reflects in the transition from traditional hierarchical and centralised control architecture to adaptive distributed control systems, being the latter capable of exploiting also knowledge-based strategies toward collaborating behaviours. The chapter intends to investigate such topics, by outlining major challenges and proposing a possible approach toward their solution, founded on autonomous, self-declaring, knowledge-based and heterarchically collaborating control modules. The benefits of the proposed approach are discussed and demonstrated in the field of re-manufacturing of electronic components, with specific reference to a pilot plant for the integrated End-Of-Life management of mechatronic products. 4.1 Scientific and Industrial Motivations Since several years, the manufacturing industry has been facing a number of technological and production challenges related to the increasing variability of mix and demand of products driven by a short product life cycle. Nevertheless, the growing industrial demand for increased levels of reconfigurability-having impact both in production process automation, supervision and data collection and aggregation systems-is not properly fulfilled, mainly due to the lack of widely accepted solutions

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Section: Experiments Results and Analysismentioning

confidence: 99%

Section: Experiments Results and Analysismentioning

confidence: 99%

Section: Developed Methodologies and Toolsmentioning

confidence: 99%

Section: Optimization Componentmentioning

confidence: 99%

See 2 more Smart Citations

Knowledge Based Modules for Adaptive Distributed Control Systems

Ballarino

Brusaferri

Cesta

et al. 2019

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“…Modern approaches are targeting this issue with particularly successful results in simulation environments (Nunes et al, 2012 ; Nunes and Gini, 2015 ). In other similar problems the routing of working parts is assigned to the most suitable transportation agent through an auction-based mechanism associated to a multi-objective function (Carpanzano et al, 2016 ). However, the relevant approaches assume auctions to proceed on an agent-centered point of view which does not consider the capacities and special skills of other team members.…”

Section: Literature Reviewmentioning

confidence: 99%

Time-Aware Multi-Agent Symbiosis

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Contemporary research in human-machine symbiosis has mainly concentrated on enhancing relevant sensory, perceptual, and motor capacities, assuming short-term and nearly momentary interaction sessions. Still, human-machine confluence encompasses an inherent temporal dimension that is typically overlooked. The present work shifts the focus on the temporal and long-lasting aspects of symbiotic human-robot interaction (sHRI). We explore the integration of three time-aware modules, each one focusing on a diverse part of the sHRI timeline. Specifically, the Episodic Memory considers past experiences, the Generative Time Models estimate the progress of ongoing activities, and the Daisy Planner devices plans for the timely accomplishment of goals. The integrated system is employed to coordinate the activities of a multi-agent team. Accordingly, the proposed system (i) predicts human preferences based on past experience, (ii) estimates performance profile and task completion time, by monitoring human activity, and (iii) dynamically adapts multi-agent activity plans to changes in expectation and Human-Robot Interaction (HRI) performance. The system is deployed and extensively assessed in real-world and simulated environments. The obtained results suggest that building upon the unfolding and the temporal properties of team tasks can significantly enhance the fluency of sHRI.

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A Framework for Manufacturing System Reconfiguration Based on Artificial Intelligence and Digital Twin

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Lecture Notes in Mechanical Engineering

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The application of digital twins and artificial intelligence to manufacturing has shown potential in improving system resilience, responsiveness, and productivity. Traditional digital twin approaches are generally applied to single, static systems to enhance a specific process. This paper proposes a framework that applies digital twins and artificial intelligence to manufacturing system reconfiguration, i.e., the layout, process parameters, and operation time of multiple assets, to enable system decision making based on varying demands from the customer or market. A digital twin environment has been developed to simulate the manufacturing process with multiple industrial robots performing various tasks. A data pipeline is built in the digital twin with an API (application programming interface) to enable the integration of artificial intelligence. Artificial intelligence methods are used to optimise the digital twin environment and improve system decision-making. Finally, a multi-agent program approach shows the communication and negotiation status between different agents to determine the optimal configuration for a manufacturing system to solve varying problems. Compared with previous research, this framework combines distributed intelligence, artificial intelligence for decision making, and production line optimisation that can be widely applied in modern reactive manufacturing applications.

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Design and implementation of a distributed part-routing algorithm for reconfigurable transportation systems

Cited by 14 publications

References 40 publications

Knowledge Based Modules for Adaptive Distributed Control Systems

Knowledge Based Modules for Adaptive Distributed Control Systems

Time-Aware Multi-Agent Symbiosis

A Framework for Manufacturing System Reconfiguration Based on Artificial Intelligence and Digital Twin

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