Agent-based monitoring service for management of disruptive events in supply chains

Fernández, Erica; Toledo, Carlos M.; Galli, Marı́a Rosa; Salomone, Enrique; Chiotti, Omar

doi:10.1016/j.compind.2015.01.009

Cited by 15 publications

(3 citation statements)

References 34 publications

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“…To detect and predict disruptive events along a schedule execution, Fernández proposed an agent-based approach for implementing a service-oriented monitoring subsystem that uses a reference model for defining monitoring models. This subsystem offers services for collecting execution data of a schedule and environment data and assessing them to detect/anticipate disruptive events [60]. Brintrup discussed the application of data analytics in predicting first-tier supply chain disruptions using historical data available to an Original Equipment Manufacturer (OEM).…”

Section: Related Workmentioning

confidence: 99%

Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management

Lee

Yang

Wei³

et al. 2021

Applied Sciences

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The risk of supply chain disruption is usually related to daily disturbances in supply chain operations (e.g., demand fluctuations) and some emergency risks, such as earthquakes and epidemic outbreaks. During a crisis, companies need agility to quickly find new suppliers and open auxiliary sales channels to meet customer needs and remain competitive. However, identifying “event” is one of the most difficult challenges of current decision support systems. If the system encounters an emergency, it is usually unable to promptly notify users of the warning to avoid risks. A sensible solution is to incorporate the real-time event-monitoring system into SCM (i.e., supply chain management) in order to share emergency information in the early stage for preemptive management in the supply chain. On the other hand, in order to process confidential supply chain data with other members, the SCM infrastructure requires secure data sharing. The blockchain-based SCM system can improve the transparency of traceability to ensure that the supply chain system provides high-quality products and protects data privacy and security. The view is taken; therefore, in this work, we combined a method of real-time event detection using collected Twitter data and blockchain technology for event monitoring to improve the visibility of the supply chain system and take preemptive measures for risk avoidance. The experiments show some interesting results and potentials for future work in the field of the agile supply chain.

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Section: Related Workmentioning

confidence: 99%

Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management

Lee

Yang

Wei³

et al. 2021

Applied Sciences

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“…Therefore, there is a need to implement a layer between the sensors and the interface, so that it can analyze the raw sensor data and do the reasoning so to differentiate between false alarms and real events. Model-Based approaches have been proposed in [10] applied to supply chains where the authors propose a set of resources, orders, specifications and a set of milestones throughout the supply chain. The milestones are then monitored and agents actively look for deviations of the expected models.…”

Section: Event Processingmentioning

confidence: 99%

Data Fusion of Georeferenced Events for Detection of Hazardous Areas

Onofre

Gomes

Pimentão

et al. 2017

IFIP Advances in Information and Communication Technology

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When dealing with events in moving vehicles, which can occur over widespread areas, it is difficult to identify sources that do not derive from material fatigue, but from situations that occur in specific spots. Considering a railway system, problems could occur in trains, not because of train's equipment failure, but because the train is crossing a specific location. This paper presents a new smart system being developed that is able to generate geolocated sensor-data; transmit it for smart processing and fusing to the inference engine being built to correlate the data, and drill-down the information. Using a statistical approach within the inference engine, it is possible to combine results collected over long periods of time in a "heat-map" of frequent fault areas, mapping faulty events to detect hazardous locations using georeferenced sensor data, collected from several trains that will be integrated in these maps to infer high probability risk areas.

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“…Also, some research areas related to service composition including service workflow [22], service management [23], and modeling of business flow [24] are widely studied. Nevertheless, few studies have been carried out with the consideration of QoS-based composition in the complex CMfg environment.…”

Section: Maintenancementioning

confidence: 99%

A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition

Zhou

Yao

2016

Int J Adv Manuf Technol

130

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With the advent of cloud manufacturing (CMfg), more and more services in CMfg platforms may provide the same functionality but differ in performance. In order to insure the manufacturing cloud to match the complicated task requirements, composited CMfg service optimal selection (CCSOS) is becoming increasingly important. This study proposes a new approach for such CCSOS problems, the so-called hybrid artificial bee colony (HABC) algorithm, which employs both the probabilistic model of Archimedean copula estimation of distribution algorithm (ACEDA) and the chaos operators of global best-guided artificial bee colony to generate the offspring individuals with consideration of quality of service (QoS) and CMfg environment. Different-scale CCSOS problems are adopted to evaluate the performance of the proposed HABC. Experimental results have shown that the HABC can find better solutions compared with such algorithms as genetic algorithm, particle swarm optimization, and basic artificial bee colony algorithm.

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Agent-based monitoring service for management of disruptive events in supply chains

Cited by 15 publications

References 34 publications

Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management

Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management

Data Fusion of Georeferenced Events for Detection of Hazardous Areas

A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition

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