scholarly journals Improving the efficiency of decision-making during emergency situations in cyberphysical distributed production systems

Author(s):  
Denis V. Shelkovyy ◽  
◽  
Oleg Yu. Sivchenko ◽  
Elizaveta E. Usina ◽  
Аleksandr N. Bykov ◽  
...  

This paper presents results of approbation of existing mathematical models, enabling operative assessment of the required link resource to serve data streams, generated by the elements of technical vision subsystem in cyberphysical distributed production systems. Simulation experiments allowed to discover dependencies between achievable multimedia traffic packet processing delay in switching systems and link-level resource, reserved for respective data transfer. Obtained dependencies are to be used during design of algorithm for link resource control for increasing speed of decision making in emergency.

2016 ◽  
Vol 66 (1) ◽  
Author(s):  
Baltazar Sánchez-Díaz ◽  
Luis Manuel Vargas-Villamil ◽  
Joel Zavala-Cruz ◽  
Nydia Del Rivero Bautista ◽  
Juan Manuel Gonzalez-Camacho ◽  
...  

The researchers propose a methodology to share, process, and exchange agricultural information among different applications through a Web service. The Web service will be available online and mobile and can be used as a tool for decision-making. Initially, agricultural regions and cartography of the study area were identified. Subsequently, a simulation model of potential yield of pasture and animal behavior by regions and area, was designed. Finally, a Web service, using Amazon Web Services and REST for exchanging information, was developed. Web services in the cloud, enable interoperability using data, mapping information of agricultural regions, simulation models, and protocols for data transfer, thus making available the prediction results.


Author(s):  
Mateusz Iwo Dubaniowski ◽  
Hans Rudolf Heinimann

A system-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a high level architecture (HLA) simulation of three networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.


2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Abbasali Ebrahimian ◽  
Seyed-Hossein Hashemi-Amrei ◽  
Mohammadreza Monesan

Introduction. Appropriate decision-making is essential in emergency situations; however, little information is available on how emergency decision-makers decide on the emergency status of the patients shifted to the emergency department of the hospital. This study aimed at explaining the factors that influence the emergency specialists’ decision-making in case of emergency conditions in patients. Methods. This study was carried out with a qualitative content analysis approach. The participants were selected based on purposive sampling by the emergency specialists. The data were collected through semistructured interviews and were analyzed using the method proposed by Graneheim and Lundman. Results. The core theme of the study was “efforts to perceive the acute health threats of the patient.” This theme was derived from the main classes, including “the identification of the acute threats based on the patient’s condition” and “the identification of the acute threats based on peripheral conditions.” Conclusions. The conditions governing the decision-making process about patients in the emergency department differ from the conditions in other health-care departments at hospitals. Emergency specialists may have several approaches to decide about the patients’ emergency conditions. Therefore, notably, the emergency specialists’ working conditions and the others’ expectations from these specialists should be considered.


2015 ◽  
Vol 6 (4) ◽  
pp. 60-69 ◽  
Author(s):  
Sławomir Kłos ◽  
Peter Trebuna

Abstract This paper proposes the application of computer simulation methods to support decision making regarding intermediate buffer allocations in a series-parallel production line. The simulation model of the production system is based on a real example of a manufacturing company working in the automotive industry. Simulation experiments were conducted for different allocations of buffer capacities and different numbers of employees. The production system consists of three technological operations with intermediate buffers between each operation. The technological operations are carried out using machines and every machine can be operated by one worker. Multi-work in the production system is available (one operator operates several machines). On the basis of the simulation experiments, the relationship between system throughput, buffer allocation and the number of employees is analyzed. Increasing the buffer capacity results in an increase in the average product lifespan. Therefore, in the article a new index is proposed that includes the throughput of the manufacturing system and product life span. Simulation experiments were performed for different configurations of technological operations.


2021 ◽  
Author(s):  
Maximilian Rolinck ◽  
Rishi Kumar ◽  
Bastian Thiede ◽  
Felipe Cerdas ◽  
Kuldip Singh Sangwan ◽  
...  

2021 ◽  
Author(s):  
Yucheng Dong ◽  
Yao Li ◽  
Ying He ◽  
Xia Chen

Preference–approval structure combines the preference information of both ranking and approval, which extends the ordinal preference model by incorporating two categories of choice alternatives, that is, acceptable (good) and unacceptable (bad), in the preference modeling process. In this study, we present some axioms that imply the existence of a unique distance function of preference–approval structures. Based on theoretical analysis and simulation experiments, we further study a preferences aggregation model in the group decision-making context based on the proposed axiomatic distance function. In this model, the group preference is defined as a preference–approval structure that minimizes the sum of its distances to all preference–approval structures of individuals in the group under consideration. Particularly, we show that the group preference defined by the axiomatic distance–based aggregation model has close relationships with the simple majority rule and Cook and Seiford’s ranking.


2018 ◽  
Vol 42 (4) ◽  
pp. 395 ◽  
Author(s):  
Alicia M. Zavala ◽  
Gary E. Day ◽  
David Plummer ◽  
Anita Bamford-Wade

Objective This paper provides a narrative overview of the literature concerning clinical decision-making processes when staff come under pressure, particularly in uncertain, dynamic and emergency situations. Methods Studies between 1980 and 2015 were analysed using a six-phase thematic analysis framework to achieve an in-depth understanding of the complex origins of medical errors that occur when people and systems are under pressure and how work pressure affects clinical performance and patient outcomes. Literature searches were conducted using a Summons Search Service platform; search criteria included a variety of methodologies, resulting in the identification of 95 papers relevant to the present review. Results Six themes emerged in the present narrative review using thematic analysis: organisational systems, workload, time pressure, teamwork, individual human factors and case complexity. This analysis highlights that clinical outcomes in emergency situations are the result of a variety of interconnecting factors. These factors may affect the ability of clinical staff in emergency situations to provide quality, safe care in a timely manner. Conclusions The challenge for researchers is to build the body of knowledge concerning the safe management of patients, particularly where clinicians are working under pressure. This understanding is important for developing pathways that optimise clinical decision making in uncertain and dynamic environments. What is known about the topic? Emergency departments (EDs) are characterised by high complexity, high throughput and greater uncertainty compared with routine hospital wards or out-patient situations, and the ED is therefore prone to unpredictable workflows and non-replicable conditions when presented with unique and complex cases. What does this paper add? Clinical decision making can be affected by pressures with complex origins, including organisational systems, workload, time constraints, teamwork, human factors and case complexity. Interactions between these factors at different levels of the decision-making process can increase the complexity of problems and the resulting decisions to be made. What are the implications for practitioners? The findings of the present study provide further evidence that consideration of medical errors should be seen primarily from a ‘whole-of-system’ perspective rather than as being primarily the responsibility of individuals. Although there are strategies in place in healthcare organisations to eliminate errors, they still occur. In order to achieve a better understanding of medical errors in clinical practice in times of uncertainty, it is necessary to identify how diverse pressures can affect clinical decisions, and how these interact to influence clinical outcomes.


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