A simulation analysis of the impact of finite buffer storage on manufacturing system reliability

Chang, Ping Chen

doi:10.1016/j.simpat.2016.10.006

Cited by 15 publications

(5 citation statements)

References 21 publications

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“…Therefore, from computational, pragmatic, and theoretical perspectives, the proposed BAT-MCS is superior to the BAT, MCS, and reliability-bound algorithms for calculating the reliability of binarystate networks. The future work is to extend the proposed algorithm to the multi-state flow networks reliability problems [44][45][46][47][48][49][50][51][52][53][54].…”

Section: Discussionmentioning

confidence: 99%

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

Yeh

2021

Reliability Engineering & System Safety

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Various real-life applications, for example, Internet of Things, wireless sensor networks, smart grids, transportation networks, communication networks, social networks, and computer grid systems, are always modeled as network structures. The binary-state network composed of binarystate (e.g., functioning or failed) components (arcs and/or nodes) is one of the most popular network structures. The two-terminal network reliability is a success probability that the network is still functioning and can be calculated by verifying the connectivity between two specific nodes, and is an effective and popular technique for evaluating the performance of all types of networks. To obtain complete information for a making better decisions, a multi-terminal network reliability extends the two specific nodes to a specific node subset in which all nodes are connected. In this study, a new algorithm called the all-multiterminal BAT is proposed by revising the binary-addition-tree algorithm (BAT) and the layered-search algorithm (LSA) to calculate all multi-terminal reliabilities. The efficiency and effectiveness of the proposed all-multiterminal BAT are analyzed from the perspective of time complexity and explained via numerical experiments to solve the all-multiterminal network reliability problems.

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Section: Discussionmentioning

confidence: 99%

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

Yeh

2021

Reliability Engineering & System Safety

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“…It provides an integrated depiction of the risk affected regions to the response team. The development and progression in the technology of sensor devices, wireless communication, and their integration in the IoT have allowed using of smartphones and IoT devices in various fields such as disaster management [15] , higher education [16] , healthcare [17] , [18] , transportation [19] , [20] , industrial manufacturing [21] , and others. Cloud computing offers higher storage and computation facilities to analyze real-time data acquired from smartphones and IoT devices.…”

Section: Introductionmentioning

confidence: 99%

A fog assisted intelligent framework based on cyber physical system for safe evacuation in panic situations

Sood

Rawat

2021

Computer Communications

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In the current scenario of the COVID-19 pandemic and worldwide health emergency, one of the major challenges is to identify and predict the panic health of persons. The management of panic health and on-time evacuation prevents COVID-19 infection incidences in educational institutions and public places. Therefore, a system is required to predict the infection and suggests a safe evacuation path to people that control panic scenarios with mortality. In this paper, a fog-assisted cyber physical system is introduced to control panic attacks and COVID-19 infection risk in public places. The proposed model uses the concept of physical and cyber space. The physical space helps in real time data collection and transmission of the alert generation to the stakeholders. Cyberspace consists of two spaces, fog space, and cloud-space. The fog-space facilitates panic health and COVID-19 symptoms determination with alert generation for risk-affected areas. Cloud space monitors and predicts the person’s panic health and symptoms using the SARIMA model. Furthermore, it also identifies risk-prone regions in the affected place using Geographical Population Analysis. The performance evaluation acknowledges the efficiency related to panic health determination and prediction based on the SARIMA with risks mapping accuracy. The proposed system provides an efficient on time evacuation with priority from risk-affected places that protect people from attacks due to panic and infection caused by COVID-19.

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“…Generally, research related to reliability optimization assumes that each production unit is independent, but in this study, there is a comparison of the reliability of systems that are independent and correlated. Reliability analysis on the multi-state manufacturing network has been carried out in Macchi et al [3]; Chang et al [2]; Chang [6]; Chang, et al [7]; Lai and Yeh [8]. Macchi et al [3] researched this study by performing throughput analysis as support in developing maintenance strategy decisions.…”

Section: Introductionmentioning

confidence: 99%

“…This study uses a case study of a footwear product manufacturing system using limited or unlimited buffering capacity. Reliability analysis by modeling a multi-state manufacturing system was also conducted in Chang [6] study. This study aims to assess the level of customer satisfaction.…”

Section: Introductionmentioning

confidence: 99%

“…This study aims to assess the level of customer satisfaction. Chang [6] defines system reliability as the probability that a multi-state manufacturing network (MMN) can provide sufficient capacity to meet customer needs. A simulation approach was carried out by Chang, et al [7] to generate random capacity status to calculate the use of buffer inventory on a multi-state manufacturing network (MSMN) system.…”

Section: Introductionmentioning

confidence: 99%

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Throughput Analysis on a Multi-state Manufacturing System by Considering Availability

Salsabila

Siswanto

Widodo

et al. 2019

jti

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Manufacturing technology becomes more complex as customer demand increases. Most manufacturing companies consist of multi-state manufacturing networks. Therefore, the reliability and availability parameters become an important issue to satisfy customer demand. Unavailability can result in reducing throughput because of decreasing operational production time. To resolve this problem, the buffer inventory can minimize the occurrence of material starving and production blocking during the equipment downtime. This paper will focus on experimenting with buffer inventory levels and the capacity of a multi-state manufacturing network to increase the production throughput on a company that has 70,000 tons per year of capacity. However, due to the unavailability problem, the existing system capacity decreases to 62,175 tons per year. The simulation model is used to improve throughput by modeling the failure interruption and the buffer inventory logics during the production process.

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A simulation analysis of the impact of finite buffer storage on manufacturing system reliability

Cited by 15 publications

References 21 publications

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

A fog assisted intelligent framework based on cyber physical system for safe evacuation in panic situations

Throughput Analysis on a Multi-state Manufacturing System by Considering Availability

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