Availability analysis and case study of mobile-OTP key generation using skip sampling of voice

2016 ◽  
Vol 19 (4) ◽  
pp. 1865-1878 ◽  
Author(s):  
ByungRae Cha ◽  
Sun Park ◽  
JongWon Kim
Keyword(s):  
Key Generation ◽  
Availability Analysis ◽  
Skip Sampling

scholarly journals Integrated Coastal Management Dynamic Models: A Case Study of Development Seaweed Cultivation in the Waters Luwu and Palopo Regency Bone Bay, South Sulawesi

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Walu Yo ◽  
Yonvit Ner ◽  
Etty Riani ◽  
Dan Taslim Arifin
Keyword(s):  
Ecological Footprint ◽  
Dynamic Models ◽  
Ecological Status ◽  
Scenario Simulation ◽  
Seaweed Cultivation ◽  
Entire Area ◽  
Availability Analysis ◽  
South Sulawesi ◽  
Seaweed Culture

Waters carrying capacity in seaweed of Eucheuma cottonii cultures should be a concernforoptimum seaweed culture. Carryingcapacity can determine by Ecological Footprint (EF) analysis, which in this research usefootprint production, and mas balance nitrate analysis. This research on Mei 2015 (1sttransitionalseason) and September 2015 (2ndtransitionalseason) in Luwu and Palopo, South Sulawesi. Map and land use analyzed with  geographic information systems (GIS).The results showed that theEcological Footprint production (EFP)in Luwu waters is 67,88 ton/capita/year, or equivalent to 235.823,93 tons/year.Based on the analysis of the availability of water for seaweed is 38.374,69 hectares, it can produce seaweed (biocapacity) for 922.928,96 tons/year and  the number of farmers that allows for use the waters is  13.595 capita. The Ecological Footprint  production (EFp) in Palopo waters is 3,08 ton/capita/year, or equivalent to 4.589,99 tons/year. Water availability analysis is 979,82 hectares are able to produce seaweed (biocapacity) for10.115,34 ton/year and the number of farmers that allows for use the waters is 3.276 capita. Based on the four scenario simulation management results of the development seaweed cultivation Eucheumacottonii in Luwu and PalopoRegency is based on the present waste input, pressing inputs of waste into the waters of 10%, 25% and 50% yield different waters biocapacity. The results comparison between biocapacity and Ecological Footprint, ecological status for  Luwu and Palopo waters are still in sustainable use.Based on those simulation results showed that in second scenario by pressing the waste input by 10% from the existing waste input, as well as assuming the availability of water utilizing the entire area of 38.374,69 hectares continuously (on the years scale of 2008-2030), it will produce the highest biocapacity waters in the amount of 8.257.274,94 tons/year. So with the management of seaweed in Palopo with second scenario, assuming the availability of water utilizing the entire area of 979,82 hectares will produce the highest waters biocapacity of 14.306,92 tons/year.

Integration between RCM and RAM: a case study

2016 ◽  
Vol 33 (6) ◽  
pp. 852-880 ◽  
Author(s):  
Ilaria De Sanctis ◽  
Claudia Paciarotti ◽  
Oreste Di Giovine
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Practical Method ◽  
Environmental Safety ◽  
Gas Industry ◽  
Content Type ◽  
Availability Analysis ◽  
Plant Safety ◽  
Offshore Industry

Purpose – The purpose of this paper is to propose a practical method of performing maintenance in the offshore industry where engineers have to manage problems such as the high cost of operations, assuring an high availability of the plant, safety on board and environmental protection. Indeed an efficient maintenance method it is necessary in order to offer methods and criteria to select the rights maintenance strategies keeping in to account the environmental, safety and production constrains. Design/methodology/approach – The paper provides an overview of reliability centered maintenance (RCM) and reliability, availability, maintainability methodologies and an integration of the two methodologies in a particular case study in the oil and gas sector. Findings – This paper suggests an improvement of the well-established RCM methodology applicable to industries with high priority level. It is proposed an integration between a reliability analysis and an availability analysis and an application on the offshore oil and gas industry. Practical implications – The methodology provides an excellent tool that can be utilized in industries, where safety, regulations and the availability of the plant play a fundamental role. Originality/value – The proposed methodology provides a practical method for selecting the best maintenance strategy considering the equipment redundancy and sparing, the asset’s performance over long time scales, and the system uptime, downtime and slowdowns.

Availability analysis of combustion flue gases—A case study

1995 ◽  
Vol 36 (12) ◽  
pp. 1133-1137 ◽  
Author(s):  
M. Abu-Arabi ◽  
A. Tamimi
Keyword(s):  
Flue Gases ◽  
Availability Analysis

Effect of Failure Rate on the Availability Analysis of Nestle CERELAC Plant Using Markov Chain Method

2018 ◽  
pp. 121-127
Author(s):  
Gurbinder Singh ◽  
Rakesh Kumar
Keyword(s):  
Markov Chain ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Research Work ◽  
Automated Production ◽  
Availability Analysis ◽  
Long Run ◽  
Machine Reliability ◽  
Markov Chain Method

In the performance analysis of production systems by using the traditional methods of engineering the knowledge of machine reliability factors is assumed to be precisely known. The current study entitled performance evaluation of food industry in India. To analyze and determine the availability of plant a case study has been undertaken from Moga Nestle food private limited industry in India. Various studies evaluating the performance of automated production systems with the help of modeling and simulation and analytical methods have always given priority to steady state performance as compared to transient performance. Production systems in which such kind of situations arises include systems with dysfunctional states and deadlocks, not stable queuing systems. This research work presents an approach for analyzing the performance of unreliable manufacturing systems that take care of uncertain machine factor estimates. The method that is being proposed is on the basis of Markov chain and probability density function discretization techniques for studying manufacture lines consist unreliable machines. To determine the performance of plant, important information has been collected from different systems and subsystems to find out long run availability of whole system.

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