Search results

1 – 10 of over 120000
To view the access options for this content please click here
Article
Publication date: 1 August 2003

Paul Feldman

The Australian Series system is an archival control or metadata system, used primarily to describe records in the custody of archival institutions. However, the article…

Downloads
1632

Abstract

The Australian Series system is an archival control or metadata system, used primarily to describe records in the custody of archival institutions. However, the article explains how concepts and descriptive model embodied in the system can also be usefully employed to document the content, context and management requirements of current records, including electronic records, at an aggregate level. This can assist in situations where records have been undermanaged, where the functionality of existing systems is limited, or where there are multiple localised systems. The system can be used as a basis to gather and present structured evidence of the need to improve existing practices. It can also assist the management of legacy records, once improved systems have been established.

Details

Records Management Journal, vol. 13 no. 2
Type: Research Article
ISSN: 0956-5698

Keywords

To view the access options for this content please click here
Article
Publication date: 29 July 2014

Kanchan Jain, Isha Dewan and Monika Rani

Joint reliability importance (JRI) of components is the effect of a change of their reliability on the system reliability. The authors consider two coherent…

Abstract

Purpose

Joint reliability importance (JRI) of components is the effect of a change of their reliability on the system reliability. The authors consider two coherent multi-component systems – a series-in-parallel (series subsystems arranged in parallel) and a parallel-in-series (parallel subsystems arranged in series) system. It is assumed that all the components in the subsystems are independent but not identically distributed. The subsystems do not have any component in common. The paper aims to discuss these issues.

Design/methodology/approach

For both the systems, the expressions for the JRI of two or more components are derived. The results are extended to include subsystems where some of the components are replicated.

Findings

The findings are illustrated by considering bridge structure as a series-in-parallel system wherein some of the components are repeated in different subsystems. Numerical results have also been provided for a series-in-parallel system with unreplicated components. JRI for various combinations of components for both the illustrations are given through tables or figures.

Originality/value

Chang and Jan (2006) and Gao et al. (2007) found the JRI of two components of series-in-parallel system when the components are identical and independently distributed. The authors derive the JRI of m=2 components for series-in-parallel and parallel-in-series systems when components are independent but need not be identically distributed. Expressions are obtained for the above-mentioned systems with replicated and unreplicated components in different subsystems. These results will be useful in analyzing the joint effect of reliability of several components on the system reliability. This will be of value to design engineers for designing systems that function more effectively and for a longer duration.

Details

International Journal of Quality & Reliability Management, vol. 31 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

To view the access options for this content please click here
Article
Publication date: 23 August 2011

Neal Wagner, Zbigniew Michalewicz, Sven Schellenberg, Constantin Chiriac and Arvind Mohais

The purpose of this paper is to describe a real‐world system developed for a large food distribution company which requires forecasting demand for thousands of products…

Downloads
3632

Abstract

Purpose

The purpose of this paper is to describe a real‐world system developed for a large food distribution company which requires forecasting demand for thousands of products across multiple warehouses. The number of different time series that the system must model and predict is on the order of 105. The study details the system's forecasting algorithm which efficiently handles several difficult requirements including the prediction of multiple time series, the need for a continuously self‐updating model, and the desire to automatically identify and analyze various time series characteristics such as seasonal spikes and unprecedented events.

Design/methodology/approach

The forecasting algorithm makes use of a hybrid model consisting of both statistical and heuristic techniques to fulfill these requirements and to satisfy a variety of business constraints/rules related to over‐ and under‐stocking.

Findings

The robustness of the system has been proven by its heavy and sustained use since being adopted in November 2009 by a company that serves 91 percent of the combined populations of Australia and New Zealand.

Originality/value

This paper provides a case study of a real‐world system that employs a novel hybrid model to forecast multiple time series in a non‐static environment. The value of the model lies in its ability to accurately capture and forecast a very large and constantly changing portfolio of time series efficiently and without human intervention.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 15 March 2011

Yi‐Hui Liang

The purpose of this study is to propose the time series decomposition approach to analyze and predict the failure data of the repairable systems.

Downloads
1286

Abstract

Purpose

The purpose of this study is to propose the time series decomposition approach to analyze and predict the failure data of the repairable systems.

Design/methodology/approach

This study employs NHPP to model the failure data. Initially, Nelson's graph method is employed to estimate the mean number of repairs and the MCRF value for the repairable system. Second, the time series decomposition approach is employed to predict the mean number of repairs and MCRF values.

Findings

The proposed method can analyze and predict the reliability for repairable systems. It can analyze the combined effect of trend‐cycle components and the seasonal component of the failure data.

Research limitations/implications

This study only adopts simulated data to verify the proposed method. Future research may use other real products' failure data to verify the proposed method. The proposed method is superior to ARIMA and neural network model prediction techniques in the reliability of repairable systems.

Practical implications

Results in this study can provide a valuable reference for engineers when constructing quality feedback systems for assessing current quality conditions, providing logistical support, correcting product design, facilitating optimal component‐replacement and maintenance strategies, and ensuring that products meet quality requirements.

Originality/value

The time series decomposition approach was used to model and analyze software aging and software failure in 2007. However, the time series decomposition approach was rarely used for modeling and analyzing the failure data for repairable systems. This study proposes the time series decomposition approach to analyze and predict the failure data of the repairable systems and the proposed method is better than the ARIMA model and neural networks in predictive accuracy.

Details

International Journal of Quality & Reliability Management, vol. 28 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

To view the access options for this content please click here
Article
Publication date: 8 February 2019

Ricardo Puziol Oliveira and Jorge Alberto Achcar

The purpose of this paper is to provide a new method to estimate the reliability of series system by using a discrete bivariate distribution. This problem is of great…

Abstract

Purpose

The purpose of this paper is to provide a new method to estimate the reliability of series system by using a discrete bivariate distribution. This problem is of great interest in industrial and engineering applications.

Design/methodology/approach

The authors considered the Basu–Dhar bivariate geometric distribution and a Bayesian approach with application to a simulated data set and an engineering data set.

Findings

From the obtained results of this study, the authors observe that the discrete Basu–Dhar bivariate probability distribution could be a good alternative in the analysis of series system structures with accurate inference results for the reliability of the system under a Bayesian approach.

Originality/value

System reliability studies usually assume independent lifetimes for the components (series, parallel or complex system structures) in the estimation of the reliability of the system. This assumption in general is not reasonable in many engineering applications, since it is possible that the presence of some dependence structure between the lifetimes of the components could affect the evaluation of the reliability of the system.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

To view the access options for this content please click here
Article
Publication date: 1 January 1989

Shashwati Guha and K.K. Aggarwal

The process by which the system failure allowance is allocated in some logical manner among its subsystems is termed Reliability Allocation. Many methods are available for…

Abstract

The process by which the system failure allowance is allocated in some logical manner among its subsystems is termed Reliability Allocation. Many methods are available for such an allocation for series system but no method exists in case the system is non‐series‐parallel. In this article, the optimum allocation of reliability among its subsystems for general non‐series‐parallel systems has been discussed by extending the Minimum Effort Method which in its present form is applicable for series systems only. A number of effort functions are listed with a view to finding one which is suitable for application in this method and the same has been used for further calculations.

Details

International Journal of Quality & Reliability Management, vol. 6 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

To view the access options for this content please click here
Article
Publication date: 1 August 1993

Zhanbo Yang

Following Ma, Yonghao and Yi Lin's definition of a mathematical model of general systems in 1987, shows the class of all general systems with relation‐reversion mappings…

Abstract

Following Ma, Yonghao and Yi Lin's definition of a mathematical model of general systems in 1987, shows the class of all general systems with relation‐reversion mappings and that of all general systems with relation‐preserving mappings to be productive, co‐productive categories Answers two questions posed in earlier published papers and poses some more questions for solution.

Details

Kybernetes, vol. 22 no. 8
Type: Research Article
ISSN: 0368-492X

Keywords

To view the access options for this content please click here
Article
Publication date: 23 August 2011

Rodolfo Baggio and Ruggero Sainaghi

Tourism systems have been considered more and more in the light of complexity and chaos theories. Most of the work done in this area has highlighted the reasons for and…

Downloads
3766

Abstract

Purpose

Tourism systems have been considered more and more in the light of complexity and chaos theories. Most of the work done in this area has highlighted the reasons for and the issues regarding this approach. A steadily growing strand of the recent literature uses the theories to overcome the problems of a reductionist and mechanistic view that is considered unable to provide a full understanding of the structural and dynamic characteristics of tourism systems, and specifically of tourism destinations. This paper seeks to continue this approach and to provide a series of quantitative methods to assess the dynamics of non‐linear complex tourism systems.

Design/methodology/approach

The time series used in the paper contains data collected from a sample of 23 large (four‐star) hotels located in Milan, Italy. For each structure daily data of occupancy, average room rate and RevPAR (revenue per available room) were recorded for the period 2006‐2009. The daily distributions of these observations are highly skewed, and therefore the median of the daily values were considered. This results in three series of 1,461 points per type (occupancy, room rate and RevPAR).

Findings

The data confirm the complex nature of the destination system and its tendency towards a chaotic state. Additionally, high stability and long memory effects are detected. The outcomes and the implications of this analysis are examined.

Research limitations/implications

A comparison of the values obtained leads to the conclusion that the series under study has a detectable level of non‐linearity, even if it does not reach the pure chaoticity of the Lorenz attractor. A first conclusion is that, as qualitatively assessed in many similar studies, the tourism destination is a complex system with a tendency to become chaotic.

Originality/value

The picture obtained with the analyses conducted can be summarised by saying that the system under study exhibits an unequivocally complex nature. It tends towards a chaotic stage but does so at a slow pace. The stability of the system is quite high: it might be able to resist transient shocks well but, once led in one direction, its long memory characteristics tend to keep it on the resulting path.

Details

International Journal of Contemporary Hospitality Management, vol. 23 no. 6
Type: Research Article
ISSN: 0959-6119

Keywords

To view the access options for this content please click here
Article
Publication date: 26 May 2020

Changhai Lin, Zhengyu Song, Sifeng Liu, Yingjie Yang and Jeffrey Forrest

The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the…

Abstract

Purpose

The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain.

Design/methodology/approach

The AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain.

Findings

Through the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system's behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity.

Practical implications

The AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are short-period factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1-AGO acting, the information mining and extrapolation prediction will have a good effect.

Originality/value

The authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time.

Details

Grey Systems: Theory and Application, vol. 11 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 11 May 2015

Ghofrane Maaroufi, Anis Chelbi, Nidhal Rezg and Ait-Kadi Daoud

The purpose of this paper is to determine a nearly optimal inspection sequence for a series system consisting of two components subject to gradual deterioration and whose…

Abstract

Purpose

The purpose of this paper is to determine a nearly optimal inspection sequence for a series system consisting of two components subject to gradual deterioration and whose failures are not self-announcing and can be detected only through inspection.

Design/methodology/approach

The problem is tackled in the context of condition-based maintenance (CBM) with a maintenance model in the class of the control-limit policies for which the maintenance decision is made following inspection by comparison of the deterioration level to critical thresholds. A mathematical model is developed to express the total expected cost per time unit as a function of the inspection instants.

Findings

For any given series system composed of two components with known critical deterioration threshold levels, and for any given set of costs related to inspection, inactivity due to failure, and preventive and corrective replacements of each component, a nearly optimal inspection sequence of the system is derived such as the total expected cost is reduced.

Research limitations/implications

Due to the complexity of the cost model with the inspection instants (×1, ×2, ×3, …) being the decision variables, it has not been possible to derive the optimal solution. A quasi-optimal sequence of inspection times is derived along with the corresponding total average cost per time unit.

Practical implications

In many practical situations in which CBM is implemented, a tradeoff between inspection costs and inactivity and replacement costs has to be balanced when determining the intervals between successive inspections at which the degradation level of the components should be assessed and compared to predetermined critical threshold levels. Inspecting too often would increase inspection costs but in the same time it would also increase the probability to avoid a failure and end up with a preventive replacement, whereas not inspecting often enough would increase the probability to end up with a failure increasing replacement and inactivity costs.

Originality/value

While the inspection problem has been largely treated for single component systems, inspection policies become much more complex when considering multi-component systems. A two-component series system is considered in this paper.

Details

Journal of Quality in Maintenance Engineering, vol. 21 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

1 – 10 of over 120000