An extended geometric process and its application in replacement policy

2019 ◽  
Vol 234 (1) ◽  
pp. 88-103
Author(s):  
Wenke Gao
Keyword(s):  
Process Model ◽  
Manufacturing Systems ◽  
Failure Time ◽  
Replacement Policy ◽  
Recovery Factor ◽  
Estimation Methods ◽  
Repairable Systems ◽  
Geometric Process ◽  
The Mean ◽  
Parameter Estimation Methods

In this article, we develop an extended geometric process model with a recovery factor and propose a two-dimensional evaluation function for each maintenance effect. The developed model can describe the mean inter-failure time which can be improved by the first or several former repairs in some repairable systems. We also propose parameter estimation methods for the developed geometric process model and use some real failure datum to prove the model’s application. Focused on the developed geometric process model, two novel replacement policies and their optimizations are also presented in detail. Then, two real case studies are discussed to illustrate the modelling and optimizing process. Modelling results show that each recovery factor is related to the effect of each repair, and the developed geometric process model has a good-fitting property for some real cases. Optimization results display that the optimal ( N, m) replacement policy is applicable for some small-sized manufacturing systems, whereas the proposed ( N) replacement policy is suitable for some expensive systems.

scholarly journals Optimal order-replacement policy for a phase-type geometric process model with extreme shocks

2014 ◽  
Vol 38 (17-18) ◽  
pp. 4323-4332 ◽  
Author(s):  
Miaomiao Yu ◽  
Yinghui Tang ◽  
Wenqing Wu ◽  
Jie Zhou
Keyword(s):  
Process Model ◽  
Replacement Policy ◽  
Optimal Order ◽  
Geometric Process ◽  
Phase Type

scholarly journals A Monotone Process Maintenance Model for a Multistate System

2005 ◽  
Vol 42 (01) ◽  
pp. 1-14 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Average Cost ◽  
Process Model ◽  
Replacement Policy ◽  
Geometric Process ◽  
Optimal Replacement ◽  
Multistate System ◽  
Long Run ◽  
Optimal Replacement Policy ◽  
Monotone Process ◽  
Maintenance Model

In this paper, we study a monotone process maintenance model for a multistate system with k working states and ℓ failure states. By making different assumptions, we can apply the model to a multistate deteriorating system as well as to a multistate improving system. We show that the monotone process model for a multistate system is equivalent to a geometric process model for a two-state system. Then, for both the deteriorating and the improving system, we analytically determine an optimal replacement policy for minimizing the long-run average cost per unit time.

scholarly journals Laplace-Stieltjes transform of the system mean lifetime via geometric process model

2016 ◽  
Vol 14 (1) ◽  
pp. 384-392 ◽  
Author(s):  
Gökhan Gökdere ◽  
Mehmet Gürcan
Keyword(s):  
Process Model ◽  
Operating Time ◽  
Reliability Function ◽  
Engineering Systems ◽  
Stieltjes Transform ◽  
Lifetime Distributions ◽  
Geometric Process ◽  
Mean Lifetime ◽  
Aging Property ◽  
The Mean

AbstractOperation principle of the engineering systems occupies an important role in the reliability theory. In most of the studies, the reliability function of the system is obtained analytically according to the structure of the system. Also in such studies the mean operating time of the system is calculated. However, the reliability function of some systems, such as repairable system, cannot be easily obtained analytically. In this case, forming Laplace-Stieltjes transform of the system can provide a solution to the problem. In this paper, we have designed a system which consists of two components that can be repairable with the aging property. Firstly, the Laplace-Stieltjes transform of the system is formed. Later, the mean operating time of the system is calculated by means of Laplace-Stieltjes transform. The system’s repair policy is evaluated depending on the geometric process. This property provides the aging of the system. We also provide special systems with different marginal lifetime distributions to illustrate the theoretical results in this study.

scholarly journals A Monotone Process Maintenance Model for a Multistate System

2005 ◽  
Vol 42 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Average Cost ◽  
Process Model ◽  
Replacement Policy ◽  
Geometric Process ◽  
Optimal Replacement ◽  
Multistate System ◽  
Long Run ◽  
Optimal Replacement Policy ◽  
Monotone Process ◽  
Maintenance Model

In this paper, we study a monotone process maintenance model for a multistate system with k working states and ℓ failure states. By making different assumptions, we can apply the model to a multistate deteriorating system as well as to a multistate improving system. We show that the monotone process model for a multistate system is equivalent to a geometric process model for a two-state system. Then, for both the deteriorating and the improving system, we analytically determine an optimal replacement policy for minimizing the long-run average cost per unit time.

Biorefinery implementation for recovery debottlenecking at existing pulp mills- Part II: Techno-economic evaluation

TAPPI Journal ◽  
2012 ◽  
Vol 11 (8) ◽  
pp. 17-24 ◽  
Author(s):  
HAKIM GHEZZAZ ◽  
LUC PELLETIER ◽  
PAUL R. STUART
Keyword(s):  
Cost Estimation ◽  
Process Model ◽  
Black Liquor ◽  
Pulp Mill ◽  
Value Added ◽  
Economic Assessment ◽  
Extraction Process ◽  
Estimation Methods ◽  
Precipitation Process

The evaluation and process risk assessment of (a) lignin precipitation from black liquor, and (b) the near-neutral hemicellulose pre-extraction for recovery boiler debottlenecking in an existing pulp mill is presented in Part I of this paper, which was published in the July 2012 issue of TAPPI Journal. In Part II, the economic assessment of the two biorefinery process options is presented and interpreted. A mill process model was developed using WinGEMS software and used for calculating the mass and energy balances. Investment costs, operating costs, and profitability of the two biorefinery options have been calculated using standard cost estimation methods. The results show that the two biorefinery options are profitable for the case study mill and effective at process debottlenecking. The after-tax internal rate of return (IRR) of the lignin precipitation process option was estimated to be 95%, while that of the hemicellulose pre-extraction process option was 28%. Sensitivity analysis showed that the after tax-IRR of the lignin precipitation process remains higher than that of the hemicellulose pre-extraction process option, for all changes in the selected sensitivity parameters. If we consider the after-tax IRR, as well as capital cost, as selection criteria, the results show that for the case study mill, the lignin precipitation process is more promising than the near-neutral hemicellulose pre-extraction process. However, the comparison between the two biorefinery options should include long-term evaluation criteria. The potential of high value-added products that could be produced from lignin in the case of the lignin precipitation process, or from ethanol and acetic acid in the case of the hemicellulose pre-extraction process, should also be considered in the selection of the most promising process option.

scholarly journals A Bimodal Extension of the Exponential Distribution with Applications in Risk Theory

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 679
Author(s):  
Jimmy Reyes ◽  
Emilio Gómez-Déniz ◽  
Héctor W. Gómez ◽  
Enrique Calderín-Ojeda
Keyword(s):  
Exponential Distribution ◽  
Hazard Rate ◽  
Rate Function ◽  
Estimation Methods ◽  
Inverse Gaussian ◽  
New Family ◽  
Tail Distribution ◽  
Zero Values ◽  
The Mean ◽  
Positive Support

There are some generalizations of the classical exponential distribution in the statistical literature that have proven to be helpful in numerous scenarios. Some of these distributions are the families of distributions that were proposed by Marshall and Olkin and Gupta. The disadvantage of these models is the impossibility of fitting data of a bimodal nature of incorporating covariates in the model in a simple way. Some empirical datasets with positive support, such as losses in insurance portfolios, show an excess of zero values and bimodality. For these cases, classical distributions, such as exponential, gamma, Weibull, or inverse Gaussian, to name a few, are unable to explain data of this nature. This paper attempts to fill this gap in the literature by introducing a family of distributions that can be unimodal or bimodal and nests the exponential distribution. Some of its more relevant properties, including moments, kurtosis, Fisher’s asymmetric coefficient, and several estimation methods, are illustrated. Different results that are related to finance and insurance, such as hazard rate function, limited expected value, and the integrated tail distribution, among other measures, are derived. Because of the simplicity of the mean of this distribution, a regression model is also derived. Finally, examples that are based on actuarial data are used to compare this new family with the exponential distribution.

On classes of life distributions based on the mean time to failure function

2021 ◽  
Vol 58 (2) ◽  
pp. 289-313
Author(s):  
Ruhul Ali Khan ◽  
Dhrubasish Bhattacharyya ◽  
Murari Mitra
Keyword(s):  
Damage Model ◽  
Replacement Policy ◽  
Time To Failure ◽  
Mean Time To Failure ◽  
Moment Convergence ◽  
Life Distributions ◽  
Cumulative Damage Model ◽  
The Mean ◽  
Age Replacement ◽  
Mean Time

AbstractThe performance and effectiveness of an age replacement policy can be assessed by its mean time to failure (MTTF) function. We develop shock model theory in different scenarios for classes of life distributions based on the MTTF function where the probabilities $\bar{P}_k$ of surviving the first k shocks are assumed to have discrete DMTTF, IMTTF and IDMTTF properties. The cumulative damage model of A-Hameed and Proschan [1] is studied in this context and analogous results are established. Weak convergence and moment convergence issues within the IDMTTF class of life distributions are explored. The preservation of the IDMTTF property under some basic reliability operations is also investigated. Finally we show that the intersection of IDMRL and IDMTTF classes contains the BFR family and establish results outlining the positions of various non-monotonic ageing classes in the hierarchy.

scholarly journals Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka
Keyword(s):  
Short Wave ◽  
Machine Learning Algorithms ◽  
Estimation Methods ◽  
Chemical Information ◽  
Tea Quality ◽  
The Mean ◽  
Processing Techniques ◽  
Spectral Patterns ◽  
Physical And Chemical ◽  
Non Destructive

AbstractSpectroscopic sensing provides physical and chemical information in a non-destructive and rapid manner. To develop non-destructive estimation methods of tea quality-related metabolites in fresh leaves, we estimated the contents of free amino acids, catechins, and caffeine in fresh tea leaves using visible to short-wave infrared hyperspectral reflectance data and machine learning algorithms. We acquired these data from approximately 200 new leaves with various status and then constructed the regression model in the combination of six spectral patterns with pre-processing and five algorithms. In most phenotypes, the combination of de-trending pre-processing and Cubist algorithms was robustly selected as the best combination in each round over 100 repetitions that were evaluated based on the ratio of performance to deviation (RPD) values. The mean RPD values were ranged from 1.1 to 2.7 and most of them were above the acceptable or accurate threshold (RPD = 1.4 or 2.0, respectively). Data-based sensitivity analysis identified the important hyperspectral regions around 1500 and 2000 nm. Present spectroscopic approaches indicate that most tea quality-related metabolites can be estimated non-destructively, and pre-processing techniques help to improve its accuracy.

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