Robust Process Capability Indices for Multivariate Linear Profiles

Toosi, Golnoosh; Ahmadi, Mohammad Mahdi

doi:10.1109/sieds58326.2023.10137780

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…A mathematical model is provided that considers the impact of long-term maintenance policies in addition to short-term conditions, aiming to minimize preventive and corrective maintenance costs in manufacturing systems [24]. The researchers emphasize the significance of robust estimation methods, such as M-estimators in quality control [25]. An approach is proposed for comparing numerically three maintenance strategies, involving minimal repairs at failure, replacement with complete renewal only at the first failure, and replacement with complete renewal at each failure.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Expected Failure Considering Repair Time and Degradation: A Rail System Case Study

Hamidi,

Sedaghat,

Gharehgozli

et al. 2024

JTTs

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The repeated failures of any equipment or systems are modeled as a renewal process. The management needs an assessment of the number of future failures to allocate the resources needed for fast repairs. Based on the idea of expectation by conditioning, special Volterra-type integral equations are derived for general types of repairs, considering the length of repair and reduced degradation of the idle object. In addition to minimal repair and failure replacement, partial repairs are also discussed when the repair results in reduction of the number of future failures or decreases the effective age of the object. Numerical integration-based algorithm and simulation study are performed to solve the resulting integral equation. Since the geometry degradation in different dimensions of a rail track and controlling and maintaining defects are of importance, a numerical example using the rail industry data is conducted. Expected number of failures of different failure type modes in rail track is calculated within a two-year interval. Results show that within a two-year period, anticipated occurrences of cross level failures, surface failures, and DPI failures are 2.4, 3.8, and 5.8, respectively.

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Section: Literature Reviewmentioning

confidence: 99%

Modeling Expected Failure Considering Repair Time and Degradation: A Rail System Case Study

Hamidi,

Sedaghat,

Gharehgozli

et al. 2024

JTTs

View full text Add to dashboard Cite

show abstract

“…The dataset was divided into two distinct stages: training and evaluation. The learning stage included 75% (124 instances) of the dataset, while the assessment stage encompassed 25% (42 instances) of the dataset [54][55][56][57]. Understanding the design and building of a certain item help experts perform analysis and ensure compliance with engineering standards.…”

Section: Data Description and Pre-processingmentioning

confidence: 99%

Optimization-Based Fuzzy System Application on Deformation of Geogrid-Reinforced Soil Structures

Dou

2024

Int J Comput Intell Syst

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When it comes to the geosynthetic-reinforced soil structures’ structural design, the analysis of deformation is of the highest relevance. In spite of this, the academic literature lays a substantial amount of attention on the potential of artificial intelligence approaches in efficiently addressing the many challenges that are faced in geotechnical engineering. The investigation of the possible use of approaches based on machine learning for the purpose of forecasting the geogrid-reinforced soil structures’ deformation ($${\text{Dis}}$$ Dis ) was the major focus of this study. These efforts are made to reduce the time and cost of numerical modeling. This study aimed to enable computers to learn patterns and insights from data to make accurate predictions or decisions about unseen data. This paper introduces novel systems that coupled the Beluga whale optimizer ($${\text{BWH}}$$ BWH ), Henry gas solubility optimization ($${\text{HGSO}}$$ HGSO ), gannet optimization algorithm ($${\text{GOA}}$$ GOA ), and Harris hawks optimizer ($${\text{HHO}}$$ HHO ) with adaptive neuro-fuzzy inference system ($${\text{ANFIS}}$$ ANFIS ). A dataset was created by gathering 166 finite element analyses accomplished in the literature. Between four $${\text{ANFIS}}$$ ANFIS systems, the integrated one with $${\text{GOA}}$$ GOA got the largest accuracy value, accounting for 0.9841 and 0.9895 in the train and test stages, better than $${\text{ANF}}_{{{\text{BWH}}}}$$ ANF BWH , followed by $${\text{ANF}}_{{{\text{HH}}}}$$ ANF HH . It was seen from $${\text{U}}_{{{95}}} { }$$ U 95 that the $${\text{ANF}}_{{{\text{GOA}}}} { }$$ ANF GOA scenario exhibits the least level of uncertainty in comparison to other models, hence demonstrating its greater capacity for generalization. Between four $${\text{ANFIS}}$$ ANFIS systems, the most accurate system with the lowest $${\text{OBJ}}$$ OBJ value is $${\text{ANF}}_{{{\text{GOA}}}}$$ ANF GOA at 2.6098, followed by $${\text{ANF}}_{{{\text{BWH}}}}$$ ANF BWH at 2.8002. Sensitivity analysis depicts that removing the surcharge $$\left( q \right)$$ q parameter from the input group has a considerable negative impact on output accuracy.

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“…conceptual model was used to predict commodity SCP through SEM with PLS estimation(Kamranfar et al, 2023;Toosi & Ahmadi, 2023). The PLS method estimated the model based on research hypotheses, while bootstrapping with 300 subsamples calculated t-statistic values for path coefficient significance.…”

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confidence: 99%

Exploring the impact of supply chain integration and agility on commodity supply chain performance

Saeid Dokhanian,

Abolfazl Sodagartojgi,

Kian Tehranian

et al. 2024

World J. Adv. Res. Rev.

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The aim of this research was to explore the influence of supply chain integration (SCI) on commodity supply chain performance (SCP) with the mediating role of supply chain agility (SCA). The research methodology employed a correlational approach using structural equation modeling. 131 employees from active companies in the agricultural commodity supply chain (SC) sector in Iran participated in the study. Analysis of the data was carried out utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) employing SMARTPLS software. The results indicate that customer integration (CI), supplier integration (SI), and internal integration have a positive and significant impact on SCA and commodity SCP. Additionally, the influence of SCA on commodity SCP is positive and significant. SCA plays a positive and significant mediating role in the impact of CI, SI, and internal integration on commodity SCP. Therefore, it can be concluded that companies that possess CI, SI, and internal integration in their commodity SC process demonstrate more satisfactory performance in the commodity SC.

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Robust Process Capability Indices for Multivariate Linear Profiles

Cited by 4 publications

References 20 publications

Modeling Expected Failure Considering Repair Time and Degradation: A Rail System Case Study

Modeling Expected Failure Considering Repair Time and Degradation: A Rail System Case Study

Optimization-Based Fuzzy System Application on Deformation of Geogrid-Reinforced Soil Structures

Exploring the impact of supply chain integration and agility on commodity supply chain performance

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