@article {34418, title = {Assessing measurement system agreement in the presence of reproducibility and repeatability}, journal = {Technometrics}, year = {2023}, pages = {1-20}, abstract = {Assessing the agreement between an established and a new measurement system is a practical and important challenge in many application areas. The probability of agreement (PoA) has recently been introduced as a metric to assess such agreement when repeatability, the precision of the measurement system itself, represents the overall measurement system variation. However, it is common in practice for the measurement system to be operated by multiple individuals, and their effects can be an important part of the overall variation. Reproducibility represents the measurement variability attributable to different operators. This paper extends the PoA methodology to account for both the repeatability and reproducibility of each measurement system along with the relative bias between them. The developed methodology also allows imbalanced replicate measurements across operators and systems, while the operator effects can either be fixed or random. We use maximum likelihood estimation to estimate the PoA. The proposed approach is illustrated using two case studies. In the first one, we compare the agreement between an old and a new measurement system used for quality inspections in an industrial context. The second case study which is presented in\ Supplementary Materials\ file assesses the agreement between two devices used to measure respiratory rates.}, url = {https://www.tandfonline.com/doi/full/10.1080/00401706.2023.2296465}, author = {Adel Ahmadi Nadi and Stefan H Steiner and Nathaniel T Stevens} } @article {32087, title = {Control charts for monitoring relative risk rate in the presence of Weibull competing risks with censored and masked data}, journal = {Quality Technology \& Quantitative Management}, year = {2023}, abstract = {Competing risks data frequently appear in real-world operations like quality inspections, survival analysis, reliability tests, and clinical trials. From the quality point of view, relative risk rate can be considered an interesting quality indicator in analyzing the competing risks data for statistical process monitoring purposes. The relative risk rate measures the proportion of failures caused by the primary risk among a set of competing risks. This paper introduces two Shewhart-type control charts for monitoring the relative risk rate when the lifetimes of competing risks are independent Weibull random variables. The former chart is constructed based on the maximum likelihood estimation method, while the latter is developed based on the Bayesian approach. The proposed control charts can be applied in Phase II. The calculation of the Bayesian control charts and the evaluation of both process monitoring techniques have been done based on Monte Carlo simulations. The performance of the proposed control charts has been examined based on the average run length metric. The illustrative example is also discussed in detail to demonstrate the applicability of the proposed methods.}, url = {https://www.tandfonline.com/doi/full/10.1080/16843703.2023.2193773}, author = {Adel Ahmadi Nadi and Robab Afshari and Bahram Sadeghpour Gildeh} } @article {32026, title = {Copula-based multivariate EWMA control charts for monitoring the mean vector of bivariate processes using a mixture model}, journal = {Communications in Statistics - Theory and Methods }, year = {2023}, pages = {1-24}, abstract = {Control charts are the main tools in the statistical process monitoring area to investigate how the quality of production remains stable or changes over time. This article develops Hotelling{\textquoteright}s\ T2\ and multivariate exponentially weighted moving average (MEWMA) control charts for monitoring the mean vector of processes when observations come from a mixture copula model including, Gumbel, Clayton, and Frank copulas. The proposed mixture model enables the quality inspectors to cover several dependence levels of observations, from weak and moderate to strong in positive values by Kendall{\textquoteright}s tau. To assess the performance of the proposed charts, extensive Monte-Carlo simulations were conducted based on the average run length (ARL) metric for both in-control and out-of-control states by considering a bivariate process with normal marginals. For more illustration, the step-by-step procedure of the proposed monitoring technique implementation has been investigated in a computer manufacturing process with both Phases I and II analysis.}, url = {https://www.tandfonline.com/eprint/DSW7ZDRJAZGPDSGQT8S8/full?target=10.1080/03610926.2023.2176717}, author = {Hussam Ahmad and Mohammad Amini and Bahram Sadeghpour Gildeh and Adel Ahmadi Nadi} } @article {31714, title = {Cost-effective optimization strategies and sampling plan for Weibull quantiles under type-II censoring}, journal = {Applied Mathematical Modelling}, volume = {116}, year = {2023}, pages = {16-31}, abstract = {This article introduces a conditional reliability sampling plan for the Weibull distribution. The plan is applicable when the interested quality characteristic is a lower quantile and the life data are observed according to a progressive type-II censoring scheme. It is called {\textquotedblleft}conditional{\textquotedblright}, since its operating characteristic function is derived by conditioning on a vector of ancillary statistics. We approximate the conditional operating characteristic function by a fixed vector that does not change by the sample. The plan is optimally designed by concentrating on economic considerations while the producer{\textquoteright}s and consumer{\textquoteright}s confidences are satisfied. In this regard, three cost models are proposed. The first cost function is constructed based on the inspection cost, while the second model accounts for the inaccurate estimation cost. The third cost function is a weighted-relative combination of the other two costs. Based on some combinations of requirements, the optimal plan parameters are prepared in some tables. We further conduct a series of simulations to show that the approximated conditional operating characteristic function can ensure the inspection{\textquoteright}s risks well. Finally, an example based on the well-known data set on the strength of carbon fibers is discussed to demonstrate the applicability of the proposed plan.}, url = { https://www.sciencedirect.com/science/article/pii/S0307904X22005455}, author = {Adel Ahmadi Nadi and Bahram Sadeghpour Gildeh and Jaber Kazempoor and Kim Duc Tran and Kim Phuc Tran} } @article {31770, title = {Monitoring processes with multiple dependent production lines using time between events control charts}, journal = {Quality Engineering}, year = {2023}, abstract = {This article develops Time Between Events (TBE) control charts to monitor processes with multiple dependent production lines. To this end, a Shewhart-type and an EWMA-type TBE chart have been proposed. The copula approach is used to describe the dependence between production lines and the homogeneous Poisson process is considered to model the number of defectives. The performance of the proposed methods is evaluated using the average time to signal metric. The numerical study showed that the EWMA-TBE chart uniformly performs better than the Shewhart-type chart. Eventually, the EWMA-TBE chart is applied to monitor two real-world processes with two and four production lines.}, url = {https://www.tandfonline.com/eprint/UIH4XA5H5R3X34GMWS2U/full?target=10.1080/08982112.2023.2169161}, author = {Hussam Ahmad and Adel Ahmadi Nadi and Mohammad Amini and Bahram Sadeghpour Gildeh} } @article {31727, title = {Monitoring simple linear profiles in the presence of within- and between-profile autocorrelation}, journal = {Quality and Reliability Engineering International}, volume = {39}, year = {2023}, pages = {1-24}, abstract = {The current study investigates the effect of within-profile and between-profile autocorrelations on the performance of four monitoring methods of simple linear profiles in Phase II. To this end, a general correlation model between error terms is considered such that the correlation structure of within-profiles errors and the error terms between consecutive profiles follow an autoregressive (AR) times series model of order one. Extensive simulations have been done to assess the effect of both autocorrelation types and the profile size on the estimations of the model parameters as well as the performance of control charts. The performance of the monitoring schemes is investigated and compared with respect to the average run length (ARL) metric. The simulation study results show that the autocorrelation within and between profiles has a negative impact on the monitoring technique{\textquoteright}s performance. It reduces the control chart{\textquoteright}s ability to detect process shifts compared to no or weak autocorrelation cases. Moreover, the performance of all the methods is improved by increasing the profile size. An illustrative example is also provided to demonstrate the use of the proposed methods for monitoring the stability of profiles in the chemical\ industry.}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/qre.3254}, author = {Adel Ahmadi Nadi and Ali Yeganeh and Alireza Shadman} } @article {34417, title = {Statistical inferences for the Weibull distribution under adaptive progressive type-II censoring plan and their application in wind speed data analysis}, journal = {Statistics, Optimization \& Information Computing}, volume = {11}, year = {2023}, pages = {829-852}, abstract = {This paper provides four well-known statistical inferences for the principal parameters regarding the two-parameter Weibull distribution including its hazard, quantile, and survival function based on an adaptive progressive type-II censoring plan. The statistical inferences involve the likelihood and approximate likelihood methods, the Bayesian approach, the bootstrap procedure, and a new conditional technique. To construct Bayesian point estimators and credible intervals, Markov chain Monte Carlo, Metropolis-Hastings, and Gibbs sampling algorithms were used. The Bayesian estimators are developed under conjugate and non-conjugate priors and in the presence of symmetric and asymmetric loss functions. In addition, a conditional estimation technique with interesting distributional characteristics has been introduced. The aforementioned methods are compared extensively through a series of simulations. The results of comparative study showed the superiority of the conditional approach over the other ones. Finally, the developed methods are applied to analyze well-known wind speed data.}, url = {https://scholar.google.com/citations?view_op=view_citation\&hl=en\&user=noKYwf0AAAAJ\&sortby=pubdate\&citation_for_view=noKYwf0AAAAJ:iH-uZ7U-co4C}, author = {J. Kazempoor and A. Habibirad and A. Ahamdi Nadi and G.R.M. Borzadaran} } @inbook {31717, title = {Application of MachineLearning in Statistical Process Control Charts: A Survey and Perspective}, booktitle = {Control Charts and Machine Learning for Anomaly Detection in Manufacturing}, year = {2022}, pages = {7-42}, publisher = {Springer}, organization = {Springer}, abstract = {

Over the past decades, control charts, one of the essential tools in Statistical Process Control (SPC), have been widely implemented in manufacturing industries as an effective approach for Anomaly Detection (AD). Thanks to the development of technologies like the Internet of Things (IoT) and Artificial Intelligence (AI), Smart Manufacturing (SM) has become an important concept for expressing the end goal of digitization in manufacturing. However, SM requires a more automatic procedure with capabilities to deal with huge data from the continuous and simultaneous process. Hence, traditional control charts of SPC now find difficulties in reality activities including designing, pattern recognition, and interpreting stages. Machine Learning (ML) algorithms have emerged as powerful analytic tools and great assistance that can be integrating to control charts of SPC to solve these issues. Therefore, the purpose of this chapter is first to presents a survey on the applications of ML techniques in the stages of designing, pattern recognition, and interpreting of control charts respectively in SPC especially in the context of SM for AD. Second, difficulties and challenges in these areas are discussed. Third, perspectives of ML techniques-based control charts for AD in SM are proposed. Finally, a case study of an ML-based control chart for bearing failure AD is also provided in this chapter.

}, url = {https://link.springer.com/chapter/10.1007/978-3-030-83819-5_2}, author = {Phuong Hanh Tran and Adel Ahmadi Nadi and Thi Hien Nguyen and Kim Duc Tran and Kim Phuc Tran} } @article {31358, title = {The effects of measurement errors on estimating and assessing the multivariate process capability with imprecise characteristic}, journal = {Computers \& Industrial Engineering}, volume = {172}, year = {2022}, abstract = {In industrial environments,\ process capability indices\ are daily employed as numerical metrics to summarize the performance of a process according to a\ predefined set\ of specification limits. Neglecting gauge measurement errors is a common phenomenon in process capability evaluations by researchers in laboratory investigations and by practitioners in daily operations. However, this common negligence is far from reality regardless of the employment of highly modern measuring tools, and may notably influence the efficiency of the measuring method for assessing the performance of a manufacturing process. In this paper, a linear\ covariate\ error model is applied to investigate the effects of gauge measurement errors on the classical and fuzzy estimation approaches of the multivariate process capability index\ SpkT\ for\ univariate\ and multivariate normally distributed quality characteristics with precise specification limits. Moreover,\ lower confidence bounds\ are also derived for the yield index\ SpkT\ in the presence of measurement errors and based on a fuzzy approach. In addition to the theoretical results, extensive simulations have been conducted to analyze how the behavior of the test statistic and lower confidence bound (LCB) for assessing the performance of the process is affected by different sources of the measurement errors. The obtained results indicate that a serious underestimation of the process capability occurs when the data is contaminated with measurement errors. It is also shown that the underestimation problem is somewhat solved by taking multiple measurements from the identical item. Moreover, comparative analyses show that the proposed method is superior to Scagliarini{\textquoteright}s method and Wang{\textquoteright}s way such that the negative effects of errors on underestimating the LCB are reduced in the proposed plan. This paper also extends the application of the introduced method to correlated variables. Finally, three practical examples are discussed to demonstrate the use of the proposed method in industrial applications.}, url = {https://www.sciencedirect.com/science/article/pii/S0360835222005666}, author = {R Afshari and A. Ahmadi Nadi and A. Johannssen and N. Chukhrova and K. P. Tran} } @article {31716, title = {An optimal construction of yield-based EWMA repetitive multivariate sampling plan}, journal = {Communications in Statistics - Theory and Methods}, year = {2022}, pages = {1-21}, abstract = {In this paper, a variable repetitive group sampling (VRGS) plan is proposed based on the exponentially weighted moving average (EWMA) statistic with yield index\ STpk for inspection of mutually independent and multivariate normally distributed characteristics. Plan parameters are found optimally based on asymptotic distribution of\ STpk using a non linear optimization. A simulation study indicates that the reported parameters can thoroughly warrant determined risks for finite sample sizes. This work also extends application of the proposed plan to the class of correlated characteristics. The obtained findings show that the proposed plan significantly reduces required average sample number compared to the existing modified VRGS plan, single, double, and multiple dependent state sampling plans with yield-based EWMA statistic. Two industrial examples are presented to illustrate the application of the proposed plan in real world.}, url = {https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2050401}, author = {Robab Afshari and Adel Ahmadi Nadi} } @article {31715, title = {The Shewhart-type RZ control chart for monitoring the ratio of autocorrelated variables}, journal = {International Journal of Production Research }, year = {2022}, pages = {1-26}, abstract = {In many industrial manufacturing processes, the quality of products can depend on the relative amount between two quality characteristics\ X\ and\ Y. Often, this calls for the on-line monitoring of the ratio\ Z=X/YZ=X/Y\ as a quality characteristic itself by means of a control chart. A large number of control charts monitoring the ratio have been investigated in the literature under the assumption of independent normal observations of the two quality characteristics. In practice, due to the high frequency in sensor data collection, both autocorrelation and cross-correlation between consecutive observations can exist for\ X\ and\ Y\ and should be modelled to protect against the false alarm rate inflation when implementing a control chart for monitoring the ratio\ Z=X/YZ=X/Y. In this paper, we tackle this problem by investigating the performance of the Phase II Shewhart-type RZ control chart monitoring the ratio of two normal variables whose relationship is captured by a bivariate time series autoregressive model VAR(1), which can also account for the cross-correlation between the two quality characteristics. With the numerical study, we discuss how the design and the statistical performance of the Shewhart-type RZ control chart change with the VAR(1) model{\textquoteright}s parameters. We also provide an example to illustrate the use of the Shewhart-type RZ control chart with bivariate time series of observations in a furnace process.}, url = {https://www.tandfonline.com/doi/full/10.1080/00207543.2022.2137594}, author = {Huu Du Nguyen and Adel Ahmadi Nadi and Kim Duc Tran and Philippe Castagliola and Giovanni Celano and Kim Phuc Tran} } @article {31718, title = {Monitoring the Weibull shape parameter under progressive censoring in presence of independent competing risks}, journal = {Journal of Applied Statistics}, year = {2021}, pages = {1-18}, abstract = {In this paper, monitoring the Weibull shape parameter arising from progressively censored competing risks data is investigated. The competing risks are assumed to be independent and not identically distributed from the Weibull distributions with different shape and scale parameters. Both the shape parameters can be monitored separately by the proposed control charts using censored and predicted observations. We also introduced a control chart for monitoring both shape parameters simultaneously to detect possible shifts in both opposite and the same directions. In addition, the problem of mask data is discussed and an efficient prediction method is proposed. The behavior of the average run length with and without mask data is investigated through extensive simulations. Furthermore, the effects of sample size, number of failures due to each risk, and censoring scheme on the charts{\textquoteright} performance are also studied. Finally, an illustrative example is presented to demonstrate the application of the proposed control charts by investigating a real data set of the failure times of two-component ARC-1 VHF communication transmitter receivers of a single commercial airline. Although this data set has been widely investigated in reliability analysis studies, this is the first time it has been analyzed in a statistical process monitoring setting.}, author = {Rusul Mohsin Moharib Alsarray and Jaber Kazempoor and Adel Ahmadi Nadi} } @article {31719, title = {One-sided Shewhart control charts for monitoring the ratio of two normal variables in short production runs}, journal = {Journal of Manufacturing Processes}, volume = {69}, year = {2021}, pages = {273-289}, abstract = {Monitoring the ratio of two normal\ random variables\ plays an important role in several manufacturing environments. In addition, the traditional control charts that have been developed for infinite production horizons can not function effectively to detect anomalies in short production runs. In this paper, we tackle this problem by proposing two one-sided Shewhart-type charts to monitor the ratio of two normal random variables for a finite horizon production. The statistical performance of the proposed charts is investigated using the truncated average run length as a\ performance measure\ in short production runs. In order to help the quality practitioner to implement these control charts, we have provided ready-to-use tables of the control limit parameters. An illustrative example from the food industry is given for illustration.}, url = {https://www.sciencedirect.com/science/article/pii/S1526612521005223}, author = {Kim DucTran and Qurat-Ul-Ain Khaliq and Adel Ahmadi Nadi and Thi Hien Nguyen and Kim Phuc Tran} } @article {31720, title = {A modified method on estimating and assessing the process yield with imprecise multiple characteristics}, journal = {Iranian Journal of Fuzzy Systems}, volume = {17}, year = {2020}, pages = {115-131}, abstract = {The conventional advanced process yield index STpk is widely applied in industry to provide an exact measure of the overall production yield whose quality characteristics are mutually independent and multivariate normally distributed. While one can find numerous studies that consider a crisp estimation of\ STpk\ to evaluate and test the overall process yield, the recorded measurements of product quality characteristics are not always reported precisely. This paper presents a new fuzzy-based method to assess the overall process yield in the presence of a specified degree of ambiguity for the sample data. After finding a fuzzy estimator of\ STpk based on Buckley{\textquoteright}s approach, a new fuzzy three-decision testing rule is proposed to evaluate process performance based on critical values and fuzzy p-values. Subsequently, this work extends the application of the proposed method to the class of correlated characteristics by adopting the principal component analysis technique. The introduced fuzzy testing procedure includes the existing customary binary-decision testing rule as a spacial case. In addition, comparative studies are conducted to display the benefits of the proposed rule. Finally, two industrial examples are given for independent and correlated characteristics to guide the practitioners.}, author = {Robab Afshari and Bahram Sadeghpour Gildeh and Adel Ahmadi Nadi} } @article {31722, title = {Optimal design of overall-yield-based variable repetitive sampling plans for process with multiple characteristics}, journal = {Applied Mathematical Modelling}, volume = {81}, year = {2020}, pages = {194-210}, abstract = {In this study, we developed two repetitive types of sampling plans for processes with multiple quality characteristics based on the overall yield index\ STpk. These plans can be implemented for mutually independent and normally distributed characteristics. The plans are optimally designed based on the asymptotic sampling distribution of\ STpk\ using an efficient\ nonlinear optimization\ algorithm. During the solution of optimization problems, the average sample number required for inspection and the contract requirements are treated as an objective function and constraints, respectively. The optimal parameters were determined for use in industrial environments with various combinations of requirements in tables. A simulation study was also conducted to show that the tabulated parameters based on the results obtained by large sample theory can guarantee the specified risks for finite sample sizes. Moreover, the limitations of the proposed plans with respect to the sample size were analyzed based on extensive simulations. Numerical calculations and\ graphical illustrations\ are presented to demonstrate the\ properties\ of the proposed plans. In addition, the advantages of the schemes are discussed compared with existing plans. Finally, the efficient plan is applied to two real industrial problems.}, url = {https://www.sciencedirect.com/science/article/pii/S0307904X1930719X}, author = {Adel Ahmadi Nadi and Bahram Sadeghpour Gildeh and Robab Afshari} } @article {31721, title = {Weighted multimodal family of distributions with sine and cosine weight functions}, journal = {Heliyon}, year = {2020}, pages = {8}, abstract = {In this paper, the moment of various types of sine and cosine functions are derived for any random variable. For an arbitrary even probability density function, the sine and cosine moments are used to define new families of univariate multimodal probability density and their corresponding characteristic functions. For illustration, two weighted multimodal generalizations of the\ t\ distribution are investigated. Furthermore, a method of calculating some interesting improper integrals is also presented. Finally, an explicit expression of the probability density function of the sum of independent\ t-distributed random variables with odd degrees of freedom is derived.}, author = {Ayman Alzaatreh and Jaber Kazempoor and Adel Ahmadi Nadi} } @article {31726, title = {Fuzzy Double Variable Sampling Plan under Uncertainty}, journal = {Journal of Quality Engineering and Production Optimization}, volume = {4}, year = {2019}, pages = {83-98}, abstract = {Double sampling plan is an examination with a certain parameter, so it cannot decide about manufactured products whose portion parameter is not certain. The main goal of this survey is to introduce double variable plan when \ is indefinite to examine manufacturing products when concerned characteristics are normally distributed. Plan parameters are achieved by an optimization manner. Sum of fuzzy customer and producer{\textquoteright}s risks and contract{\textquoteright}s commitments are assumed as a goal function and restrictions, respectively, in this manner. Optimum values of parameters are provided to be employed in industry for variant compositions of demands. A simulation study is also conducted to represent that the presented approach becomes traditional one as \ is not imprecise. In addition, conclusions display that the proposed method is more economical than the existing scheme. At the end, an industrial example is given in real situations.}, url = {http://jqepo.shahed.ac.ir/article_1119_0.html}, author = {Robab Afshari and Bahram Sadeghpour Gildeh and Adel Ahmadi Nadi} } @article {31724, title = {A group multiple dependent state sampling plan using truncated life test for the Weibull distribution}, journal = {Quality Engineering}, volume = {31}, year = {2019}, pages = {553-563}, abstract = {Group and conditional sampling methods have been recently developed to apply in industrial environments. Based on the combination of two group and conditional schemes, this article introduces a group multiple dependent state sampling plan for a truncated life test when the lifetime of item follows the Weibull distribution. The proposed plan can be applied when the quality history of process is accessible and a multiple number of items are installed as a group in each tester. The proposed plan has merits which are illustrated via a comparative study over the existing group acceptance sampling plan. Furthermore, a real example is provided.}, url = {https://www.tandfonline.com/doi/full/10.1080/08982112.2018.1558250}, author = {Adel Ahmadi Nadi and Bahram Sadeghpour Gildeh} } @article {31725, title = {Estimating the lifetime performance index of products for two-parameter exponential distribution with the progressive first-failure censored sample}, journal = {International Journal for Quality Research}, volume = {10}, year = {2016}, pages = {389-406}, abstract = {In practice, Process capability indices such as lifetime performance index CL indicate the relationships between the actual process performance and the manufacturing specifications, where L is the lower specification limit and it is known. Progressive first-failure censoring scheme is quite useful in many practical situations where lifetime of a product is quite high and test facilities are scarce but test material is relatively cheap. This study, under the assumption of two-parameter exponential distribution and by applying data transformation constructs a uniformly minimum variance unbiased estimator (UMVUE) of CL based on a progressive first-failure censored sample. Then the UMVUE of CL is utilized to develop the new hypothesis testing procedure. Finally, two illustrative examples are given to assess the behavior of this test statistic for testing null hypothesis under given significance level.}, url = {http://www.ijqr.net/journal/v10-n2/10.pdf}, author = {Adel Ahmadi Nadi and Bahram Sadeghpour Gildeh} }