References of "Faraz, Alireza"      in Complete repository Arts & humanities   Archaeology   Art & art history   Classical & oriental studies   History   Languages & linguistics   Literature   Performing arts   Philosophy & ethics   Religion & theology   Multidisciplinary, general & others Business & economic sciences   Accounting & auditing   Production, distribution & supply chain management   Finance   General management & organizational theory   Human resources management   Management information systems   Marketing   Strategy & innovation   Quantitative methods in economics & management   General economics & history of economic thought   International economics   Macroeconomics & monetary economics   Microeconomics   Economic systems & public economics   Social economics   Special economic topics (health, labor, transportation…)   Multidisciplinary, general & others Engineering, computing & technology   Aerospace & aeronautics engineering   Architecture   Chemical engineering   Civil engineering   Computer science   Electrical & electronics engineering   Energy   Geological, petroleum & mining engineering   Materials science & engineering   Mechanical engineering   Multidisciplinary, general & others Human health sciences   Alternative medicine   Anesthesia & intensive care   Cardiovascular & respiratory systems   Dentistry & oral medicine   Dermatology   Endocrinology, metabolism & nutrition   Forensic medicine   Gastroenterology & hepatology   General & internal medicine   Geriatrics   Hematology   Immunology & infectious disease   Laboratory medicine & medical technology   Neurology   Oncology   Ophthalmology   Orthopedics, rehabilitation & sports medicine   Otolaryngology   Pediatrics   Pharmacy, pharmacology & toxicology   Psychiatry   Public health, health care sciences & services   Radiology, nuclear medicine & imaging   Reproductive medicine (gynecology, andrology, obstetrics)   Rheumatology   Surgery   Urology & nephrology   Multidisciplinary, general & others Law, criminology & political science   Civil law   Criminal law & procedure   Criminology   Economic & commercial law   European & international law   Judicial law   Metalaw, Roman law, history of law & comparative law   Political science, public administration & international relations   Public law   Social law   Tax law   Multidisciplinary, general & others Life sciences   Agriculture & agronomy   Anatomy (cytology, histology, embryology...) & physiology   Animal production & animal husbandry   Aquatic sciences & oceanology   Biochemistry, biophysics & molecular biology   Biotechnology   Entomology & pest control   Environmental sciences & ecology   Food science   Genetics & genetic processes   Microbiology   Phytobiology (plant sciences, forestry, mycology...)   Veterinary medicine & animal health   Zoology   Multidisciplinary, general & others Physical, chemical, mathematical & earth Sciences   Chemistry   Earth sciences & physical geography   Mathematics   Physics   Space science, astronomy & astrophysics   Multidisciplinary, general & others Social & behavioral sciences, psychology   Animal psychology, ethology & psychobiology   Anthropology   Communication & mass media   Education & instruction   Human geography & demography   Library & information sciences   Neurosciences & behavior   Regional & inter-regional studies   Social work & social policy   Sociology & social sciences   Social, industrial & organizational psychology   Theoretical & cognitive psychology   Treatment & clinical psychology   Multidisciplinary, general & others     Showing results 1 to 20 of 54 1 2 3     The np- Control Charts with the Guaranteed In-Control PerformanceFaraz, Alireza ; Heuchenne, Cédric E-print/Working paper (2016)In this paper, we evaluate the in-control performance of np-control charts with estimated parameters. We then apply the bootstrap method to adjust the control charts’ limits to guarantee the desired in ... [more ▼]In this paper, we evaluate the in-control performance of np-control charts with estimated parameters. We then apply the bootstrap method to adjust the control charts’ limits to guarantee the desired in-control average run length (ARL0) value in monitoring stage. The adjusted limits ensure that ARL0 would take a value greater than the desired value (say, B) with a certain specified probability, that is Pr⁡(ARL_0>B)=1-ρ. We finally provide users with tables which with practitioners do not need to do bootstrapping Phase I data set to obtain the control limit thresholds. [less ▲]Detailed reference viewed: 111 (1 ULg) Statistically Bundled Shewhart Control Charts for Monitoring Delivery Chains SystemsFoster, Earnest; Faraz, Alireza ; Heuchenne, Cédric in European Journal of Industrial Engineering (2016)Continuous monitoring of Delivery Time variables by means of control charts in a delivery chain is a very recent application of Statistical Process Control (SPC) to the service sector. The aim of the ... [more ▼]Continuous monitoring of Delivery Time variables by means of control charts in a delivery chain is a very recent application of Statistical Process Control (SPC) to the service sector. The aim of the proposed method is to provide supply chain decision makers with an easy to be managed tool monitoring the current functioning state of the delivery chain. The implementation of SPC control charts makes it possible to limit over-corrections to false alarm conditions and to maintain at an acceptable level the safety stock, with a consequent reduction of the overall management costs of the delivery chain. An illustrative example shows the proposed control chart implementation in a real delivery chain. [less ▲]Detailed reference viewed: 120 (2 ULg) Monitoring partnership networks- A graph theory approachFaraz, Alireza ; Treiblmaier, Horst; Gerschberger, MarkusConference (2016, June 17)Recently, companies are forming strong relationships with their strategic suppliers and customers in order to maximize their profit in the global market. Such a partnership or strategic alliance is based ... [more ▼]Recently, companies are forming strong relationships with their strategic suppliers and customers in order to maximize their profit in the global market. Such a partnership or strategic alliance is based on the mutual needs of both parties. A partnership network is formed by different strategic firms (e.g., suppliers, manufacturers, distributors, retailers) who intend to establish strong relationships together but without losing their ownership, power and control on the firm. For example, if supplier X has a strong relationship with customer Y and Y has a strong relationship with supplier Z, then X, Y and Z can form a partnership network with three nodes (X, Y and Z) and two edges (X ->Y and Z->Y). In this paper, we develop a statistical methods to study the normal behaviour of partnership networks. We furthermore develop a methodology that will help diagnose the nature of identified unusual network behavior. [less ▲]Detailed reference viewed: 78 (3 ULg) An Exact Method for Designing Shewhart X ̅ and S2 Control Charts to Guarantee the In-Control PerformanceFaraz, Alireza ; Heuchenne, Cédric in Journal of Quality Technology (2016)The in-control performance of the Shewhart X ̅ and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate an unrealistically large amount of ... [more ▼]The in-control performance of the Shewhart X ̅ and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate an unrealistically large amount of Phase I data is needed to have the desired in-control average run length (ARL) value in Phase II. To overcome this problem, it has been recommended that the control limits be adjusted based on a bootstrap method to guarantee that the in-control ARL is at least a specified value with a certain specified probability. In our paper we present simple formulas for the required control limits so that practitioners do not have to use the bootstrap method. An assumption of normality is required. The advantage of our proposed method is in its simplicity; there is no bootstrapping and the control chart constants do not depend on the Phase I sample data. [less ▲]Detailed reference viewed: 142 (2 ULg) A Statistically adaptive sampling policy to the Hotelling's T2 Control Chart: Markov Chain ApproachSeif, A.; Faraz, Alireza ; Heuchenne, Cédric et alin Communications in Statistics : Theory & Methods (2016)Detailed reference viewed: 51 (7 ULg) The Robust Economic Statistical Design of the Hotelling’s T^2 ChartFaraz, Alireza ; Chalaki, Kamyar; Saniga, Erwin et alin Communications in Statistics : Theory & Methods (2016)Economic statistical designs aim at minimizing the cost of process monitoring when a specific scenario or a set of estimated process and cost parameters is given. However, in practical situations the ... [more ▼]Economic statistical designs aim at minimizing the cost of process monitoring when a specific scenario or a set of estimated process and cost parameters is given. However, in practical situations the process may be affected by more than one scenario which may lead to severe cost penalties for upsetting the true scenario. This paper presents the robust economic statistical design (RESD) of the T^2 chart to reduce the monetary losses when there are multiple distinct scenarios. The genetic algorithm optimization method is employed here to minimize the total expected monitoring cost across all distinct scenarios. Through two numerical examples the proposed method is illustrated. Simulation studies indicate that the robust economic statistical designs should be encouraged in practice. [less ▲]Detailed reference viewed: 92 (3 ULg) Nonparametric control charts: economic statistical designMarcos Alvarez, Alejandro ; Heuchenne, Cédric ; Faraz, Alireza E-print/Working paper (2016)This paper studies economic statistical designs (ESD) for nonparametric control charts based on the sign and Wilcoxon tests. The main advantage of the procedures is that, except for the tested location ... [more ▼]This paper studies economic statistical designs (ESD) for nonparametric control charts based on the sign and Wilcoxon tests. The main advantage of the procedures is that, except for the tested location parameter, they do not use either any parametric distribution for the quality characteristic or any information about the possible involved parameters, neither in the in-control nor in the out-of-control state. This is made possible by minimizing a cost function specified independently of these quantities. Unlike the ESD for the $\overline{x}$ chart, the resulting charts designs are robust to changes of the distributions of the observations (in control or out of control), provide reliable statistical guarantees when the $\overline{x}$ chart ESD does not and stay competitive even when the strong assumptions of the $\overline{x}$ chart ESD are fully satisfied. These new techniques can therefore be applied to a definitely wider class of problems and their designs may stay constant over time without losing performance. [less ▲]Detailed reference viewed: 83 (3 ULg) Monitoring The quality Loss Performance of ProductsFaraz, Alireza ; Treiblmaier, HorstConference (2015, November 03)This paper presents a control chart based on the Taguchi (1986)’s loss function for monitoring the performance of a process and its capability in monetary form. The proposed chart monitors the loss due to ... [more ▼]This paper presents a control chart based on the Taguchi (1986)’s loss function for monitoring the performance of a process and its capability in monetary form. The proposed chart monitors the loss due to poor quality to the society. The proposed control chart also allows for simultaneously monitoring both changes of the mean and variance. [less ▲]Detailed reference viewed: 23 (0 ULg) Shewhart Control Charts with Guaranteed In-Control PerformanceFaraz, Alireza ; Heuchenne, Cédric ; Woodall, W.H.Conference (2015, July 08)The in-control performance of the Shewhart X ̅ and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate an unrealistically large amount of ... [more ▼]The in-control performance of the Shewhart X ̅ and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate an unrealistically large amount of Phase I data is needed to have the desired in-control average run length (ARL) value in Phase II. To overcome this problem, it has been recommended that the control limits be adjusted based on a bootstrap method to guarantee that the in-control ARL is at least a specified value with a certain specified probability. In our paper we present simple formulas for the required control limits so that practitioners do not have to use the bootstrap method. An assumption of normality is required. The advantage of our proposed method is in its simplicity; there is no bootstrapping and the control chart constants do not depend on the Phase I sample data. [less ▲]Detailed reference viewed: 57 (2 ULg) Monitoring supply chains with multivariate control charts: an economic-statistical design approachHeuchenne, Cédric ; Faraz, Alireza ; Saniga, ErwinScientific conference (2015, June 02)Detailed reference viewed: 29 (1 ULg) Evaluation of the Economic Statistical Design of the Multivariate T2 Control Chart with Multiple Variable Sampling Intervals Scheme: NSGA-II ApproachFaraz, Alireza ; Seif, Asghar; Sadeghifarin Journal of Statistical Computation & Simulation (2015), 85(12), 2442-2455The economic and statistical merits of a multiple variable sampling intervals (MVSI) scheme are studied. The problem is formulated as a double-objective optimization problem with the adjusted average time ... [more ▼]The economic and statistical merits of a multiple variable sampling intervals (MVSI) scheme are studied. The problem is formulated as a double-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the economic objective. Bai and Lee’s ‎[2] economic model is considered. Then we find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the non-dominated sorting genetic algorithm. Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, which indicate the advantage of flexibility and adaptability of our approach. [less ▲]Detailed reference viewed: 52 (4 ULg) Characteristics of Economically Designed CUSUM and \bar{X} Control ChartsSaniga, Erwin; Davis, Darwin; Faraz, Alireza et alin Knoth, Sven; Schmid, Wolfgang (Eds.) Frontiers in Statistical Quality Control 11 (2015)In this paper we investigate the characteristics of economic control chart designs for both Shewhart (¯X ) and CUSUM control charts. Authors in the past have made some suggestions regarding the design of ... [more ▼]In this paper we investigate the characteristics of economic control chart designs for both Shewhart (¯X ) and CUSUM control charts. Authors in the past have made some suggestions regarding the design of these charts, where design is defined as finding the values of sample size, intersample interval and control limit (Shewhart chart) or control parameters (k and h) for the CUSUM chart. Here, we run a large number of experiments consisting of many configurations of the parameters and describe and model the results in terms of the actual economic designs. [less ▲]Detailed reference viewed: 19 (3 ULg) Guaranteed Conditional Performance of the S2 Control Chart with Estimated ParametersFaraz, Alireza ; Heuchenne, Cédric ; Woodall, Williamin International Journal of Production Research (2015)We evaluate the in-control performance of the S2 control chart with estimated parameters conditional on the Phase I sample. Simulation results indicate no realistic amount of Phase I data is enough to ... [more ▼]We evaluate the in-control performance of the S2 control chart with estimated parameters conditional on the Phase I sample. Simulation results indicate no realistic amount of Phase I data is enough to have confidence that the in-control average run length (ARL) obtained will be near the desired value. To overcome this problem, we adjust the S2 chart controls limits such that the in-control ARL is guaranteed to be above a specified value with a certain specified probability. The required adjustment does not have too much of an effect on the out-of-control performance of the chart. [less ▲]Detailed reference viewed: 111 (5 ULg) Shewhart Control Charts for Monitoring Reliability with Weibull LifetimesFaraz, Alireza ; Saniga, Erwin; Heuchenne, Cédric in Quality and Reliability Engineering International (2015), 31In this paper, we present Shewhart type Z ̅ and S2 control charts for monitoring individual or joint shifts in the scale and shape parameters of a Weibull distributed process. The advantage of this method ... [more ▼]In this paper, we present Shewhart type Z ̅ and S2 control charts for monitoring individual or joint shifts in the scale and shape parameters of a Weibull distributed process. The advantage of this method is its ease of use and flexibility for the case where the process distribution is Weibull, although the method can be applied to any distribution. We illustrate the performance of our method through simulation and the application through the use of an actual data set. Our results indicate that Z ̅ and S2 control charts perform well in detecting shifts in the scale and shape parameters. We also provide a guide that would enable a user to interpret out-of-control signals. [less ▲]Detailed reference viewed: 99 (2 ULg) Control Charts monitoring product’s loss to societyCelano, Giovanni; Faraz, Alireza ; Saniga, Erwinin Quality and Reliability Engineering International (2014), 30(8), 1393-1407Taguchi introduced a new philosophy in quality control that accounts for the economic loss associated to process variation measured by deviations from the target value of a product quality characteristic ... [more ▼]Taguchi introduced a new philosophy in quality control that accounts for the economic loss associated to process variation measured by deviations from the target value of a product quality characteristic. The Taguchi loss function has been considered in the design of control charts only for the computation of costs associated with nonconformities. This paper considers sample statistics based on the Taguchi loss function as a means to implement Shewhart control charts monitoring both the deviation from the target and dispersion of normally distributed quality characteristics. The aim of this proposed control chart is to perform on-line quality control of a process by monitoring its quality loss cost performance over time. To compute the quality loss performance, we consider a nominal-the-best quality characteristic. The statistical performance of the proposed control charts has been evaluated and compared with that of widely used control charts. Implementing target costing philosophy by means of one of the proposed charts is also discussed. An example illustrates the Taguchi control chart in a practical implementation. [less ▲]Detailed reference viewed: 90 (25 ULg) Statistical performance of a control chart monitoring the ratio of two normal variablesCelano, Giovanni; CASTAGLIOLA, Philippe; Faraz, Alireza et alin Quality and Reliability Engineering International (2014), 30(8), 1361-1377On-line Statistical Process Control (SPC) monitoring the ratio Z of two normal variables X and Y has surprisingly received too little attention in the quality control literature. Several potential ... [more ▼]On-line Statistical Process Control (SPC) monitoring the ratio Z of two normal variables X and Y has surprisingly received too little attention in the quality control literature. Several potential applications dealing with monitoring the ratio Z can be found in the industrial sector, when quality control of products consisting of several raw materials calls for monitoring the stability of the proportions (ratios) of different components within a product. Tables about the sensitivity of these charts in the detection of one or more assignable causes are still not available. This paper investigates the statistical performance of Phase II Shewhart control charts monitoring the ratio of two normal variables in the case of individual observations. The obtained results show that the performance of the proposed charts is a function of the distribution parameters of the two normal variables. In particular, the Shewhart chart monitoring the ratio Z outperforms the (p=2) multivariate  control chart when a process shift affects the in-control mean of X or, alternatively, of Y and the correlation among X and Y is high and when the in-control means of X and Y shift contemporarily to opposite directions. The sensitivity of the proposed chart to a shift of the in-control dispersion has been investigated, too. We also show that the standardization of the two variables before computing their ratio is not a good practice due to a significant loss in the chart’s statistical sensitivity. An illustrative example from the food industry is detailed to show the implementation of these control charts. [less ▲]Detailed reference viewed: 104 (18 ULg) Economic Statistical Design of the VP( X) ̅ Control Charts for Monitoring a Process under Non-normalitySeif, Asghar; Faraz, Alireza ; Saniga, Erwinin International Journal of Production Research (2014), 53(14), 4218-4230Recent studies proved that variable parameters (VP) X ̅ control charts not only detects process mean shifts quicker than the classical X ̅ control chart but also has better economic properties ... [more ▼]Recent studies proved that variable parameters (VP) X ̅ control charts not only detects process mean shifts quicker than the classical X ̅ control chart but also has better economic properties. Furthermore, like most papers in control chart design, the fundamental assumption is that process data are normally distributed. Nevertheless, process quality variables may not be normal in application. In this paper, we investigate the economic statistical design of the VP X ̅ control chart when the underlying process distribution is non-normal. We illustrate the design procedure and perform a sensitivity analysis on the process and cost parameters based upon the degrees of skewness and kurtosis of the population using an industrial application. [less ▲]Detailed reference viewed: 72 (12 ULg) The application of the NSGA-II optimization method in designing control chartsFaraz, Alireza ; Heuchenne, Cédric ; Seif, AsgharConference (2014, June 04)The problem of designing control chart is formulated as a multi-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the ... [more ▼]The problem of designing control chart is formulated as a multi-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the economic objective. Then we try to find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the elitist non-dominated sorting genetic algorithm method. Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, thereby bolding the advantage of flexibility and adaptability. [less ▲]Detailed reference viewed: 36 (3 ULg) The variable parameters T2 chart with run rulesFaraz, Alireza ; Celano, Giovanni; Heuchenne, Cédric et alin Statistical Papers (2014), 55(4), 933-950The Hotelling’s T2 control chart with variable parameters (VP T2) has been shown to have better statistical performance than other adaptive control schemes in detecting small to moderate process mean ... [more ▼]The Hotelling’s T2 control chart with variable parameters (VP T2) has been shown to have better statistical performance than other adaptive control schemes in detecting small to moderate process mean shifts. In this paper, we investigate the statistical performance of the VP T2 control chart coupled with run rules. We consider two well-known run rules schemes. Statistical performance is evaluated by using a Markov chain modeling the random shock mechanism of the monitored process. The in-control time interval of the process is assumed to follow an exponential distribution. A Genetic Algorithm has been designed to select the optimal chart design parameters. We provide an extensive numerical analysis indicating that the VP T2 control chart with run rules outperforms other charts for small sizes of the mean shift expressed through the Mahalanobis distance. [less ▲]Detailed reference viewed: 148 (14 ULg) Monitoring Delivery Networks in supply chainsFaraz, Alireza Conference (2014, March 14)Detailed reference viewed: 11 (0 ULg) 1 2 3