Journal of Quality Engineering and Management

Abstract Control charts are widely used to identify changes in the production process, and when it comes to identifying small changes in the process, non-Shewhart control charts such as exponential weighted moving average (EWMA) and generalized weighted moving average (GWMA) are better alternatives to control charts than Shewhart ¯X control chart. In this context, nonparametric control charts are used when the distribution of quality characteristic of the process is unknown, in which the Sign control chart is one of the most popular nonparametric control charts. In this paper, for the first time, a generalized weighted moving average sign control chart using a ranked set sampling (RSS) design is introduced. The performance of the proposed control chart is evaluated using simulated data according to the average run length evaluation criterion, and simulation studies showed that the GWMA sign control chart under the RSS design is better at detecting small process changes than the EWMA sign control chart under the RSS design.

Abstract Health index is a tool to evaluate the functional condition of an equipment with the aim of improving its operational performance. In this research, the types of models available in the field of asset health index estimation along with their challenges and limitations were examined, based on a developed model. The proposed model was implemented in five different types of wind tunnel equipment fans, due to their significant maintenance and repair costs. The model proposed in this research in order to estimate the health index includes steps such as: 1) selecting the equipment and defining its class, 2) evaluating the effect of loading factors and location, 3) calculating the aging rate, 4) achieving the initial health index at age t and 5) evaluation of load effect, modifiers of health index and reliability, and calculation of current health index. Examining the values obtained from the fan health index, in the form of a graphic design, showed that it is possible to determine the speed of failure rate and the functional life of the equipment. The results of this research can be used in choosing the appropriate strategy for maintenance and repairs with the aim of improving the operational performance of other equipment.

Abstract In this article, three monitoring approaches using cumulative sum (CUSUM) control charts in phase two for zero inflated poisson-based processes are presented. The first approach is based on the zero inflated poisson distribution, the second on, a proportional hazard regression model, and the third integrates a proportional hazard (PH) regression model and a frailty model to consider both measurable and unmeasurable covariates. The performance of all three control charts was evaluated separately and simultaneously by applying shifts to both parameters of the zero inflated poisson distribution. Extensive simulation studies were conducted to evaluate the performance of these monitoring methods in terms of the average run length (ARL) of the control charts. The proposed cumulative sum control chart with simultaneous consideration of measurable and unmeasurable variables showed superior performance. Finally, a real case study in a label printing factory has been provided to show the effectiveness of the proposed control chart.

Abstract Compressive strength is one of the important properties of concrete, which is affected by factors such as humidity, water-cement ratio, cement composition, aggregate dimensions, and age of concrete. All cases except age can be controlled by making changes in the mixing plan, therefore, in this research, the relationship between age and compressive strength of concrete has been investigated using profile analysis in a 6-story building construction project by concrete quality control experts. In this research, 10 concrete samples were processed in laboratory conditions after preparation, and the compressive strength of the samples was checked by 3 experts and each expert checked each sample 3 times. In the zero phase, with the Gage study method, the data is not affected by the measurement error. In phase one, by using the Storr and Braille control chart, out-of-control profiles have been removed, and a model has been presented to estimate the compressive strength of concrete according to the age of the sample. In the second phase, using 10,000 data simulated by MATLAB software, the performance of the model has been examined using the (EWMA) chart, the results show that the EWMA chart is able to identify out-of-control signals by applying changes in the model parameters An out-of-control signal can be a warning for signs such as cracking, cracking, sanding, and discoloration at older ages of concrete. Therefore, managers and concrete quality control experts can predict the factors of concrete destruction and take measures to restore concrete without spending a lot of money.

Abstract Knowing the real costs of a project, correctly estimating them and identifying the risks involved in resource allocation for projects such as the construction of a petrochemical unit whose resources are expensive or difficult to access, is of particular importance. By using costing methods in conditions of risk and uncertainty, more reliable cost information can be obtained. By examining past studies and researches in the field of costing, it was found that their focus was mostly on carrying out activities, and less attention was paid to the risk factor. In this article, the use of the ABC approach, which focuses on identifying activities and cost centers, has been discussed in the form of a mathematical model whose purpose is to minimize the risk of resource allocation to activity centers based on the desired limitations in costs and resources. Due to the fact that the numerical values of the parameters in the general model, such as cost and time, have uncertainty, risk-based resource allocation modeling has been considered. To test the proposed model, the main activities of the construction and installation stage of a petrochemical unit were considered, and after collecting the necessary data, the steps of the compiled model for resource allocation and the steps of the activity-based costing approach have been implemented. The results show that there is a difference between the costs calculated based on the allocation of resources of the proposed model for the activity centers and the costs estimated according to the past data.

Abstract In time series analysis, ignoring outliers leads to misidentification of the model, biased estimation of parameters, and poor predictions. One of the reliable non-parametric methods in predicting and improving the quality of multivariate time series modeling is the multivariate Singular Spectrum Analysis (MSSA) technique, which does not require any initial assumptions. The presence of outliers affects the Frobenius norm of matrix and reduces the efficiency of the MSSA method. In this research, a new version of MSSA based on the L₁- norm is proposed. Then the performance of this method is compared with basic MSSA using simulation studies and real data.