How freezing and thawing processes affect black-soil aggregate stability in northeastern China

Laboratory experiments were carried out to investigate the effect of freezing and thawing processes on wet aggregate stability （WAS） of black soil. Wet aggregate stability was determined by different aggregate size groups, different water contents, various freeze-thaw cycles, and various freezing temperatures. The results showed that, when at suitable water content, aggregate stability was enhanced, aggregate sta-bility will be disrupted when moisture content is too high or too low, especially higher water content. Temperature also had a significant ef-fect, but moisture content determined the suitable freezing temperatures for a given soil. Water-stable aggregate （WSA〉0.5）, the total aggre-gate content, and mean weight diameter decreasing with the freeze-thaw cycles increase, reached to 5 percent significance level. The reason for crumbing aggregates is the water and air conflict, thus raising the hypothesis that water content affects the aggregate stability in the process of freezing and thawing.

RATE OF CONVERGENCE FOR MULTIPLE CHANGEPOINTS ESTIMATION OF MOVING-AVERAGE PROCESSES

In this paper, the least square estimator in the problem of multiple change points estimation is studied. Here, the moving-average processes of ALNQD sequence in the mean shifts are discussed. When the number of change points is known, the rate of convergence of change-points estimation is derived. The result is also true for p-mixing, φ-mixing, a-mixing, associated and negatively associated sequences under suitable conditions.

Some Group Runs Based Multivariate Control Charts for Monitoring the Process Mean Vector

In this article, we propose two control charts namely, the “Multivariate Group Runs’ (MV-GR-M)” and the “Multivariate Modified Group Runs’ (MV-MGR-M)” control charts, based on the multivariate normal processes, for monitoring the process mean vector. Methods to obtain the design parameters and operations of these control charts are discussed. Performances of the proposed charts are compared with some existing control charts. It is verified that, the proposed charts give a significant reduction in the out-of-control “Average Time to Signal” (ATS) in the zero state, as well in the steady state compared to the Hotelling’s T2 and the synthetic T2 control charts.

A MARKOVIAN APPROACH TO DETERMINING PROCESS MEANS WITH DUAL QUALITY CHARACTERISTICS

This paper studies a production system where products are produced continuously and whose specification limits are specified for screening inspection. In this paper, we consider dual quality characteristics and different costs associated with each quality characteristic that falls below a lower specification limit or above an upper specification limit. Due to these different costs, the expected total profit will greatly depend on the process parameters, especially a process mean. This paper develops a Markovian-based model for determining the optimum process means with the consideration of dual quality characteristics in a single-stage system. The proposed model is then illustrated through a numerical example and sensitivity analysis is performed to validate the model. The results showed that the optimum process mean for both quality characteristics have a significant effect on the performance of the system. Since the literature survey shows that dealing with multi-quality characteristics is extremely limited, the proposed model, coupled with the Markovian approach, provides a unique contribution to this field.

Simultaneous determination of manufacturer’s process mean and production run length,and retailer’s order quantity

In Chen and Liu’s optimum profit model with a traditional production system,they did not consider the effect of product quality on the customer’s demand order quantity,and also ignored the used cost of customers for product.In fact,the customer’s demand quantity is always seriously related to product quality.Hence,in the present paper,we modify Chen and Liu’s model to address the determination of the optimal process parameters by employing the idea of quality loss and single sampling rectifying inspection plan.Assuming that the quality characteristic of the product is normally distributed,Taguchi’s symmetric quadratic quality loss function is applied in evaluating the product quality.Three decision variables,i.e.,the mean of the process characteristic,the production run length of the product and the retailer’s order quantity,are jointly determined in our modified model to maximize the expected total profit of society,which includes both the manufacturer and the retailer.A heuristic solution procedure is developed for this optimization problem,and a numerical example is provided for illustration.From the numerical results,it can be seen that both the sale price per unit and the intercept of the mean demand of the customer are two major(or significant)parameters in the model and should be more accurately estimated in practice.Finally,the quality investment policy is provided to compare its effect on the optimum profit model with quality improvement.