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In this paper, the same distribution principle is developed based on the studies with many years for short run processes. The quality control philosophy and background of the principle are introduced. Some implementing techniques for the principle are presented, and application cases both in industry and evaluation & decision‐making areas are shown.

With the development of the American Customer satisfaction index (ACSI), research on customer satisfaction measurement or evaluation methods have become significant in the last decade. Most of international customer satisfaction barometers or indices are evolved based on the cause and effect relationship model of ACSI. Of critical importance to validity of customer satisfaction indices is how to construct a measurement attribute or indicator model and provide an effective implementation method effectively. Quality Funcion Deployment (QFD) is a very useful tool for translating the customer voice into product design through quality engineering. In fact, this is a methodology for measuring and analyzing evaluation indicators by their relationship matrix. In this paper, we will make an effort to integrate the framework of QFD into teh measurement problem of customer satisfaction, and also develop a new multi‐phase QFD model for evaluation of Customer Satisfaction Index (CSI). From the houses of quality in this model, the evaluation indicators impacting on customer’s global satisfaction are identified by means of their relationship matrix. Then the evaluation indicator hierarchy and its measurement method for the customer satisfaction index are presented graphically. Furthermore, survey data from the Chinese autombobile maintenance sector and a relevant case study are utilized to show the implementation method of the QFD model used to measure and analyze of customer satisfaction.

As we know, the quality of processes is technically depicted by variation, a product or process with the best quality must naturally require the variation as less as possible. The variation is usually reduced with many ways, say, by adjusting parameters settings under robust design with many turns expensive experiements. So ones are trying to reach the robusiness by detecting cheap and simple methods. In this paper, a both practical and simple technique for quality improvement, namely reducing the variation, by data classification is studied. First, all possible system factors are included, which may dominate the variation law. And then we make use of the past observations and their classification as well as boxplot charts to find out the internal rule between the variation and the system factor. Next, adjust the location of the system factor according to the rule so that the variation could, to some extent, be lessened. Finally, two typical quality improvement cases based on data classification are presented.

Multivariate Exponentially Weighted Moving Average (MEWMA) chart is a control chart under multivariate process based on the idea of EWMA that rapidly detects small dispersion with a trend. the MEWMA chart was first time discussed by Woodall. However, in his study the correlativity among the multivariate was not considered for the selection of the constant of the diagonal matrix (the smooth parameter λ). In this paper, the EWMA chart with a generalized smooth parameter matrix has been discussed which is believed to have a better fitness for practical production processes than Woodall’s approach.

As a sign of international quality system, ISO9000 certification has been adopted by more and more enterprises. In recent five years, there have been 560,000 certified companies in Europe and America, and there have been more than 390,000 ones in China. It has being attracted many quality scholars’ attentions whether ISO9000 certification can bring more benefits to certified companies or not. This paper investigates the ISO9000 certification effect on market performance by the samples from Chinese list companies in shanghai stock exchange. Considering ISO9000 certification as an event, a certification effect model will be set up by means of the event study method, which takes abnormal return rate as a basic indicator to measure the ISO9000 certification effect on Chinese market performance in different event times. Investigation results show that the Chinese certified companies have some positive effects on market performance in the short term. From a long standpoint, the relation between certification and performance has a positive trend.

How to measure Quality Performance (QP) or excellence performance in organizations is very important for improving the quality of an organization’s products and services. This paper takes Quality Function Deployment (QFD) as a ueful tool to identify the key characteristics of quality performance and measure the influence factors on quality performance. Most national quality awards provide a framework of the criteria to show the essential elements of an organization’s quality performance and get the Quality Performance Score (QPS) by self‐assessment using the criteria. By means of these criteria, especially, the criteria of China Quality Award (CQA), a measurable indicator system for quality performance is set up. A four‐phase QFD model of assessment for quality performance is developed. This QFD model not only presents the most important efforts for the deployment of the measurable indicators of quality performance, but also takes great advantage of evaluating the quality performance and obtaining the quality performance score. The measurable indicator hierarchy of quality performance is formed and its implementation method for assessment quality performance is described in this paper.

A COQ model plays an important role in the total quality cost survey. Based on the methodology of continuous quality improvement, a dynamic COQ model for different quality level is developed in this paper. A quality level is defined by Six Sigma level that can be measured by two indicators. The relationships among the four major quality costs are analyzed. Finally, the curves of total quality costs for different quality level are presented.

A full-order multi-objective anti-disturbance robust filter for SINS/GPS navigation systems with multiple disturbances is designed. Generally, the unmodeled dynamics, the external environmental disturbance and the inertial apparatus random drift may exist simultaneously in an integrated navigation system, which can be classified into three type of disturbances, that is, the Gaussian noise, the norm bounded noise and the time correlated noise. In most classical studies, the disturbances in integrated navigation systems are classified as Gaussian noises or norm bounded noises, where the Kalman filtering or robust filtering can be employed, respectively. While it is not true actually, such assumptions may lead to conservative results. The paper aims to discuss these issues.

The Gaussian noises, the norm bounded noises and the time correlated noises in the integrated navigation system are considered simultaneously in this contribution. As a result, the time correlated noises are augmented as a part of system state of the integrated navigation system error model, the relative integrated navigation problem can be transformed into a full-order multi-objective robust filter design problem for systems with Gaussian noises and norm bounded disturbances. Certainly, the errors of the time correlated noises are estimated and compensated for high precision navigation purpose. Sufficient conditions for the existence of the proposed filter are presented in terms of linear matrix inequalities (LMIs) such that the system stability is guaranteed and the disturbance attenuation performance is achieved.

Simulations for SINS/GPS integrated navigation system given show that the proposed full-order multi-objective anti-disturbance filter, has stronger robustness and better precision when multiple disturbances exist, that is, the present algorithm not only can suppression the effect of white noises and norm bounded disturbance but also can estimate and compensate the modeled disturbance.

The proposed algorithm has stronger anti-disturbance ability for integrated navigation with multiple disturbances. In fact, there exist multiple disturbances in integrated navigation system, so the proposed scheme has important significance in applications.

The purpose of this paper is to investigate the economic‐statistical design of EWMA charts with variable sampling intervals (VSIs) under non‐normality to reduce the process production cycle cost and improve the statistical performance of control charts. The objective is to minimize the cost function by adjusting the control chart parameters which suffice for the statistical restriction.

First, using the Burr distribution to approximate various non‐normal distributions, the economic‐statistical model of the VSI EWMA charts under non‐normality can be developed. Further, the genetic algorithms will be used to search for the optimal values of parameters of the VSI EWMA charts under non‐normality. Finally, a sensitivity analysis is carried out to investigate the effect of model parameters and statistical restriction on the solution of the economic‐statistical design.

The result of sensitivity analysis shows that a large lower bound of average time to signal when the process is in control increases the control limit coefficient, no model parameter significantly affects the short sampling intervals, and so on.

The economic‐statistical design method proposed in this paper can improve the statistical performance of economic design of control charts and the general idea can be applied to other VSI control charts.

Titanium(IV) oxide nanoparticles (TiO₂ NP) were deposited to cotton denim fabrics using a self-crosslinking acrylate – a polymer dispersion to extend the lifetime of the products. This study aims to determine the optimum conditions to increase abrasion resistance, to provide self-cleaning properties of denim fabrics and to examine the effects of these applications on other physical properties.

The denim samples were first treated with nonionic surfactant to increase their wettability. Three different amounts of the polymer dispersion and two different pH levels were selected for the experimental design. The finishing process was applied to the fabrics with pad-dry-cure method.

The presence of the coatings and the adhesion of TiO₂ NPs to the surfaces were confirmed by scanning electron microscope and Fourier transform infrared spectroscopy analysis. It was ascertained that the most appropriate self-crosslinking acrylate amount and ambient pH level is 10 mL and “2”, respectively, for providing increased abrasion resistance (2,78%) and enhanced self-cleaning properties (363,4%) in the denim samples. The coating reduced the air permeability and softness of the denim samples. Differential scanning calorimetry and thermogravimetry analysis results showed that the treatments increased the crystallization temperatures and melting enthalpy values of the denim samples. Based on the thermal test results, it is clear that mass loss of the denim samples at 370°C decreased as the amount of self-crosslinking acrylate increased (at pH 3).

This study helped us to find out optimum amount of self-crosslinking acrylate and proper pH level for enhanced self-cleaning and abrasion strength on denim fabrics. With this finishing process, an environmentally friendly and long-life denim fabric was designed.