Process Quality Index Research Articles

Development and properties of glass fiber reinforced plastics geogrid

Glass fiber reinforced plastics geogrid has a wide application in the field of soil reinforcement because of its high strength, good toughness, and resistance to environmental stress, creep resistance and strong stability. In order to get high-powered glass fiber reinforced plastics geogrid and its mechanical characteristics, the properties and physical mechanical index of geogrid have been got through the study of its raw material, production process and important quality index. The analysis and study have been made to the geogrid’s mechanical properties with loading speed, three-axial compression, temperature tensile test and FLAC3D numerical simulation, thus obtain the mechanical parameters of its displacement time curve, breaking strength and elongation at break. Some conclusions can be drawn as follows: (a) Using glass fiber materials, knurling and coated projection process, the fracture strength and corrosion resistance of geogrid are greatly improved and the interlocking bite capability of soil is enhanced. (b) The fracture strength of geogrid is related to temperature and loading rate. When the surrounding rock pressure is fixed, the strength and anti-deformation ability of reinforced soil are significantly enhanced with increasing reinforced layers. (c) The pullout test shows the positive correlation between geogrid displacement and action time. (d) As a new reinforced material, the glass fiber reinforced plastics geogrid is not mature enough in theoretical research and practical experience, so it has become an urgent problem both in theoretical study and practical innovation.

Design of EWMA Control Charts for Assuring Predetermined Production Process Quality

In this study, we establish the relationship model in process capability indices, the coefficient of process shift and quality target utilizing statistical tolerance technology. A new systematic method for concurrent design of process quality, Statistical Tolerance (ST) and control chart is presented. A set of standardized Process Quality Indices (PQIs) for variables is introduced for meeting the measurement and evaluation to process yield, process centering and quality loss. To develop a quality-oriented SPC approach, a standardized interface between process quality indices system and the parameter design of EWMA control charts is needed. The two-dimensional array form ST (C_p*, &delta*) is presented for selecting a set of parameters (&lambda, L) with suitable ARL₀ and ARL1 to realize the optimal control for a process toward a predetermined quality target. The ST (C_p*, k*) will be the guideline to form the restriction of the centerlines of the control charts for assuring the preset PQIs. If the process statistical parameters are unknown, (C_p*, k*) will be converted into the ST form for estimated values based on a required confidence probability. A case study shows the detail procedure of this concurrent design for PQIs, ST and SPC parameters.

Quality-Related Process Monitoring Based on Total Kernel PLS Model and Its Industrial Application

Projection to latent structures (PLS) model has been widely used in quality-related process monitoring, as it can establish a mapping relationship between process variables and quality index variables. To enhance the adaptivity of PLS, kernel PLS (KPLS) as an advanced version has been proposed for nonlinear processes. In this paper, we discuss a new total kernel PLS (T-KPLS) for nonlinear quality-related process monitoring. The new model divides the input spaces into four parts instead of two parts in KPLS, where an individual subspace is responsible in predicting quality output, and two parts are utilized for monitoring the quality-related variations. In addition, fault detection policy is developed based on the T-KPLS model, which is more well suited for nonlinear quality-related process monitoring. In the case study, a nonlinear numerical case, the typical Tennessee Eastman Process (TEP) and a real industrial hot strip mill process (HSMP) are employed to access the utility of the present scheme.

A Study of Process Quality Assessment for Golf Club-Shaft in Leisure Sport Industries

Abstract Effective management of process quality is crucial for attracting customers and maintaining their loyalty, and the quantification of quality for processes with multiple characteristics has recently been receiving considerable attention. This paper proposes a comprehensive process quality index to provide numerical measures for the precision, accuracy, and performance of processes in the manufacturing of golf club-shafts, using both smaller-the-better type and symmetric nominal-the-best type characteristics. The point estimates of these indices were replaced with joint confidence blocks in order to overcome a lack of reliability. Based on this index, we developed a control chart with process capability zones describing joint confidence blocks of all characteristics related to golf club-shafts within a single chart. Finally, we present an assessment procedure and illustrated examples with which to evaluate the process quality for the manufacture of golf club-shaft. The results reveal that the straightness and torsion of the club-shaft are “out of control” and unqualified, whereas the length, tip outer circumference, and butt outer circumference of the club-shaft are categorized as “excessive.” The application of this chart enables engineers involved in the manufacturing of golf equipment to simultaneously monitor and control the quality characteristics of golf club-shafts.

Optimization and Analysis of WEDM Process Parameters Based on Nonlinear Regression Model

The process parameters of wire cut electrical discharge machining were optimized to improve machining quality and efficiency.The nonlinear regression model of process parameters and processing index was established. The objective function is presented by test method and an optimization result containing multiple parameters was achieved. The results show that the nonlinear regression model can accurately reflect the relation between process parameters and quality index.

Application of Optimization Algorithms in Injection Molding Process Parameters

The data of process parameters and quality index from CAE simulation orthogonal test is used as training samples, the BP neural network is trained and the neural networks ensemble approximate calculation agent model of the relations between processing parameters and the quality index of product are obtained. The agent model with a clear mathematical formula calculates quickly and accurately, so it can optimize globally by the genetic algorithm. The best group of process parameters is obtained and a multi-objective optimization of the quality index of products is realized.

A coordinate SPC model for assuring designated fit quality via quality-oriented statistical tolerancing

On the basis of studies to process quality indices and fit quality indices, the quality-oriented statistical tolerancing is introduced, which provides an interface between fit quality and the process parameter design of mating parts. A statistical mating model via the quality-oriented statistical tolerancing under information-based manufacturing condition is discussed. Compared with traditional mating model for a pair of hole/shaft fit, the statistical mating model is developed for equal batches of hole/shaft fit, and it can achieve a designated fit quality and minimum defective ratio by fully utilizing statistical tolerance zone and the known information of manufactured mating parts via a coordinate SPC model and local network and information system. Thus, production cost for mating parts can be reduced obviously. This new approach provides a possibility and guideline to concurrent design of the process quality, statistical tolerances to assure designated process quality and fit quality for hole and shaft parts.

Concurrent Design for Process Quality, Statistical Tolerance, and SPC

The rapid response to the requirements of customers and markets promotes the concurrent engineering (CE) technique in product and process design. The decision making for process quality target, SPC method, sampling plan, and control chart parameter design can be done at the stage of process quality plan based on historical data and process knowledge database. Therefore, it is a reasonable trend to introduce the concepts and achievements on process quality evaluation and process capability analysis, CE, and SPC techniques into process plan and tolerance design. A new systematic method for concurrent design of process quality, statistical tolerance (ST), and control chart is presented based on a NSFC research program. A set of standardized process quality indices (PQIs) for variables is introduced for meeting the measurement and evaluation to process yield, process centering, and quality loss. This index system that has relatively strong compatibility and adaptability is based on raisonne grading by using the series of preferred numbers and arithmetical progression. The expected process quality based on this system can be assured by a standardized interface between PQIs and SPC, that is, quality-oriented statistical tolerance zone. A quality-oriented ST and SPC approach that quantitatively specifies what a desired process is and how to assure it will realize the optimal control for a process toward a predetermined quality target.

Quantitative model for evaluating the quality of an automotive business process

One of the key issues to business process control is the identification of measurable process attributes. For manufacturing processes these are typically physical parameters of the process (e.g. temperature, set points) or physical attributes of the manufactured product (e.g. dimension, functional performance). However, for business processes the metrics are more abstract. The challenge has been to develop metrics that capture the contributing subtle and hard to measure factors for business process control. This paper presents an analytical model that uses the weights-of-evidence concept to convert answers to audit or self-assessment questions into a single numerical process quality index. This index is used to forecast process success or failure and monitor its performance from start to end. The application of the approach is illustrated with an automotive industry product development sub-process where the process performance metric is the field warranty data, i.e. incidents per thousand vehicles (IPTV). The analytical model converts process self-assessment (failure mode and effect analysis) questions into a single numeric process quality index. The validity of the model is reflected in the strength of the correlation between the index and the IPTV results. Also, in this paper a measure is developed for identifying critical process quality assessment questions. This measure quantifies the deviation in the automotive business process that should have more focus. The significance of the analytical model proposed in this research is that the project managers or quality assurance auditors may be able to use the metric to predict product quality at any point in the product development process.

A MAIC approach to TFT-LCD panel quality improvement

The liquid crystal displays (LCDs) possess the most mature technology and best consuming competitiveness in the flat panel display (FPD) industries. Of all the LCDs, thin film transistor-liquid crystal display (TFT-LCD) keeps some real advantages. It is thinner, smaller and lighter than other displays and has low power consumption, low-radiation, high-contrast and high-dpi at the same time. Hence, the TFT-LCD panel is widely applied in daily electronic products, and the demand for the TFT-LCD panel increases. The product life cycle of the TFT-LCD panel is gradually getting into the mature stage, and meanwhile, Taiwan’s firms face fierce competition from South Korea and Japan. Thus, at present, continual cost reduction is an all-out pursuing topic for Taiwan’s panel manufacturers. If the quality and yield of the TFT-LCD panel can be effectively enhanced, the non-conforming rate and the cost of the TFT-LCD panel will be reduced. In this study, TFT-LCD panel manufacturing process is discussed, and then five critical-to-quality (CTQ) characteristics (or sub-processes) are identified and summarized. At the early stages, the assessing model of process quality index ( C pm) and the MAIC (i.e., measure-analyze-improve-control) approach of Six Sigma are used to measure and analyze the CTQ characteristics that make TFT-LCD panel unqualified and incapable. During the later stages, Hartley’s homogeneity test and joint confidence intervals were conducted to determine the optimal parameter setting of the critical factor in TFT-LCD panel manufacturing process. By using these optimal settings, Six Sigma quality level can be achieved.

Three-way data analysis with time lagged window for on-line batch process monitoring

In this paper, on-line batch process monitoring is developed on the basis of the three-way data structure and the time-lagged window of process dynamic behavior. Two methods, DPARAFAC (dynamic parallel factor analysis) and DTri-PLS (dynamic trilinear partial least squares), are used here depending on the process variables only or on the process variables and quality indices, respectively. Although multivariate analysis using such PARAFAC (parallel factor analysis) and Tri-PLS (trilinear partial least squares) models has been reported elsewhere, they are not suited for practicing on-line batch monitoring owing to the constraints of their data structures. A simple modification of the data structure provides a framework wherein the moving window based model can be incorporated in the existing three-way data structure to enhance the detectability of the on-line batch monitoring. By a sequence of time window of each batch, the proposed methodology is geared toward giving meaningful results that can be easily connected to the current measurements without the extra computation for the estimation of unmeasured process variables. The proposed method is supported by using two sets of benchmark fault detection problems. Comparisons with the existing two-way and three-way multiway statistical process control methods are also included.

Kinetics of fine powder centrifugation

Sedimentation of polydispersed particles in a centrifugal field as applied to the process of fine powder hydroclassification is regarded as a random Markovian process. According to the analytical solution of the boundary problem by the Kolmogorov—Fokker—Planck equation the separation process quality index depends upon the particle porperties and the process conditions. The results of the calculation are compared with the experimental data on the classification of fine abrasive powders.