Bayesian testing for process capability indices

Process capability indices have been widely used in the manufacturing industry. They measure the ability of a manufacturing process to produce items that meet certain specifications. A capability index relates the voice of the customer (specification limits) to the voice of the process. There is a need to understand and interpret process capability indices. Most of the existing work in this area has been devoted to classical frequentist large sample theory. An alternative approach to the problem of making inference about capability indices is the Bayesian approach. In this paper a Bayesian version of Tukey’s method is used for constructing simultaneous credibility intervals for all pairwise differences. A Bayesian procedure for testing all possible contrasts is also given. The problem of selecting the best supplier(s) has received considerable attention in the literature, but mainly from a classical frequentist point of view. A Bayesian simulation procedure is also illustrated to find the best supplier or group of suppliers.This method seems much easier to perform than the Monte Carlo integration method given in Wu, Shiau, Pearn and Hung (2016). In section 10, a sensitivity analysis regarding the prior choice is considered and in the last section, t-distributed data are analysed

A Variable Control Chart Based on Process Capability Index Under Generalized Multiple Dependent State Sampling

This paper proposed a process capability index-based control chart under the new extended form of multiple-dependent state sampling (MDS) named generalized MDS (GMDS). The scheme is based on inner and outer control limits and utilizes the previous state of the samples. The performance comparisons of the proposed chart with the existing charts are made by using out-of-control ARL. The simulation study showed the superiority of the proposed chart over the existing PCI-based control charts under Shewhart and MDS schemes. An empirical illustration is also given to demonstrate the application of the proposed chart.11Ysciescopu

Capability Testing Based on C pm with Multiple Samples

Numerous process capability indices have been proposed in the manufacturing industry to provide unitless measures on process performance, which are effective tools for quality improvement and assurance. Most existing methods for capability testing are based on the distribution frequency approaches. Recently, Bayesian approaches have been proposed for testing capability indices C p and C pm but restricted to cases with one single sample. In this paper, we consider estimating and testing capability index C pm based on multiple samples. We propose accordingly a Bayesian procedure for testing C pm . Based on the Bayesian procedure, we develop a simple but practical procedure for practitioners to use in determining whether their manufacturing processes are capable of reproducing products satisfying the preset capability requirement. A process is capable if all the points in the credible interval are greater than the pre-specified capability level. To make the proposed Bayesian approach practical for in-plant applications, we tabulate the minimum values of C * (p) for which the posterior probability p reaches various desirable confidence levels

Systems Engineering

The book "Systems Engineering: Practice and Theory" is a collection of articles written by developers and researches from all around the globe. Mostly they present methodologies for separate Systems Engineering processes; others consider issues of adjacent knowledge areas and sub-areas that significantly contribute to systems development, operation, and maintenance. Case studies include aircraft, spacecrafts, and space systems development, post-analysis of data collected during operation of large systems etc. Important issues related to "bottlenecks" of Systems Engineering, such as complexity, reliability, and safety of different kinds of systems, creation, operation and maintenance of services, system-human communication, and management tasks done during system projects are addressed in the collection. This book is for people who are interested in the modern state of the Systems Engineering knowledge area and for systems engineers involved in different activities of the area. Some articles may be a valuable source for university lecturers and students; most of case studies can be directly used in Systems Engineering courses as illustrative materials

Minimizing rework costs in multistage production processes by modifying quality specification limits

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksMultistage production processes are becoming more important in the industry to ensure levels of flexibility, efficiency and modularity. Thus, the way in which companies define optimal production parameters related to production costs and quality must be adapted to this reality. In this paper we introduce a multi-response optimization (MRO) model for a two stage production process. The model gives first stage quality specification limits which minimize the rework costs caused by the nonconforming parts of the whole process. The proposed model is applied to an example based on a production process of the automotive industry. The benefits of the model are evaluated by comparing the capability and the rework costs of the multistage production process before and after the optimization.Peer ReviewedPostprint (published version

An Analytic Hierarchy Process approach to assess health service quality

While improving quality in health care is currently at the forefront of professional, political, and managerial attention, the key dimensions constituting health-care quality have not been fully understood. Also, few valid approaches have been proposed to the measurement of health-care quality. In this research, the Analytic Hierarchy Process (AHP) approach is applied to study the structure of health-care quality and deducted relative importance weights for each of the quality elements. A statistical quality model is derived to assess medical equipment quality which is an important part constituting the general health-care quality. Finally, the application of the AHP model to assess health-care quality is demonstrated based on a scenario

The Effects of Autocorrelation in the Estimation of Process Capability Indices.

The current popularity of the process capability index, a measure of a supplier\u27s ability to meet the product specifications demanded by a customer, has become a matter of some controversy. While admitting the validity of much existing criticism, this research demonstrates that sample estimation of the triple index (Cpl, Cp, Cpu), a variant of the widely used index pair (Cp, Cpk), is equivalent to estimation of the natural parameters (mu, sigma) whenever the measured process characteristic X has an unconditional (marginal) normal probability density function. This includes processes which obey the strictly stationary, normal ARMA( p, q) model. By this extension to stationary normal models beyond ARMA(0, 0), the author shows the continued viability of the process capability index as a decision making tool of wider applicability. Estimators of the indices (Cpl, Cp, Cpu) are studied under conditions of both sample independence and sample autocorrelation. A new method for determining a joint confidence region for the triple index (Cpl, Cp, Cpu) is given. The region presented is, both conceptually and computationally, more direct than previously known approaches

Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction

Quality deviation requirements in residential buildings: predictive modeling of the interaction between deviation and cause

To address construction defects, sub-task requirements (STRs) were generated alongside a Bayesian belief network-BBN quantification, towards the modelling of a unique causation pattern. The study found that the patterns of direct causes of deviation from quality norms are unique for each STR, and that causation patterns cannot be generalised. The work conducted provides Building-Quality-Managers with a new visualization tool to clarify the STR-specific cause of quality deviation pathways when creating the built environment

Circuit Design

Circuit Design = Science + Art! Designers need a skilled "gut feeling" about circuits and related analytical techniques, plus creativity, to solve all problems and to adhere to the specifications, the written and the unwritten ones. You must anticipate a large number of influences, like temperature effects, supply voltages changes, offset voltages, layout parasitics, and numerous kinds of technology variations to end up with a circuit that works. This is challenging for analog, custom-digital, mixed-signal or RF circuits, and often researching new design methods in relevant journals, conference proceedings and design tools unfortunately gives the impression that just a "wild bunch" of "advanced techniques" exist. On the other hand, state-of-the-art tools nowadays indeed offer a good cockpit to steer the design flow, which include clever statistical methods and optimization techniques.Actually, this almost presents a second breakthrough, like the introduction of circuit simulators 40 years ago! Users can now conveniently analyse all the problems (discover, quantify, verify), and even exploit them, for example for optimization purposes. Most designers are caught up on everyday problems, so we fit that "wild bunch" into a systematic approach for variation-aware design, a designer's field guide and more. That is where this book can help! Circuit Design: Anticipate, Analyze, Exploit Variations starts with best-practise manual methods and links them tightly to up-to-date automation algorithms. We provide many tractable examples and explain key techniques you have to know. We then enable you to select and setup suitable methods for each design task - knowing their prerequisites, advantages and, as too often overlooked, their limitations as well. The good thing with computers is that you yourself can often verify amazing things with little effort, and you can use software not only to your direct advantage in solving a specific problem, but also for becoming a better skilled, more experienced engineer. Unfortunately, EDA design environments are not good at all to learn about advanced numerics. So with this book we also provide two apps for learning about statistic and optimization directly with circuit-related examples, and in real-time so without the long simulation times. This helps to develop a healthy statistical gut feeling for circuit design. The book is written for engineers, students in engineering and CAD / methodology experts. Readers should have some background in standard design techniques like entering a design in a schematic capture and simulating it, and also know about major technology aspects