Taguchi Philosophy of Engineering Quality

Most technology development engineers use traditional reliability engineering methods to calibrate the objective functions of their new systems to meet various marketing requirements. Quality is related to products and services to customer satisfaction. Cost reduction and quality improvement is vital to business. Therefore it is no surprise that both consumers and management are so obsessed with the term quality that a separate branch of quality engineering has been developed. Quite a few glorified terminologies have cropped up such as total quality management (TQM), Quality Function Development (QFD), ISO9000, Continuous quality improvement or KAIZEN, and more popularly six sigma design. These are management-oriented and rather incomprehensible to an average engineer. In contrast, Taguchi methods are easier to comprehend and adopt. They are also based on some common sense ideas. The management's interest was evoked owing to the claimed economic consequences of Taguchi methods of reduced cost with improved quality and consequent consumer satisfaction.

Reliability Engineering Techniques Applied to the Human Failure Analysis Process

Human reliability and human error are factors that are present in all areas: industrial, economic, social, etc. All these areas require to a greater or lesser extent a physical and mental effort to satisfy their own needs, those of others, or established requirements that, depending on the circumstances and the nature of the person, can lead to errors. Certainly, it is not possible to find a single human reliability method that can meet all the expectations and technical demands related to the analysis of human errors. However, it is important to note that the orientation of all human reliability methods is focused on the study and analysis of the risk factor (frequency by consequences). In other words, as can be observed throughout this chapter, all human reliability methodologies seek to help us reduce the uncertainty in the process of evaluating the frequencies of unforeseen events (human errors) and the consequences that such human errors can bring to safety, the environment, and the operations within the framework of an industrial production process.

Reliability Estimation for the Remained Stress-Strength Model under the Generalized Exponential Lifetime Distribution

A stress-strength reliability model compares the strength and stresses on a certain system; it is used not only primarily in reliability engineering and quality control but also in economics, psychology, and medicine. In this paper, a novel extension of stress-strength models is presented. The mew model is applied under the generalized exponential distribution. The maximum likelihood estimator, asymptotic distribution, and Bayesian estimation are obtained. A comprehensive simulation study along with real data analysis is performed for illustrating the importance of the new stress-strength model.

Classical and Bayesian Inference of a Mixture of Bivariate Exponentiated Exponential Model

Exponentiated exponential (EE) model has been used effectively in reliability, engineering, biomedical, social sciences, and other applications. In this study, we introduce a new bivariate mixture EE model with two parameters assuming two cases, independent and dependent random variables. We develop a bivariate mixture starting from two EE models assuming two cases, two independent and two dependent EE models. We study some useful statistical properties of this distribution, such as marginals and conditional distributions and product moments and conditional moments. In addition, we study a dependent case, a new mixture of the bivariate model based on EE distribution marginal with two parameters and with a bivariate Gaussian copula. Different methods of estimation for the model parameters are used both under the classical and under the Bayesian paradigm. Some simulation studies are presented to verify the performance of the estimation methods of the proposed model. To illustrate the flexibility of the proposed model, a real dataset is reanalyzed.

Neutrosophic Exponential Distribution: Modeling and Applications for Complex Data Analysis

The exponential distribution has always been prominent in various disciplines because of its wide range of applications. In this work, a generalization of the classical exponential distribution under a neutrosophic environment is scarcely presented. The mathematical properties of the neutrosophic exponential model are described in detail. The estimation of a neutrosophic parameter by the method of maximum likelihood is discussed and illustrated with examples. The suggested neutrosophic exponential distribution (NED) model involves the interval time it takes for certain particular events to occur. Thus, the proposed model may be the most widely used statistical distribution for the reliability problems. For conceptual understanding, a wide range of applications of the NED in reliability engineering is given, which indicates the circumstances under which the distribution is suitable. Furthermore, a simulation study has been conducted to assess the performance of the estimated neutrosophic parameter. Simulated results show that imprecise data with a larger sample size efficiently estimate the unknown neutrosophic parameter. Finally, a complex dataset on remission periods of cancer patients has been analyzed to identify the importance of the proposed model for real-world case studies.

A Study of Maintenance-Related Education in Swedish Engineering Programs

Engineers of today require a holistic understanding of the lifecycle of products and processes, from conceptualization to operations. Maintenance and reliability are areas receiving increased attention due to the contribution to sustainable industry practices. The related literature describes ways to strengthen the education with respect to curricula and teaching, but studies on the extent and content of maintenance-related education in engineering programs are lacking. The purpose of this study is to describe the maintenance-related education content in Swedish engineering programs. The main objects of study are the curricula and courses of engineering programs in Sweden. In total, 123 Bachelor of Engineering and 119 Master of Engineering programs were studied, as well as 36 maintenance-related courses. It was found that 12% of the engineering programs include one or more maintenance-related course, either mandatory or elective. On the Master of Engineering level, only 4% of the programs include mandatory maintenance-related courses. The corresponding number for Bachelor of Engineering programs is 15%. The courses are typically of 6–7.5 credits, but as low as under one credit worth of maintenance-related content is seen, as well as two specialized programs offering up to 60 credits. Of the 36 courses, 20 have a distinct maintenance focus, 2 are degree thesis courses, and 2 are within reliability engineering, while the rest have a focus in other areas. The lack of maintenance-related education makes future engineers less prepared to make good decisions and judgments that might affect the operational phase of the product or system.