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The first book to address the underlying premises of systems integration and how to exposit them into a practical and productive manner, this book prepares systems managers and systems engineers to consider their decisions in light of systems integration metrics. The book addresses two questions: Is there a way to express the interplay of human actions and the result of system interactions of a product with its environment, and are there methods that combine to improve the integration of systems? The systems integration theory and integration frameworks proposed in the book tie General Systems Theory with practice.

A medical test to diagnose a disease is often used to distinguish between healthy and diseased individuals, where early, accurate and reliable diagnosis can decrease morbidity and mortality rates of disease. An optimal cut-off point is required to discriminate healthy from diseased individuals, and a corresponding biomarker value is used to assess the accuracy and robustness whether a person is healthy (negative) or diseased (positive). If the biomarker values, that are greater than or equal to this cut-off value, are considered positive, otherwise they are negative. Several indices such as Youden index, Euclidean index, product of sensitivity and specificity have been used in clinical practices but their reliability of performance are not well understood by clinicians. This study uses Taguchi quality loss function to compare the choice of methods in determining optimal cut-off points for the diagnostic tests. The results illustrate that the variance of diseased populations is less than the variance of healthy populations and the loss coefficient of false negative results is greater than loss coefficient of the false positive results, the Youden index has a better performance; in other cases, the Euclidean index is a better measure. This paper proposes a Taguchi index based on the quality loss function can measure the diagnostic accuracy for differences in the sensitivity and specificity by minimizing the cost of false positive and false negative results. The proposed index can assess diagnostic tests and offer perfect discrimination.

Voltage sags resulting from symmetrical or asymmetrical faults pose a significant threat to power quality. In response to this challenge, a voltage sag loss assessment method based on a two-stage Taguchi quality perspective approach is proposed to address the quantitative analysis of voltage sag economic losses. Initially, using the Taguchi quality perspective method, single-index quality loss functions are separately established for voltage sag magnitude and fault duration. Subsequently, by introducing a comprehensive load tolerance curve, sensitivity parameters within the quality loss function are accurately calculated. This yields a deterministic model for voltage sag assessment. Building upon this, the relative impact of the two indices on voltage sag loss is evaluated using the quality loss function. Consequently, a comprehensive loss model under the influence of multiple indices is formed by integrating two single-index evaluation models. The simulation results indicate that this method can effectively assess the economic losses of voltage sags under the combined influence of multiple factors. Compared to the original economic loss assessment method, it improves quantitative accuracy by approximately 3.72%. Moreover, the method reduces the computational complexity of loss assessment through the consolidation of intervals with similar sensitivity parameters.

The aim of the paper is to develop a method for increasing the signal-to-noise ratio of eddy current measurement of geometric anomalies in static planar objects without actually eliminating the inherent effects of noise factors. This is achieved by means of Taguchi's robust parameter design of rectangular frame surface probes, which allows determining the optimal configuration of their constructions. On a specific example, a robust configuration construction of the eddy current probe design is found, i.e., its technical variant that ensures a reduction of the output signal variance near its average value, i.e., resistance to noise disturbances, due only to the appropriate determination of the values of the controllable design and operating parameters of the probe without eliminating uncontrollable interference inherent in the test objects. For the robust design of a number of eddy current meters with different functionalities, a universal magnetodynamic model of the probe was used, which, together with the application of orthogonal arrays, allows the creation and implementation of Taguchi-design of experiments. The software that implements this model has been verified, including by comparing it with the results of calculations on test’s examples performed using the finite element method. The accuracy achieved in this case allows us to assert the adequacy of the created computer program. The data obtained as part of the Taguchi-design of experiment were used to evaluate design options using the “larger is better“ quality loss function and the signal-to-noise ratios calculated on its basis, which made it possible to select the optimal combination of design and operating parameters of the eddy current probe. The reliability of the found optimal configuration of the eddy current probe design was proved by confirmatory calculations. The research results were also experimentally verified on a prototype. References 21, figures 6, tables 9.

Taguchi’s loss function has been used for optimal tolerance design, but the traditional quadratic quality loss function is inappropriate in the tolerance design of hierarchical products, which are ubiquitous in industrial production. This study emphasizes hierarchical products and extends the traditional quality loss function on the basis of Taguchi’s quadratic loss function; the modified formulas are subsequently used to establish quality loss function models of the nominal-the-best, larger-the-better, and smaller-the-better characteristics of hierarchical products. An example is presented to demonstrate the application of the extended smaller-the-better characteristic loss function model to the optimal tolerance design of hierarchical products. Furthermore, the problem associated with selecting materials of various grades in the design process is discussed. The results show that the extended quality loss function model demonstrates good operability in the tolerance design of hierarchical products.

Concurrent tolerancing becomes an optimisation problem to find out the optimum allocation of the process tolerances in the given design function constraints. In traditional optimisation methods, finding out the optimum solution for this advanced tolerance design problem is complex. The proposed algorithms (elitist non-dominated sorting genetic algorithm) and differential evolution extensively do better than the previous algorithms for attaining the optimum result. The aim of this paper is to suggest a model for optimal tolerance allocation by considering both tolerance cost and the present worth of quality loss such that the total manufacturing cost/loss is minimised. The suggested model takes into account the time value of money for quality loss and product degradation over time and consists of two new parameters: the planning horizon and the product user’s discount rate. From the outcome of this study, a longer planning horizon results in an increase in both tolerance cost and quality loss; however, a larger value of discount rate gives up a decrease in both tolerance cost and quality loss. Finally, a practical example is brought into reveal the effectiveness of the suggested method.

Existing research on quality gain-loss functions predominantly focuses on single variables or separable quality characteristics, overlooking the correlations among multiple quality attributes and the complexity of spatiotemporal factors. To address this issue, this study proposes a multivariate and multidimensional quality gain-loss function model based on a nonseparable Gaussian process (NSGP). A spatiotemporal interaction term is constructed using the Matérn kernel function, while the Kalman filtering and smoothing algorithms are introduced to improve computational efficiency. In addition, the signal-to-noise ratio is employed to determine the joint gain-loss weights, thereby establishing the multivariate and multidimensional quality gain-loss function model. Taking hydraulic concrete construction as the research background, simulation experiments and a practical engineering case are used to examine the performance and applicability of the proposed model. The results indicate that, compared with conventional machine learning methods, the NSGP model achieves superior predictive accuracy and can effectively characterize the spatiotemporal evolution patterns of concrete slump and segregation resistance. However, the interval coverage probability in the dam concrete case study remains lower than the nominal level, indicating that uncertainty quantification requires further improvement. The proposed model does not require prior determination of covariance separability during computation. Under the given dataset and assumptions, it provides an exploratory quantitative tool for point prediction, multivariate quality evaluation, and parameter optimization of selected fresh concrete indicators.

Nickel Titanium (NiTi) alloys are the class of smart materials classified under shape memory alloys. The traditional machining of these alloys is hard because of various inherent mechanical characteristics of these alloys. Therefore, non-traditional machining process such as wire electro discharge machining (WEDM) has been employed for machining of such alloys. The present study is focused on multi-performance characteristic simultaneous optimization of WEDM process parameters, in which three system control factors, namely, pulse on time (TON), pulse off time (TOFF) and wire feed (WF) are considered for simultaneously maximizing material removal rate (MRR), while minimizing surface roughness (SR) and tool wear rate (TWR). The simultaneous optimization is performed using Taguchi’s Quality Loss Function. Analysis of means and analysis of variance have been carried out to identify the significance level of each system control factor. The different levels of settings and the optimized setting have been analysed using scanning electron microscope images for surface morphological studies. The multi-response optimization investigations revealed that TON is the major contributing factor and optimal performance values were obtained at TON of 125μs, TOFF of 25μs and at WF of 4 m/min.

Underwater image analysis is crucial for many applications such as seafloor survey, biological and environment monitoring, underwater vehicle navigation, inspection and maintenance of underwater infrastructure etc. However, due to light absorption and scattering, the images acquired underwater are always blurry and distorted in color. Most existing image enhancement algorithms typically focus on a few features of the imaging environments, and enhanced results depend on the characteristics of original images. In this study, a local cycle-consistent generative adversarial network is proposed to enhance images acquired in a complex deep-water environment. The proposed network uses a combination of a local discriminator and a global discriminator. Additionally, quality-monitor loss is adopted to evaluate the effect of the generated images. Experimental results show that the local cycle-consistent generative adversarial network is robust and can be generalized for many different image enhancement tasks in different types of complex deep-water environment with varied turbidity.

Purpose This research aims to study the stencil printing process of the quad flat package (QFP) component with a pin pitch of 0.4 mm. After the optimization of the printing process, the desired inspection specification is determined to reduce the expected total process loss. Design/methodology/approach Static Taguchi parametric design is applied while considering the noise factors possibly affecting the printing quality in the production environment. The Taguchi quality loss function model is then proposed to evaluate the two types of inspection strategies. Findings The optimal parameter-level treatment for the solder paste printing process includes a squeegee pressure of 11 kg, a stencil snap-off of 0.14 mm, a cleaning frequency of the stencil once per printing and using an air gun after stencil wiping. The optimal upper and lower specification limits are 119.8 µm and 110.3 µm, respectively. Originality/value Noise factors in the production environment are considered to determine the optimal printing process. For specific components, the specification is established as a basis for subsequent processes or reworks.