Taguchi's Quality Loss Function Research Articles

Robust parameter design for 3D printing process using stochastic computer model

3D printing technology has been developing rapidly in recent years, but product quality control has become one of the main obstacles to its widespread use in manufacturing. A new stochastic computer model and robust optimization method are proposed for the highly fluctuating 3D printing process to improve the stability of the printed product quality. Firstly, the signal and noise are jointly modeled, and the idea of latent variables in machine learning is incorporated to overcome the limitation that the replication times of the stochastic Kriging model must be greater than one. Then, the chain rule and Woodbury identity are utilized to reduce the time required for hyperparameter estimation of the model. Finally, the optimization objective function is constructed based on the Taguchi quality loss function, and optimal process parameters are found using a genetic algorithm. The numerical simulation results demonstrate that the robust optimization method based on heteroskedasticity Gaussian process model proposed in this paper can estimate model hyperparameters faster and predict results more accurately. Furthermore, the prediction and validation results of 3D printing experiments verify the effectiveness of the proposed method.

Sustainable Quality Management Based on Metrological Sampling Scheme Design: A Case Study of Food Processor

The optimization of the sampling scheme is particularly important in order to achieve sustainability in quality management. This paper discusses the problem of optimizing the design of metrological sampling scheme when the mean is a random variable. Assuming that the prior distribution of product means is known, a Bayesian posterior probability is calculated by using the likelihood function with decision variables to measure the sampling risk, and the expected cost of the sampling scheme is calculated based on the protection of producer and user risk in combination with the Taguchi quality loss function. The influence of model parameters on the selection of the optimal sampling scheme is investigated through sensitivity analysis. The model constructed in this paper solves the problem of sampling design in the case of food processing enterprises, quantifies the quality loss of products in the sampling process, facilitates sustainable quality management of enterprises, and has important theoretical significance and application value for sustainable business management of food processing enterprises.

Sand Supplier Selection Analysis Based on the Integration of Analytical Hierarchy Process (AHP) and Taguchi Quality Loss Function Methods

Supplier selection process is a step to evaluate and select the most suitable supplier to see the needs of the company or organization. This evaluation is important to ensure that the selected supplier is able to provide quality products or services, competitive prices, timely delivery, and meet ethical and sustainability standards. This research uses two methods, namely Analytical Hierarchy Process (AHP) and Taguchi Loss Function. AHP is used to calculate the weight of criteria, while the Taguchi Loss Function is used to estimate losses caused by suppliers. The criteria applied in supplier evaluation are quality criteria, product accuracy, delivery, price, warranty policy, and response to claims. The results obtained from this study PT. Bumi Makmur with a percentage loss of 21%, while the supplier that has the largest loss value is PT. Mergo Bopo with a percentage of 47%.
 Highlights :
 
 Integration of AHP and Taguchi Loss Function enhances supplier selection accuracy.
 Identified supplier exhibits substantial loss percentage, emphasizing the importance of thorough evaluation.
 Findings enable informed decision-making, facilitating risk mitigation and operational optimization
 
 Keywords :Supplier Evaluation; Sand; Analytical Hierarchy Process, Taguchi Loss Function

Surface Integrity Analysis of Wire Electric Discharge Machining of Nitinol Shape Memory Alloy: A Literature Review

When nitinol is machined, quantitative details regarding the surfaces such as the surface crack density, utmost peak-to-valley heights, recast layer thickness and the mean peak-to-valley height among others offer the most appropriate features to consider in the integrity of the surfaces of machined nitinol. This quantitative information directs the integrity and the projected future performance of the machined nitinol in the components. Consequently, the research question of how to achieve optimal surface integrity of the machined nitinol is important. A literature review is conducted to study the surface integrity analysis of wire electrical discharged machined nitinol. In particular, published papers between 2007 and 2021 have been reviewed. Literature is explored concerning the method of analysis, parameters of research interest and the problems/issues arising from the literature. Diverse methods were employed to evaluate the surface integrity of nitinol after machining. Commonly, both mathematical optimization and microstructural characterizations are used to suggest ideas. Mathematical optimization has been in two broad perspectives, namely, experimental design-based methods such as orthogonal arrays, signal-to-noise ratios, Taguchi's utility and quality loss function, Box-Behnken design and response surface methodology. The non-traditional optimization schemes such as the differential evolution, multi-objective optimization based on ratio analysis and teaching learning-based optimization have been applied. For microstructural characterization, tools to evaluate the surface integrity of nitinol such as field emission scanning electron microscope and energy dispersive X-ray have been deployed. Parameters such as residual stress, geometric deviation, microhardness and profile accuracy are pursued to be optimized. It is known that various literature reviews in previous years have studied the surface integrity problem of nitinol using large-scale approaches. However, in this article, a brief review is prescribed and this work reveals how the surface integrity analysis of nitinol has been tackled in the literature.

Many-Objective Optimization and Decision-Making Method for Selective Assembly of Complex Mechanical Products Based on Improved NSGA-III and VIKOR

In Industry 4.0, data are sensed and merged to drive intelligent systems. This research focuses on the optimization of selective assembly of complex mechanical products (CMPs) under intelligent system environment conditions. For the batch assembly of CMPs, it is difficult to obtain the best combinations of components from combinations for simultaneous optimization of success rate and multiple assembly quality. Hence, the Taguchi quality loss function was used to quantitatively evaluate each assembly quality and the assembly success rate is combined to establish a many-objective optimization model. The crossover and mutation operators were improved to enhance the ability of NSGA-III to obtain high-quality solution set and jump out of a local optimal solution, and the Pareto optimal solution set was obtained accordingly. Finally, considering the production mode of Human–Machine Intelligent System interaction, the optimal compromise solution is obtained by using fuzzy theory, entropy theory and the VIKOR method. The results show that this work has obvious advantages in improving the quality of batch selective assembly of CMPs and assembly success rate and gives a sorting selection strategy for non-dominated selective assembly schemes while taking into account the group benefit and individual regret.

Robust design under cumulative damage due to dynamic failure mechanisms

AbstractThe purpose of this paper is to broaden the practical notion of Taguchi's Quality Loss Function (QLF) from a static, one‐stage concept into a dynamic time‐varying tool. Taguchi challenged the old‐age notion of engineering tolerance and proposed a quadratic QLF that quantifies loss to society, caused by deviation of products and systems from their target values. Accordingly, design engineers attempt to set each technical parameter to minimize such systems' losses. Traditionally, failure mechanisms are assumed to affect systems' performance stochastically under a steady state. So often, technical parameters are set at the mid‐point between the lower and upper specification limits where they are least likely to cause a system failure. However, in reality, many failure mechanisms affect systems over time in a predictable and directional manner rather than stochastically. Such mechanisms are designated as “Directional Degrading Failure Mechanisms”. The paper describes an optimized robust design method based on setting the operating points of technical parameters to explicitly counteract the effects of such failure mechanisms. Then, the paper describes how to minimize the lifetime societal loss of a given system utilizing a cardiac pacemaker system. The consequence of this approach suggests an extension to the Taguchi's QLF from its current static confines to a dynamic, time‐varying concept achieving, in our example, ≈65% reduction in lifetime societal losses.

Process quality indices: new metrics for process quality capability with zero-loss baseline

The traditional process capability indices Cp /Cpk for evaluating process capability used in the current industry are based on the probability model of a process distribution, which makes it difficult for many processes whose actual output with non-normal distribution to apply these indices. In this paper, new process quality indices (PQI) Qp /Qpk are proposed for measuring the quality capability of the process. The new PQI are derived from Taguchi's quality loss function model and do not need to estimate the probability distribution of the process output. The traditional process capability indices Cp /Cpk are zero-defect indices, it focus on meeting the process specification requirements, while the new PQI Qp /Qpk are zero-loss indices, it focus on approaching the process target value. The construction of the new PQI is logical, simple, and practical. The PQI approach is more suitable for quality management in the Era of big data.

Reliability analysis for mechanical parts considering hidden cost via the modified quality loss model

AbstractThe improvement of mechanical parts inherent reliability has an impact on the reputation and performance of the company. To estimate the inherent reliability of products more conveniently and economically, a hidden quality cost‐production cost (HQC‐PC) reliability prediction model is put forward. To estimate the hidden quality cost (HQC) of products more accurately, a quadratic exponential quality loss function model is established, which is different from Taguchi's quadratic quality loss function (QLF) and the modified QLFs. In the new quality loss model, the growth rate of quality loss on both sides of the target value is considered. Under the condition that the quality characteristic value obeys normal distribution, the general estimation formulas of HQC in the tolerance range is obtained considering sampling error and the numerical model of inherent reliability is established. The effect of different parameters on the inherent reliability of products is discussed with practical case, such as design and production parameters. Then, the appropriate process capability index (PCI) is selected according to different production processes. The relationship between the HQC‐PC reliability prediction model and PCI is derived by a numerical model of inherent reliability. A new analysis method of inherent reliability is proposed.

Quality Gain-Loss Function and Its Empirical Analysis in Dam Concrete Construction

Wang, B.; Zhou, H.G.; Li, Z.Y.; Fan, T.Y., and Nie, X.T., 2020. Quality gain-loss function and its empirical analysis in dam concrete construction. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 842–848. Coconut Creek (Florida), ISSN 0749-0208.For the quality offset effect that cannot be described by Taguchi quality loss function, the concept of quality gain-loss function (QGLF) is presented in this paper. In considering the interaction between multiple quality characteristics, multivariate quality gain-loss function (M-QGLF) is constructed. The process mean design method of quality gain-loss is discussed under asymmetric conditions respectively. Through an example, the optimum process mean design method is analyzed under the condition of quality characteristic following skewed distribution, and the optimum process mean modified formula and deviation degree calculation formula are proposed. The presentation of QGLF creates the preconditions for the quantitative statistical analysis of quality fluctuation and quality compensation, and provides a new theoretical basis for parameter design. It will also bring great benefit to the production quality improvement as well as get significant economic effect.

Evaluating the reliability of diagnostic performance indices by using Taguchi quality loss function

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.

Optimization of Fractal Dimension of Turned AISI 1040 Steel Surface Considering Different Cutting Conditions

The present work examines the effect of turning process parameters, namely depth of cut and feed rate on the fractal dimension of AISI 1040 steel. Machined surfaces have been characterized using fractal dimensions. Apart from the aforesaid conventional turning parameters, cutting condition has been also considered as a design variable. Three cutting conditions have been considered, e.g. dry, water lubricated, and commercially available water-soluble emulsion lubricated condition. The depth of cut and feed rate has been also been varied at three levels. Experiments were performed following Taguchi's L9 orthogonal array. The optimal setting of process parameters has been achieved through the use of Taguchi's quality loss function represented by a signal-to-noise ratio. The optimal condition predicted from Taguchi's analysis is a 0.4 mm depth of cut, a 0.07 mm/rev feed rate and a water-based emulsion cutting environment. The results obtained for fractal dimensions has been also compared with the more conventional roughness parameter centre line average roughness which is dependent on instrument resolution.

Study and analysis on fuzzy quality control for the high-end manufacturing process based on Taguchi quality loss function

Study and analysis on fuzzy quality control for the high-end manufacturing process based on Taguchi quality loss function

Applying the Taguchi parametric design to optimize the solder paste printing process and the quality loss function to define the specifications

PurposeThis 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/approachStatic 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.FindingsThe 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/valueNoise 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.

Multi-Level Welding Quality Fault Discovery of an Intelligent Production Line by Using Taguchi Quality Loss Function and Signal-Noise Ratio

The rapid and extensive pervasion of intelligent manufacturing concept has enhanced the revolution of the industry. A great interest has arisen in the past five years for the quantity and quality of an intelligent production line. Despite this fact, research areas, such as performance evaluation and fault discovery of these intelligent production lines based on different sets of criteria and techniques, are conspicuously untapped. This paper aims to contribute to the fault discovery by proposing an integrated approach combining the Taguchi quality loss function (QLF), the signal–noise ratio (SNR), and the relief method. First, in order to measure the theoretical value of quality deviation, the Taguchi QLF is introduced. By using the QLF, the information set is transformed into the quality features set. Thereby, the multiple quality features can be fused by using the SNR. Moreover, the features need to be reduced by the relief algorithm, if necessary. The Taguchi QLF-SNR allows decision makers to set tolerance thresholds for multi-levels (characteristic-level/unit-level/system-level) to discover the welding quality fault in the process of production line. Also a case study is presented to verify the feasibility and accuracy of the approach.

Optimization of Multiple Performance Characteristics of Cold rolling Processes Using Taguchi’s Quality Loss Function

The single stand cold rolling mills are generally called as reversing mills, whereby the metal strip is successively wound and unwound in the form of coil as it is repeatedly passed back and forth through the one mill stand. Rolling Pass schedule consists of setting of control parameters at each pass depending on various factor like input and output thickness, width of the coil, material to be rolled, mill capability etc. Majority Quality related problem faced by cold rolled producers using single stand cold rolling are strip thickness variation and strip flatness, also they are concerned about power consumption and production rate. This happens because there is no standard pass schedule available which can predict these Performance parameters. The operator uses thumb rule to make pass schedule. There is no Theoretical model available for such complex cold rolling process. Experimental Model using Taguchi based Single Optimization Method can improve the quality and process performance of the Mill. The main objective of this paper is to show the capability of the Taguchi Quality loss function based multi response optimization methods in increasing productivity of cold rolling process while controlling the Quality and cost of Production. The proposed methodology is used to optimize Multi process performance namely thickness variation, strip flatness, production rate and Power consumption by obtaining optimal solution for control factors exit tension, entry tension, Mill speed and Roll bending pressure for cold rolling of low carbon steel in single stand reversible cold rolling mill. A L_27 orthogonal array was selected and total 27 experiments were conducted after selecting control factors and its levels. Interaction plot shows no interaction among the control parameters. The ANOVA carried out which shows the mill speed is most significant control factor. The optimal values obtained using the multi characteristics optimization Model using Taguchi loss function has been validated by confirmation experiment.

A Hybrid Indicator of Youden Index and Taguchi Loss Function to Determine the Diagnostic Efficiency

Taguchi's robust design aims to reduce the impact of noise on the product or process quality and leads to greater customer satisfaction and higher operational performance. The objective of robust design is to minimize the total quality loss in products or processes. A diagnostic test is a medical test that is applied to a patient in order to determine the presence of a specific disease, where early and accurate diagnosis can decrease morbidity and mortality rates of disease. The application of a diagnostic test in the assessment of a disease may lead to errors, and therefore the accuracy of a diagnostic test is measured in terms of two probabilities: sensitivity and specificity. The problem of two error probabilities in diagnostic tests can be viewed as a digital dynamic system in Taguchi robust design. This paper presents a hybrid index to capture the performance of a diagnostic test based on Youden's index and Taguchi's quality loss function. The loss model of diagnostic tests is proposed due to different loss coefficients between false negative and false positive. The Youden_Taguchi index can be used as a criterion to discriminate non-diseased from diseased individuals for minimizing the total loss of misdiagnoses.

Measuring machine-group flexibility: a case study for surface mount assembly line with different configurations

Flexible production is essential for manufacturers in the face of changing demands for the printed circuited board assembly (PCBA) industry. Machine flexibility is an important factor used to enhance the flexibility of a PCBA system. Configuring the surface mount assembly (SMA) lines is one of the most significant operational decisions of PCBA to cope with variable demands and product variants. Aggregating the flexibility of a chip-placer group is conducive to evaluate the SMA line flexibility, so that decision-makers can develop better production strategy. In this research, a flexibility measuring framework was developed using an entropy-based method and the Taguchi quality loss function to assess SMA line configurations with different chip-placer groups. Based on the resulting flexibility measurements, a neural network model is adopted to estimate the flexibilities of possible chip-placer combinations and suggest the most appropriate line configurations for the subject company. Some findings and managerial implications are also provided.

Taguchi and utility based concept for determining optimal process parameters of cold sprayed coatings for multiple responses

Most of the existing multi-response optimization approaches focus on subjective and practical know how of the process. As a result some confusions and uncertainties are introduced in overall decision making process. In this investigation, an approach based on a Utility theory and Taguchi quality loss function has been applied to low-pressure cold spray process to deposit copper coatings, for simultaneous optimization of more than one response characteristics. In the present paper, three potential response parameters i.e. coating density, surface roughness and Micro hardness have been selected. Utility values based upon these response parameters have been analyzed for optimization by using Taguchi approach. The selected input parameters of powder feeding arrangement, substrate material, air stagnation pressure, air stagnation temperature and stand-off distance significantly improves the Utility function (raw data) comprising of quality characteristics (coating density, surface roughness and micro hardness). The percentage contribution of the parameters to achieve a higher value of utility function is: substrate material (64.59%), air stagnation pressure (16.35%), powder feeding arrangement (6.92%), air stagnation temperature (6.49%) and stand-off distance (1.84%) respectively.

Effect of Additives on Green Sand Molding Properties using Design of Experiments and Taguchi's Quality Loss Function - An Experimental Study

The experimental study aims to underseek the effect of various additives on the green sand molding properties as a particular combination of additives could yield desired sand properties. The input parameters (factors) selected were water and powder (Fly ash, Coconut shell and Tamarind) in three levels. Experiments were planned using design of experiments (DOE). On the basis of plans, experiments were conducted to understand the behavior of sand mould properties such as compression strength, shear strength, permeability number with various additives. From the experimental results it could be concluded that the factors have significant effect on the sand properties as P-value found to be less than 0.05 for all the cases studied. The optimization based on quality loss function was also performed. The study revealed that the quality loss associated with the tamarind powder was lesser compared to other additives selected for the study. The optimization based on quality loss function and the parametric analysis using ANOVA suggested that the tamarind powder of 8 gm per Kg of molding sand and moisture content of 7% yield better properties to obtain sound castings.

Simultaneous settings of order quantity, wholesale price, production run length, process mean, and warranty period

In this article, the authors propose a modified version of S.L. Chen and Liu's model with a two-stage production system. Assume that the retailer's order quantity is concerned with the manufacturer's selling price and the warranty period of product. The used cost of the customer is measured under the Taguchi's quadratic quality loss function and concluded in the retailer's profit function. The quality of the lot for the manufacturer is determined by adopting a two-stage single sampling rectifying inspection plan. The modified economic manufacturing quantity (EMQ) model is addressed in formulating the manufacturer's expected profit. The retailer's order quantity, manufacturer's wholesale price, production run length, process mean, and warranty period of product will be jointly determined by maximizing the total expected profit of the supply chain system including the manufacturer and the retailer. Finally, the quality investment policy is introduced to illustrate the profit improvement for the supply chain system.