Signal-to-noise ratio development for quality engineering

Dr. Taguchi developed the concept of signal-to-noise (SN) ratio in quality engineering to evaluate the performance of a system. The objective is to develop systems which are robust against noise factors. The SN ratio indicates the degree of the predictable performance of a product or process in the presence of noise factors. Parameter design of the Taguchi method optimizes the SN ratio in the domain of control factors, so that performance could be made insensitive to the noise factors in order to improve product quality. If the domain of the control factors is a continuous space, the problem is a non-linear programming problem. Usually, in practice, there are only a few available levels for the control factors. Thus, experimental design methods can be useful for such problems. The SN ratio for four cases of dynamic characteristic problems is developed in this paper. This paper also gives the method to compute SN ratios for both equispaced and non-equispaced intervals for levels of signal factors. Two examples are presented to illustrate the method.     

Optimization of product and process design for quality and cost

Robust product and process design is an important technique for achieving high quality at low cost. It involves making the product's function much less sensitive to various sources of noise such as manufacturing variation, environmental variation and deterioration. This is a problem in optimization involving minimization of the mean square loss resulting from the deviation of the product's function from its target. Here we show that the optimization can be carried out in two steps: first maximize a quantity called signal-to-noise ratio (S/N) and then bring the performance on target by special adjustment parameters. The two-step procedure works for a wide variety of product functions and makes the optimization process more efficient and practical compared to the direct minimization of the quadratic loss function.     

Optimization strategies in robust engineering design and computer-aided design

This paper reviews the fundamental ideas involved in robust engineering design (RED), and how they relate to computer-aided design. There are several areas of RED that may be successfully resolved by the use of statistical methods or ideas. This paper gives a general overview of several popular statistical strategies in RED and discusses how these strategies approach the statistical problems involved.     

Mechanical and hydrophobic properties of chromium carbide films via a multi-objective optimization approach

In this study, chromium carbide films are deposited on high-speed tool steel and silicon wafers using an unbalanced magnetron sputtering process. A gradient interlayer consisting of Cr/CrN/CrCN between the chromium carbide layer and substrate is prepared in order to enhance the adhesion. In the experimental design, L18 (2¹ × 3⁷) orthogonal array experiments were used for the statistical purpose and the eight process control factors selected in order to study their contributions to the properties of carbide films. The mechanical and hydrophobic properties were evaluated by means of the coefficient of friction (CoF) and water contact angle (WCA), respectively. For optimizing and balancing the performance of these two properties, a grey relational analysis is applied to combine the two signal-to-noise ratios of self property in a performance index. With the grey Taguchi multi-objective optimization (GTMO) approach, the optimal experimental parameters can be determined and the verification experiments carried out. A comparison of the integrated performance index between the initial and the optimal conditions shows that the magnitude increases from 0.38 to 0.87. For film properties, the CoF decreased from 0.656 to 0.234, and the WCA increased from 83.2 to 96.3°. The gain for integrated performance index by the GTMO from the initial condition is reported as 49% positive.     

Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics

This article addresses an approach based on the Taguchi method with grey relational analysis for optimizing turning operations with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. Optimal cutting parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. Tool life, cutting force, and surface roughness are important characteristics in turning. Using these characteristics, the cutting parameters, including cutting speed, feed rate, and depth of cut are optimized in the study. Experimental results have been improved through this approach.     

Optimization of Removal Rate and Weibull Modulus in Polishing of Ceramic Blocks Using the Fuzzy-Based Taguchi Method

This paper not only analyzed the Weibull modulus through reliability engineering but also obtained the optimal parameters with multiple performance characteristics using the fuzzy-based Taguchi method for polishing ceramic blocks. Optimization with the multiple performance characteristics is found to be the highest speed and greatest load, and diamond particle of 3 μm and 30% concentration. The analysis of variance shows that the most significant polishing parameters are load (57.75%) and speed (24.43%), followed by concentration (12.52%) and diamond particle size (5.30%). Experimental results have shown that the multiple performance characteristics can be improved effectively through this approach.     

Selection of Welding Process Parameters for the Optimum Butt-Joint Strength of an Aluminum Alloy

In this paper, the selection of welding process parameters for obtaining the optimum weld butt-joint ultimate tensile strength (UTS) of aluminum alloy (6061-T6) is presented. Considering weld-joint UTS as the quality characteristic in the selection of process parameters, the Taguchi method is used to analyze the effect of each individual process parameter and of their interaction and then to determine process parameters for the optimum weld-joint UTS. Analysis of variance (ANOVA) technique is applied to investigate which welding process parameter has significant effect on the weld-joint UTS. Experimental results are provided to illustrate the proposed approach.     

Selection of Welding Process Parameters for the Optimum Butt-Joint Strength of an Aluminum Alloy

In this paper, the selection of welding process parameters for obtaining the optimum weld butt-joint ultimate tensile strength (UTS) of aluminum alloy (6061-T6) is presented. Considering weld-joint UTS as the quality characteristic in the selection of process parameters, the Taguchi method is used to analyze the effect of each individual process parameter and of their interaction and then to determine process parameters for the optimum weld-joint UTS. Analysis of variance (ANOVA) technique is applied to investigate which welding process parameter has significant effect on the weld-joint UTS. Experimental results are provided to illustrate the proposed approach.     

Parametric Optimization of Centrifugal Force-Assisted Abrasive Flow Machining (CFAAFM) by the Taguchi Method

Extrusion honing, known as abrasive flow machining (AFM), deburrs, polishes, and radiuses surfaces and edges by flowing an abrasive-laden media over these areas. The process is particularly used on internal shapes that are difficult to process by other nonconventional machining processes. Because abrasive action occurs only in areas where the flow is restricted, tooling is used to direct the media to the appropriate areas. Like other nonconventional machining processes, AFM has the limitation of lower material removal rates. The application of centrifugal force (by using rotating rectangular rod inside the hollow workpiece) has been explored for the productivity enhancement of the process. This article reports that centrifugal force enhances the material removal rate (MRR) and improves the scatter of surface roughness (SSR) value in AFM. It outlines the development of a system that determines sets of viable process parameters for a new process called centrifugal force-assisted abrasive flow machining (CFAAFM). Cylindrical workpieces of brass are used for the experiment. During the experiments, parameters, such as rotational speed of rectangular rod, extrusion pressure, and grit size, were varied to explore their effect on material removal and scatter of surface roughness. Taguchi's parameter design strategy has been applied to investigate the effect of process parameters on the MRR and SSR values.     

Microstructure and texture studies on twin-roll cast AZ31 (Mg-3 wt.%Al-1 wt.%Zn) alloy and the effect of thermomechanical processing

The microstructure and texture of the twin-roll cast (TRC) AZ31 (Mg-3 wt.%Al-1 wt.%Zn) sheet, with a thickness of 6 mm, have been investigated. The TRC AZ31 exhibits a dendritic microstructure with columnar and equiaxed grains. These contain Al-Mn and Mg-Al-Zn second-phase particles that are approximately 1 μm in size. This heterogeneous structure is attributed to the effect of the cooling rate, which varies from 325 °C/s on the surface to ∼150 °C/s in the mid-thickness of the sheet. No surface segregation, but a certain degree of macrosegregation is observed in the mid-thickness which persists after annealing and rolling. Recrystallization at 420 °C leads to a bimodal grain-size distribution, while a fine-grain structure is obtained after rolling and annealing. The TRC AZ31 sheet exhibits basal textures in the (i) as-received, (ii) rolled and (iii) rolled-annealed conditions. However, post-annealing of the TRC AZ31 at 420 °C produces a relatively random texture that has not been previously observed in the conventional AZ31 sheet. The texture randomization is attributed to the particle-stimulated nucleation of new grains in the TRC structure. The preliminary evaluation of mechanical properties indicates that such annealing treatment slightly increases the ultimate tensile strength (UTS), but significantly improves elongation.     

Characterizing and optimizing multi-response processes by the taguchi method

In this paper we demonstrate the ability of the Taguchi technique accurately to characterize and successfully to optimize complicated multi-response processes with the minimum of experiments, provided one uses simple statistical techniques which can ensure valid, and definitive results. We point out the usefulness of suitable data-transformations, and we suggest a systematic procedure for establishing the optimal operating conditions and for carrying out confirmatory experiments. For the particular case detailed in this paper (which is typical of multi-response processes) the Taguchi technique achieved an improvement in uniformity of a factor of 2, together with optimized process control.     

Better than Taguchi orthogonal tables

There has been a great amount of publicity about Taguchi orthogonal tables. This paper will evaluate the pros and cons of that approach. In addition an American approach, having the same initial goals of the Taguchi approach, will be presented in detail, representing a significant improvement in meeting those goals without confounding interactions with any main effect or with other interactions. In addition, this constructive alternative generally requires a much smaller number of tests.     

Surface Roughness and Microhardness Evaluation for EDM with Cu–Mn Powder Metallurgy Tool

In the present research, composite electrode (Cu–Mn) manufactured through powder metallurgy has been used to machine hot die steel (H11) by electrical discharge machining (EDM) process with the aim of inducing manganese and carbon into the machined surface. Such alloying is expected to improve the microhardness and other surface characteristics. Best level of process parameters for better surface finish and high microhardness are found using Taguchi method. Six processing parameters are considered and their significance is investigated by analysis of variance. Techniques like energy dispersive spectroscopy, scanning electron microscopy, and X-ray diffraction are used to ascertain the surface characteristics. Surface machined at optimum process conditions for microhardness shows 93.7% improvement due to formation of cementite, ferrite and manganese carbide phases. Surface roughness having Ra value of 3.11 µm has been achieved.