Improvement of mechanical properties of recycled plastic blends via optimizing processing parameters using the Taguchi method and principal component analysis

In this paper, the Taguchi method and principal component analysis (PCA) are used to improve the mechanical properties of recycled polypropylene (PP) blends in injection moulding procedure, with detailed assessments performed on each method and comparison was made based on results of both the methods. The experimental design was carried out by adopting a L9-3⁴ Taguchi orthodoxy array (OA), which has four controllable factors (i.e., melt temperature, mould temperature, injection speed and packing pressure) at three levels. Injection moulded specimens made from different compositions of virgin-recycled PP were tested to determine the optimal conditions for the injection moulding procedure. The effects of the processing parameters and the proportion of recycled plastic in composites on the mechanical properties were investigated, the optimal conditions for desired properties were obtained and then verified. The appropriate blending ratio of virgin and recycled plastic was evaluated. The results reveal that deteriorations in the mechanical properties of products produced from recycled plastic can be improved by optimizing the processing parameters during the injection moulding procedure.     

Application of Taguchi approach to optimize the sol–gel process of the quaternary Cu2ZnSnS4 with good optical properties

Present research deals with the optimal deposition parameters configuration for the synthesis of Cu₂ZnSnS₄ (CZTS) thin films using the sol–gel method associated to spin coating on ordinary glass substrates without sulfurization. The Taguchi design with a L9 (3⁴) orthogonal array, a signal-to-noise (S/N) ratio and an analysis of variance (ANOVA) are used to optimize the performance characteristic (optical band gap) of CZTS thin films. Four deposition parameters called factors namely the annealing temperature, the annealing time, the ratios Cu/(Zn + Sn) and Zn/Sn were chosen. To conduct the tests using the Taguchi method, three levels were chosen for each factor. The effects of the deposition parameters on structural and optical properties are studied. The determination of the most significant factors of the deposition process on optical properties of as-prepared films is also done. The results showed that the significant parameters are Zn/Sn ratio and the annealing temperature by applying the Taguchi method.     

Optimization of tensile properties thermoplastic blends from soy and biodegradable polyesters: Taguchi design of experiments approach

Soy meal-based biodegradable blends were prepared by melt extrusion process. The effects of denaturants, i.e., urea and sodium sulfite and plasticizer (glycerol) and polyester type (polybutylene succinate, polycaprolactone, polybutylene adipate terephthalate) on tensile strength and elongation at break were investigated using a Taguchi experimental design approach. The results showed that the sodium sulfite had little or no effect on final properties of the blends. Also, biodegradable polyester type had significant effect on the tensile strength and elongation at break of the blends prepared. The predicted values and experimental were found to be in tune with each other. The chemical structure and morphology of the optimum sample was probed by FT-IR spectroscopy and scanning electron microscopy (SEM). Also, the results provided an insight into how important the plasticization and destructurization of soy protein to obtain the blends with desired mechanical properties.     

Economic optimization of off-line inspection

In this paper we solve the problem of determining the optimal inspection/disposition policy for a finite batch of items produced by a machine that is subject to random breakdowns. In particular, we identify which units should be inspected and in which order so as to minimize costs. The operational implications of the optimal policy are analyzed with a selected set of numerical results. We place special emphasis on three different policies: the cost minimizing policy; the policy of perfect information, i.e., we insist on determining the quality of each unit; and the policy of zero-defects,i.e., we insist that all accepted units are known to conform to specifications, allowing the rejection of units of unknown quality. We also show how the optimal inspection/disposition policy is incorporated into the optimization of the batch size.     

Interval Estimation for the Smaller-the-Better Type of Signal-to-Noise Ratio using Bootstrap Method

The signal-to-noise ratio is an indicator, introduced by Taguchi, for evaluating the experimental data in robust design. Estimating the confidence interval of the signal-to-noise ratio is an important topic in data analysis of robust design. Calculating the confidence interval for a parameter usually needs the assumption about the underlying distributions. Bootstrapping is a nonparametric, but computer-intensive estimation method. In this article, we present the results of a simulation study on the behavior of three 95% bootstrap confidence intervals (i.e., SB, PB, and BCPB) for estimating the smaller-the-better signal-to-noise ratio when the data are from either a normal distribution or one of the Burr distributions. A detailed discussion of the simulation results is presented and some recommendations are given.     

Efficient heuristics for robot acquisition planning for a CIM system

In this paper, a planning model and three efficient heuristics are developed for equipment acquisition planning for a CIM system using multiple-type robots. Our planning model considers selection of a proper mix of multiple-type robots such that operational requirements (i.e., time and space) from a given number of work stations are satisfied at minimal system cost. In specific, each robot is characterized by its fixed charge and subject to two capacity constraints on machine time and work space; and each work station has known demands for both machine time and work space, and is to be served by only one robot. The model is formulated as a pure 0–1 mathematical program and is shown to be harder than two-dimensional bin packing, a well-known NP-hard problem. The three heuristics developed are: a greedy heuristic, tabu thresholding, and simulated annealing. All heuristics are tested by solving 450 randomly generated problems. Computational results indicate that all three heuristics are effective and efficient in solving problems of a practical size (i.e., 50 work stations and a maximum of 20 robots). However, none of the heuristics are overwhelmingly better than the others in terms of both solution time and quality. Future research issues are also discussed.     

The use of a generalized signal-to-noise ratio to identify adjustment and dispersion factors in taguchi experiments

A signal-to-noise ratio proposed by Taguchi for ‘nominal the best’ can be made more flexible and used additionally for the cases ‘smaller the better’ and ‘larger the better’. The main feature which distinguishes this generalized ratio from Taguchi's signal-to-noise ratios is that its precise form is determined by the experimental data. Taken together with a transformation of the mean response it effectively identifies adjustment (signal) factors and dispersion factors. Examples are given to illustrate the routine operational procedure and also to demonstrate that Taguchi's signal-to-noise ratios can lead to inefficient, and sometimes incorrect, identification of design factors. Two important considerations are to preserve the evident appeal of the Taguchi method to engineers and also to provide a theoretical justification which is acceptable to statisticians. The principal objective of the joint transformation is to achieve approximate functional independence between the mean and variance in the new metric. This, in turn, leads to efficient identification of adjustment and dispersion factors. A comparison is made with a similar approach using Box and Cox transformations.     

A Taguchi Design of Experiment Approach to Pulse and Lock in Thermography,Applied to CFRP Composites

The current text presents a parametric study of two active thermography routines namely, Pulse and Lock-in as applied to carbon fiber reinforced plastics (CFRP) composites; using a Taguchi design of experiment approach. A set of controllable factors are highlighted and selected for each technique at different levels. Three factors have been identified for the pulse thermography (specifically; defect aspect ratio, pulse period, and experimental duration), and two factors for the Lock-in mode (that is lock in frequency and period); each factor can be manipulated at three different levels. The analysis reveals the effectiveness of the Taguchi design of experiment in consolidating the number of factorial experiments, and in quantifying the results and the associated sensitivity for each factor (its dominance), using a signal to noise ratio criterion. The analysis of variance and analysis of means show that the aspect ratio is not a controlling parameter for the pulse thermography, with the pulse time being the most dominant. Moreover, it decides on the optimal settings for each testing mode. These settings are further validated using additional CFRP artificial sample with eight and six layers of laminates.     

Simultaneous measurement of shrinkage and temperature of reactive powder concrete at early-age using fibre Bragg grating sensors

The physical properties of reactive powder concrete (RPC) at early-age, i.e., the first 24 h from casting, and up to an age of 7 days is investigated experimentally using fibre Bragg gratings (FBGs), a type of fibre-optic sensors. A number of FBG sensors are multiplexed together and embedded directly into the RPC specimens, and the shrinkage and temperature change are measured directly and simultaneously. The final setting time and specimen size effect were also investigated. Results showed that there is an interplay between the shrinkage and temperature. The overall shrinkage for 7 days is 488 με, with the early-age shrinkage contributing about 77% of this. The temperature curve exhibits a double peak behaviour, with the first peak appears at about 7 h, which is the final setting time. There is a size effect in that smaller prisms have a higher overall shrinkage and lower temperature change than larger prisms.     

Influences of clay and manufacturing on fire resistance of organoclay/thermoset nanocomposites

The organoclay GFRP nanocomposites are prepared using the vacuum assisted resin transfer moulding method. Two grades of organophilic clay with three content levels, three types of thermosetting resins (polyester, vinyl ester and epoxy), and three nanoclay dispersion techniques are investigated. To understand the effects of these factors on the fire performance, Taguchi design of experiments (DoE) method is employed and preferred combinations of factors are determined using a one-step and a proposed two-step GLM ANOVA. The one-step ANOVA is applied directly on the experimental results, while the two-step ANOVA is conducted on the signal-to-noise ratios obtained from the Taguchi analysis. The combination of mechanical and ultrasonic dispersing procedure has been found to have considerable influence on the of nanoclay distribution. While both approaches provide insights into the influences of each fabrication factor, the two-step gives a better prediction of the favourable response combination for the nanocomposites when validated with experiments.     

高光注塑成型工艺控制试验

建立了制品对模具型腔复原性的宏观量化表征模型,以自主开发的车用高光蓝牙模具和温控辅助装置为试验基础,以制品质量、线收缩率、翘曲变形和沉降指数等为品质考核指标,采用试验生产与仿真分析相结合的方法对高光制品成型性能进行了试验研究。在考虑到各指标权重因素的同时,采用信噪比之望小特性理论实现了样本数据的归一化处理。得出了各考核参数相对于各个品质指标的影响趋势及影响显著性顺序,进而研究得出了相对于该高光制品的最佳成型工艺组合。     

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.     

Taguchi design-based optimization of sandwich immunoassay microarrays for detecting breast cancer biomarkers

Taguchi design, a statistics-based design of experiment method, is widely used for optimization of products and complex production processes in many different industries. However, its use for antibody microarray optimization has remained underappreciated. Here, we provide a brief explanation of Taguchi design and present its use for the optimization of antibody sandwich immunoassay microarray with five breast cancer biomarkers: CA15-3, CEA, HER2, MMP9, and uPA. Two successive optimization rounds with each 16 experimental trials were performed. We tested three factors (capture antibody, detection antibody, and analyte) at four different levels (concentrations) in the first round and seven factors (including buffer solution, streptavidin-Cy5 dye conjugate concentration, and incubation times for five assay steps) with two levels each in the second round; five two-factor interactions between selected pairs of factors were also tested. The optimal levels for each factor as measured by net assay signal increase were determined graphically, and the significance of each factor was analyzed statistically. The concentration of capture antibody, streptavidin-Cy5, and buffer composition were identified as the most significant factors for all assays; analyte incubation time and detection antibody concentration were significant only for MMP9 and CA15-3, respectively. Interactions between pairs of factors were identified, but were less influential compared with single factor effects. After Taguchi optimization, the assay sensitivity was improved between 7 and 68 times, depending on the analyte, reaching 640 fg/mL for uPA, and the maximal signal intensity increased between 1.8 and 3 times. These results suggest that Taguchi design is an efficient and useful approach for the rapid optimization of antibody microarrays.     

An adaptive image denoising method based on local parameters optimization

In image denoising algorithms, the noise is handled by either modifying term-by-term, i.e., individual pixels or block-by-block, i.e., group of pixels, using suitable shrinkage factor and threshold function. The shrinkage factor is generally a function of threshold and some other characteristics of the neighbouring pixels of the pixel to be thresholded (denoised). The threshold is determined in terms of the noise variance present in the image and its size. The VisuShrink, SureShrink, and NeighShrink methods are important denoising methods that provide good results. The first two, i.e., VisuShrink and SureShrink methods follow term-by-term approach, i.e., modify the individual pixel and the third one, i.e., NeighShrink and its variants: ModiNeighShrink, IIDMWD, and IAWDMBMC, follow block-by-block approach, i.e., modify the pixels in groups, in order to remove the noise. The VisuShrink, SureShrink, and NeighShrink methods however do not give very good visual quality because they remove too many coefficients due to their high threshold values. In this paper, we propose an image denoising method that uses the local parameters of the neighbouring coefficients of the pixel to be denoised in the noisy image. In our method, we propose two new shrinkage factors and the threshold at each decomposition level, which lead to better visual quality. We also establish the relationship between both the shrinkage factors. We compare the performance of our method with that of the VisuShrink and NeighShrink including various variants. Simulation results show that our proposed method has high peak signal-to-noise ratio and good visual quality of the image as compared to the traditional methods: Weiner filter, VisuShrink, SureShrink, NeighBlock, NeighShrink, ModiNeighShrink, LAWML, IIDMWT, and IAWDMBNC methods.     

预应力活性粉末混凝土受弯过程声发射特性

为研究钢纤维增强活性粉末混凝土（SF/RPC）复合材料的受弯破坏微观机制,对10根试验梁进行抗弯试验研究。基于声发射技术,采用宽频传感器对试验过程中的声发射信号和波形进行了采集。分析研究了SF/RPC材料的声发射特征参数,在对波形进行信号处理的基础上对波形频谱进行了深入研究。通过传感器之间互相发射和接受信号,对SF/RPC材料的声发射波速进行了测定。同时与普通混凝土（NC）材料声发射特性进行了对比分析研究。结果表明：相同荷载作用下SF/RPC的撞击累计数远大于NC梁,声发射活跃性高于NC材料;预应力SF/RPC梁的声发射特征参数与NC梁有着明显区别,SF/RPC短上升时间段（<30 μs）的声发射撞击平均比例为64.2%,明显高于NC的比例51.2%;SF/RPC材料波形频域特性也与NC材料明显不同;荷载作用前,SF/RPC材料内平均波速为4 342.8 mm/s,NC材料内平均波速为2 337.7 mm/s。通过引入Gutenberg-Richter理论,计算了声发射信号损伤参数（b_I）,对预应力SF/RPC损伤开裂过程与b_I值的关系进行了分析研究。本研究结果为有效识别SF/RPC材料的声发射特性提供试验依据。     

Optimization of hot extrusion process for AZ61 magnesium alloy carriers

This study applies fuzzy-base Taguchi method to investigate the optimal process parameters of the multiple performance characteristics index (MPCI) for the hot extrusion process of AZ61 magnesium alloy products. Flattening strength, fracture strength and extrusion load are taken as the input data of MPCI. Since the optimal combination of process parameters for Taguchi method varies with individual quality characteristic, the optimal combination of parameters for different quality characteristics may be contradictory to each other. In order to consider the larger-the-better quality characteristic of flattening strength and T-slot fracture strength values as well as the smaller-the-better quality characteristic of extrusion load, the fuzzy-base Taguchi method is used to analyze and to obtain the optimal combination of process parameters for the MPCI. First of all, orthogonal array is applied to arrange the experimental combination of extrusion process. The signal-to-noise (S/N) ratios of the three quality characteristics of flattening strength, T-slot fracture strength and extrusion load for the products acquired from experiments are calculated. The S/N ratio serves as the input variable of fuzzy control unit, whereas MPCI serves as a single output variable. The acquired MPCI is employed to analyze the optimal process parameters. In this study, an optimal combination of process parameters of AZ61 carrier for MPCI is obtained, and the verification experiments are conducted to prove the accuracy. Moreover, mechanical properties of AZ31 and AZ61 magnesium alloy carriers are tested for further comparison.     

Corrosion in Wet Gas Piping: Root Cause,Mitigation, and Neural Network Prediction Modeling

This paper discusses the root causes and operational mitigations of corrosion anomalies reported for an FPSO wet gas system, and crucially, proposes a neural network (NN) prediction model. The NN model involves ‘back-propagation’ processing of each nodal root cause and mitigation to obtain a value which when combined with a processing weight and then summed, provides an output value. This value is then used to further adjust the weights. Each weight correlates with the magnitude of influence on the overall corrosion rate. The ability to train the model (i.e., weight-adjustment during processing) makes it responsive and adaptable, such that when fresh data inputs are made in a ‘forward-propagation’ mode, into the large modeling database that has been developed (which includes a large number of susceptibility factors), significant increases in the accuracy of predicting corrosion rate and integrity behavior of the wet gas system can be achieved. The identified root causes and mitigations will be useful in further understanding the internal degradation mechanisms operating in wet gas systems in general.     

Application of the Taguchi analytical method for optimization of effective parameters of the chemical vapor deposition process controlling the production of nanotubes/nanobeads

Seven variable parameters of the chemical vapor deposition system have been optimized with the help of the Taguchi analytical method for getting a desired product, e.g., carbon nanotubes or carbon nanobeads. It is observed that almost all selected parameters influence the growth of carbon nanotubes. However, among them, the nature of precursor (racemic, R or Technical grade camphor) and the carrier gas (hydrogen, argon and mixture of argon/hydrogen) seem to be more important parameters affecting the growth of carbon nanotubes. Whereas, for the growth of nanobeads, out of seven parameters, only two, i.e., catalyst (powder of iron, cobalt, and nickel) and temperature (1023 K, 1123 K, and 1273 K), are the most influential parameters. Systematic defects or islands on the substrate surface enhance nucleation of novel carbon materials. Quantitative contributions of process parameters as well as optimum factor levels are obtained by performing analysis of variance (ANOVA) and analysis of mean (ANOM), respectively.     

Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance

This research applies agent-based modelling (ABM) to study volume flexibility in a dual resource constrained (DRC) assembly flow shop environment. The simulation experiment evaluated system and human effects of varying DRC system staffing levels according to design (i.e., workforce, distance and buffer capacity), sensitivity (i.e. coefficient of variation) and operating (i.e. when rule and where rule) factors. Results showed that the rule by which workers are assigned to workstations affects WIP and flow time performances more than production rates. Furthermore per-worker productivity was found to increase, compared to the fully staffed system, particularly where the downstream movement rule was applied. Using the downstream rule when changing stations after completing current tasks reduced flow time (?15%) and WIP (?10%). If another where rule is chosen then it may be preferable for workers to move only after completing all jobs in the station (decentralised rule). For utilisation rates and mean hourly switching of work (human effects), the model shows complex relationships depending on almost all evaluated factors. The novel ABM approach used here enabled the evaluation of emergent system behaviours and showed potential to help firms understand both human and performance effects of operational choices in efforts to achieve volume flexibility.