A new algorithm and multi-response Taguchi method to solve line balancing problem in an automotive industry

One of the most important issues in an assembly line balancing problem is to control a flow of production and manufacturing to provide continuous flow to balance the production line. For this purpose, a line balancing problem was considered for a special assembly line in an automotive factory. A new algorithm was required to deal with balancing an assembly line which consisted of the same job which must be performed by more than one worker at the same time. In this way, the new algorithm was expected to be effective in such a case that jobs were simultaneously completed in a parallel way. In order to measure effectiveness of the proposed algorithm, performance criteria were identified as total number of assembly station, total number of workers, and line productivity. As a result of the application of the proposed algorithm with taking into consideration factors such as cycle time, an allowable number of workers in an assembly station, and an allowable idle time of a worker, alternative solutions were determined in order to measure these criteria. However, these alternative solutions do not give any information about which of the solutions provide not only minimization of the number of assembly station and number of workers on the line but also maximize the line productivity at the same time. Hereby, a multi-response Taguchi method was applied in order to investigate levels of factors which directly affected system performance criteria.     

Simultaneous Optimisation of Multiple Quality Characteristics in Manufacturing Processes Using Taguchi's Quality Loss Function

Taguchi methods have proved to be successful over the last fifteen years or so for the improvement of product quality and process performance. Most Taguchi experiments are concerned with the optimisation of a single quality characteristic. Optimisation of multiple quality characteristics in manufacturing processes is not common and has received very little attention among the Taguchi practitioners. Many engineers using Taguchi methods have employed pure engineering judgement when dealing with multiple quality characteristics in manufacturing process optimisation. This approach is very subjective and therefore always brings an element of uncertainty to the decision-making process. This paper presents an alternative approach for tackling such optimisation problems using Taguchi’s quality loss function analysis. The paper also presents a case study to illustrate the potential of the proposed methodology.     

Erosion Response of Thixoformed A356-5TiB2 in situ Composite Using Taguchi's Experimental Design

The present article describes the application of Taguchi's experimental design methodology to investigate the erosion wear behavior of in situ-formed A356-5TiB₂ composite subjected to thixoforming. The effects of process parameters—such as impact velocity, erodent temperature, erodent size, standoff distance, and impingement angle—on the erosion rate have been analyzed. The results indicated that impact velocity is the most significant factor and accounts for 42.31% of the total effect on the erosion rate of the thixoformed A356-5TiB₂ composite. It is found that material loss during erosive wear is primarily due to microploughing (i.e., abrasive type) and microfracture (i.e., impact type). The erosion rate of thixoformed A356-5TiB₂ in situ composite was found to be 48.82 mg/kg, which is nearly 44% lower than that of as-cast alloy.     

CAE process to simulate and optimise engine noise and vibration

The vibratory and acoustic behaviour of the internal combustion engine is a highly complex one, consisting of many components that are subject to loads that vary greatly in magnitude and which operate at wide range of speed. CAE tools development will lead to a significant reduction in the duration of the development period for engine as well as ensure a dramatic increase in product quality. This paper presents today's state-of-the-art CAE capabilities in the simulation of the dynamic and acoustic behaviour of engine and focuses on the relative merits of modification and full-scale structural/acoustic optimisation of engine, together with the creation of new low-noise designs. Modern CAE tools allow the analysis, assessment and acoustic optimisation of the engine.     

A simple approach to solving multi-response quality characteristic problems in CMOS ion implantation

This study develops a systematic algorithm for optimizing the multi-response quality characteristics in complementary metal-oxide semiconductor (CMOS) ion implantation experiments in terms of overall product quality, by adopting the grey situation decision-making method. Finally, the feasibility and effectiveness of the proposed algorithm is demonstrated by such an experiment.     

利用改进的遗传算法解决全局寻优问题

寻找函数的全局最优解是一个很常见的工程应用问题,简单遗传算法是解决此类问题的有力工具.但由于简单遗传算法具有中全局收敛能力差和收敛速度慢的缺点.本文基于对遗传算子的优化,提出一种混合分类选择和定向变异的改进遗传算法来解决全局寻优问题.经仿真结果表明,该算法具有较强的全局收敛能力和较快的收敛速度.     

两阶段法求解1.5维切割问题

切割问题亦称为下料问题.多维切割问题是机加工、木材加工和造纸等行业在生产中经常遇见的实际问题.1.5维切割问题是介于一维和二维切割问题之间的一类问题.针对1.5维切割问题的特殊性,采用两阶段方法进行求解.第一阶段是将1.5维切割问题转化为一维切割问题,第二阶段首先利用一种启发式算法得到一组初始解,然后使用粒子群算法对初始解进行优化,得最终解.     

Optimization of multi-response processes using the VIKOR method

Design of experiments and Taguchi methods are extensively adopted as off-line quality improvement techniques in industry. However, these methods were developed to optimize single-response processes. In many situations, multiple responses must be optimized simultaneously, since some product designs, especially in the integrated circuit industry, are becoming increasingly complex to meet customers’ demands. Although several procedures for optimizing multi-response processes have been developed in recent years, the associated quality measurement indices do not consider variations in the relative quality losses of multiple responses. These procedures may therefore result in an optimization in which quality losses associated with a few responses are very small but those associated with others are very large, even if the overall average quality loss is small. Such an optimization with a large variation of quality losses among the responses is usually unacceptable to engineers. Accordingly, this study employs the VIKOR method, which is a compromise ranking method used for multicriteria decision making (MCDM), to optimize the multi-response process. The proposed method considers both the mean and the variation of quality losses associated with several multiple responses, and ensures a small variation in quality losses among the responses, along with a small overall average loss. Two case studies of plasma-enhanced chemical vapor deposition and copper chemical mechanical polishing demonstrate the effectiveness of the proposed method.     

A genetic algorithm to optimise the component placement process in PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.     

田口校准系统损失函数的改进及其应用

测量系统的校准周期是计量领域长期研究的问题.实践中测量仪器的校准周期由各生产厂家和研究机构根据具体情况自行规定.田口博士通过建立校准系统损失函数确定了最佳校准周期和最佳调整界限.讨论了田口博士的质量损失函数和校准系统损失函数,在分析了田口校准系统损失函数不足的基础上,给出了相应的改进后的校准系统损失函数,推导出基于改进后的校准系统损失函数的最佳校准周期和最佳调整界限,最后通过实例验证了改进后的校准系统损失函数良好的经济性.     

利用双位置反馈功能解决机械传动中的刚性不足问题

目前,我国生产的数控机床,一般都采用直接测量反馈装置,利用编码器、光栅尺和圆光栅等器件作为反馈元件,进行全闭环控制,以此来提高机床的定位精度.但由于零部件的制造加工及装配等各方面的因素影响,机械传动的刚性都不是很理想.所以在机床调整初期,加上编码器、光栅尺和圆光栅等的检测反馈,机床反而会出现抖动、报警和运行不稳定等现象.有些机床在运行一段时间后,由于机床各运动部件发生摩擦和变形等多方原因,有时也会发生抖动现象.这种情况一般在断开反馈功能后,抖动等现象会消失,机床运行稳定.     

Simultaneous optimization of multi-response problems in the Taguchi method using genetic algorithm

The optimization of multiple responses (or performance characteristics) has received increasing attention over the last few years in many manufacturing organizations. Most previous applications of the Taguchi method only emphasize the single-response problems, while the multi-response problems have received relatively little attention. Many Taguchi practitioners have employed past experience and engineering knowledge or judgement when dealing with multiple responses. The approach presented in this paper takes advantage of both the Taguchi method and genetic algorithm, which forms a robust and practical methodology in tackling multiple response optimization problems. The paper also presents a case study to illustrate the potential of this powerful integrated approach for tackling multiple response optimization problems. The variance analysis is also an integral part of the study, which identifies the most critical and statistically significant parameters.     

Comparison of performances of five prospective approaches for the multi-response optimization

The Taguchi method of experimental design is widely used for optimization of process performance. However, this method has been developed to optimize single-response processes. But, in many situations, the engineers are required to determine the process settings that can simultaneously optimize multiple responses. In the recent past, researchers have proposed several systematic procedures for multi-response optimization. Most of these methods use complicated statistical/mathematical models and are, therefore, not easily comprehendible to the engineers who do not have a strong background in mathematics. Only a few methods, e.g. weighted signal-to-noise (WSN) ratio, Grey relational analysis, multiple-response signal-to-noise ratio, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian), and weighted principal component methods, use relatively simpler procedures. In this paper, the computational procedures for these five methods are standardized. Three sets of experimental data are analyzed using these standardized procedures and the predicted optimization performances of the five methods are compared. The results show that no method can give better optimization than the WSN method.     

A study on the performance of some multi-response optimisation methods for WEDM processes

Wire electrical discharge machining (WEDM) processes are having several performance measures which are affected by different process parameters. In the recent past, researchers have attempted several systematic procedures for optimising the multiple responses of WEDM processes. However, most of these approaches use complex statistical/mathematical tools and are, therefore, impractical for application by the engineers who may not have a strong background in mathematics. Only a few methods, e.g., grey relational analysis and multiple response signal-to-noise ratio approaches use relatively simpler computational procedures. On the other hand, the computational procedures for the weighted signal-to-noise (WSN) ratio and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian) methods are also quite simpler and, therefore, can easily be implemented by the engineers. However, an engineer needs to select the method that can give the best optimisation performance for the process. In this paper, the computational requirements for these four multi-response optimisation methods are standardised. Two sets of experimental data on WEDM processes are analysed using these standardised multi-response optimisation methods, and their relative performances are then compared. The results show that no method can lead to better optimisation than the WSN ratio method.     

Quality management research by considering multi-response problems in the Taguchi method – a review

Off-line quality control is considered to be an effective approach to improve product quality at a relatively low cost. The Taguchi method is one of the conventional approaches for this purpose. Through this approach, engineers can determine a feasible combination of design parameters such that the variability of a product’s response can be reduced and the mean is close to the desired target. Most previous applications of the Taguchi method only emphasize single-response problems, while the multi-response problems have received relatively little attention. However, several correlated quality characteristics of a product are usually considered for product quality by a consumer. Though a lot of research is being done on this subject, there is ample scope for applying quality by design concepts, especially when dealing with multi-response variables. This paper presents a literature review on solving multi-response problems in the Taguchi method.     

A hybrid approach for multi-response optimization of non-conventional machining on AlSiCp MMC

In this study, investigation on machinability characteristic of aluminum silicon carbide composite on electrical discharge machine is carried out. The composites are prepared through powder metallurgy route. The influence of four machining parameters (discharge current, pulse duration, duty cycle, and flushing pressure) and two material parameters (weight fraction of silicon carbide in the composite and mesh size) on selected responses are studied. The responses considered, in this work, are material removal rate, tool wear rate, surface roughness and circularity. In actual machining application, it is desirable to find a parametric combination that leads to simultaneous optimization of all the responses. Classical Taguchi method can optimize a single response but not multiple responses. In order to simultaneously optimize multiple responses, a hybrid approach combining principal component analysis (PCA) and fuzzy inference system is coupled with Taguchi method. The influence of each parameter on the responses is established using analysis of variances (ANOVA) at 5% level of significance. It is found that pulse duration, duty cycle, discharge current and flushing pressure contribute significantly to the multiple performance characteristic index. The four responses at optimal parameter setting have been reported.     

基于粗糙集-田口质量观的失效模式与影响分析

针对目前失效模式与影响分析（FMEA）方法中对实际风险较大的失效模式的风险难以有效评估的问题,提出了一种基于粗糙集理论和质量损失函数的FMEA新方法。首先,在对潜在失效模式进行分析的基础上,通过专家系统构建失效模式风险评估矩阵模型;其次,以降低数据本身的主观性和模糊性为目标,基于粗糙集理论将风险评估矩阵模型转换成粗糙域矩阵模型;再次,根据求解的粗糙域矩阵,运用多元质量损失函数模型,对每一个失效模式的潜在损失进行求解,依据潜在损失的大小对失效模式风险进行排序。最后,以发动机装配过程为例,对其失效模式与影响进行分析,并将其分析结果与目前的FMEA方法比较,验证了所提出方法的合理性和有效性。     

Improving yarn quality through multi-response optimisation of electronic yarn clearer in winding machine

One of the essential post-spinning operations of yarn is winding. In winding machine, ring yarn (i.e. the yarn produced in ring frame) is passed through electronic yarn clearer (EYC) and wound into empty conical-shaped packages called cones. The purpose of EYC is to improve the yarn quality as much as possible by eliminating the various types of faults or irregularities, e.g. thin places, thick places and neps from the ring yarn. The process engineer in an Indian spinning mill was facing the problem of inaccurate detection of faults by the EYC, which led to higher number of winding breaks as well as yarn irregularities. Aiming to tackle the problem, Taguchi’s L₂₇ orthogonal array experimentation was carried out. The experimental data are analysed using weighted principal component (WPC) method and principal component analysis-based grey relational analysis that take care of correlation among multiple responses. The WPC method is found to give better optimisation. By using the optimal settings, sensitivity of the EYC to detection of faults increased and thus, yarn quality improved substantially.     

Modelling and multi-response optimization of hole sinking electrical discharge micromachining of titanium alloy thin sheet

Thin sheets of titanium alloys are widely used in aerospace and automotive industries for specific applications. The creation of micro holes with requisite hole quality in thin sheets of these alloys using energy of electric discharge is a challenging task for manufacturing engineers. Hole sinking electrical discharge micromachining (HS-EDMM) is one of the most promising micromachining processes to create symmetrical and non-symmetrical micro holes. The present paper is related to selection of optimum parameter settings for obtaining maximum material removal, minimum tool wear and minimum hole taper in HS-EDMM. In this paper an attempt has been made to develop an integrated model (ANN-GRA-PCA) of single hidden layer back propagation neural network (BPNN) for prediction and grey relational analysis (GRA) coupled with principal component analysis (PCA) hybrid optimization strategy with multiple responses of HSEDMM of Ti-6Al-4V. Experiments have been conducted to generate dataset for training and testing of the network where input parameters consist of gap voltage, capacitance of capacitor and the resulting performance parameters are represented by material removal rate (MRR), tool wear rate (TWR), and hole taper (T_a). The results indicate that the integrated model is capable to predict and optimize process performance with reasonable accuracy under varied operating conditions of HS-EDMM. The proposed approach would be extendable to other configurations of EDMM processes for different materials.     

The principal component analysis (PCA)-based approaches for multi-response optimization: some areas of concerns

Over the years, Taguchi method for process optimisation has become very popular among the engineers. However, Taguchi method focuses on the optimisation of a single-response variable only, whereas most of the modern manufacturing processes demand for simultaneous optimisation of multiple response variables, and some of these responses are often correlated. Several methods have been proposed in literature which aims at making the Taguchi method useful for solving multi-response optimisation problems too. However, only few of these methods take into account the possible correlations that may exist among the response variables. Among these, principal component analysis (PCA)-based approaches are quite popular among the practitioners. However, we find that the PCA-based approaches suffer from some weaknesses, e.g. problem due to using signal-to-noise ratios as input data, problem due to scaling of the input data, problem due to difference in PCA results given by different software. This article aims at drawing attention of the researchers/practitioners to these problem areas of the PCA-based approaches so that appropriate research initiatives can be taken up by the researchers/practitioners to overcome those weaknesses.