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In the past few years, several capability indices have been developed for evaluating the performance of multivariate manufacturing processes under the normality assumption. However, this assumption may not be true in most practical situations. Thus, the purpose of this paper is to develop new capability indices for evaluating the performance of multivariate processes subject to non-normal distributions.

In this paper, the authors propose three non-normal multivariate process capability indices (MPCIs) RNMC _p , RNMC _pm and RNMC _pu by relieving the normality assumption. Using the two normal MPCIs proposed by Pan and Lee, a weighted standard deviation method (WSD) is used to modify the NMC _p and NMC _pm indices for the-nominal-the-best case. Then the WSD method is applied to modify the multivariate ND index established by Niverthi and Dey for the-smaller-the-better case.

A simulation study compares the performance of the various multivariate indices. Simulation results show that the actual non-conforming rates can be correctly reflected by the proposed capability indices. The numerical example further demonstrates that the actual quality performance of a non-normal multivariate process can properly reflected by the proposed capability indices.

Process capability index is an important SPC tool for measuring the process performance. If the non-normal process data are mistreated as a normal one, it will result in an improper decision and thereby lead to an unnecessary quality loss. The new indices can provide practicing managers and engineers with a better decision-making tool for correctly measuring the performance for any multivariate process or environmental system.

Once the existing multivariate quality/environmental problems and their Key Performance Indicators are identified, one may apply the new capability indices to evaluate the performance of various multivariate processes subject to non-normal distributions.

The Taguchi method is the conventional approach used in off‐line quality control. However, most previous Taguchi method applications have dealt only with a single‐response problem. The multi‐response problem has received only limited attention. Proposes an effective procedure on the basis of the quality loss of each response so as to achieve the optimization on multi‐response problems in the Taguchi method. The procedure is a universal approach which can simultaneously deal with continuous and discrete data. Evaluates a plasma‐enhanced chemical vapour deposition (PECVD) process experiment and a case study, indicating that the proposed procedure yields a satisfactory result.

The purpose of this paper is to explore the relationship between multivariate process capability indices and loss functions for both nominal‐the‐best and smaller‐the‐better cases, so the likelihood and consequences resulting from the nonconforming of a manufacturing process or an environmental system can be evaluated simultaneously.

In this paper, the authors present a new approach of correlated risk assessment by linking the multiple process capability indices and loss functions, in which the multivariate process capability indices and multivariate loss functions describe the likelihood and consequences as a result of nonconformities in multivariate manufacturing or environmental system, respectively. Then, the associated relationship equations are developed using multivariate methods. Moreover, a step‐by‐step procedure is provided to facilitate the implementation of the correlated risk assessment.

Given the multivariate process capability indices, the authors show that the expected loss can be estimated by developed relationship equations and two numerical examples are also given, to demonstrate how the correlated manufacturing and environmental risks can be properly assessed by linking the multivariate process capability indices and multivariate loss function.

The risk information of likelihood and expected loss, classified in the four planning zones of a strategic planning matrix, provides practising managers and engineers with a decision‐making tool for prioritizing their quality improvement projects when conducting risk assessment for any multivariate process or environmental system.

Once the existing quality/environmental problems and their Key Performance Indicators are identified, one may conduct risk assessment by applying the relationship equations to evaluate the impact of correlated risk on manufacturing processes or multiple environmental emissions inside company; this can lead to the direction of continuous improvement for any industry.

The performance of technical institutions in India is reflected through the level of campus placements. It is vital for them to have efficient, effective and robust placement policies. Selective assembly is a technique used in manufacturing industry in improving the quality of assemblies from relatively low-quality components. The purpose of this paper is to develop a methodology using selective assembly approach to improve the quality of placements of technical institutions in India.

The paper presents a conceptual model for campus placement process by integrating Selective Assembly, Taguchi’s quality loss function (QLF) and analytic network process (ANP). The data used in the study was taken through surveys and expert opinions. In this paper, for “Selective Assembly” the terminology, “Selective Recruitment” has been used at appropriate places in the context of technical education.

Selective matching of students’ skills done through ANP minimizes the total loss in terms of opportunity cost. Taguchi’s QLF concept was used to evaluate the total loss, in terms of opportunity cost, and to validate the superiority of selective assembly technique over the conventional selection process.

The paper outlines measures that can help policy makers to successfully implement the suggested methodology to improve the quality of placements.

The application of selective recruitment in the campus placement process is a unique feature in the area of technical education in India. The role of ANP in selective recruitment and assessment of the process through Taguchi’s QLF, illustrate the importance of integrated approach adopted in the selection process.

To investigate laminated object manufacturing (LOM) process quality, using a design of experiments approach.

The quality characteristics measured were in‐plane dimensional accuracy, actual layer thickness (ALT), and mean time per layer. The process parameters tested were nominal layer thickness (LT), heater temperature (HT), platform retract (PR), heater speed (HS), laser speed (LS), feeder speed (FS) and platform speed (PS). A typical test part has been used, and matrix experiments were carried out based on Taguchi design. Optimal process parameter values were identified and finally, additive and regression models were applied to the experimental results and tested using evaluation experiments.

The statistical analysis of the experimental results shows that error in X direction was higher than error in Y direction. Dimensional accuracy in X direction depends mainly on the HS (89 percent) and HT (5 percent), and in Y direction on HS (50 percent), LT (31 percent), LS (9 percent), PS (6 percent), and HT (3 percent). On the other hand, ALT depends mainly on the nominal ALT (96 percent), HS (2 percent), HT (1 percent), and PR (1 percent). Finally, mean time per layer depends mainly on HS (59 percent), LS (17 percent), FS (17 percent), and PS (4 percent).

Future work should involve extensive matrix experiments using parameters such as dimensions of test part (X_max, Y_max, Z_max), hatch spacing in X and Y directions, and delay time between sequential layers.

Using the extracted models, the quality of LOM parts can be predicted and appropriate process parameter values selected. This means minimization of post processing time, easier disengagement between supporting frame and part, easier decubing, process optimization, less finishing and satisfactory final LOM parts or tools. Also, ALT prediction and mean time per layer analysis could be used to improve LOM build time predictions.

The above analysis is useful for LOM users when predictions of part quality, paper consumption, and build time are needed. This methodology could be easily applied to different materials and initial conditions for optimisation of other LOM‐type processes.

The purpose of this research is to provide a new loss function‐based risk assessment method so the likelihood and consequence resulting from the failure of a manufacturing or environmental system can be evaluated simultaneously.

Instead of using risk matrices of the occurrence and consequence separately for evaluating manufacturing and environmental risks, an integrated approach by exploring the relationship between process capability indices: C_p, C_pk and C_pm, and three different loss functions: Taguchi's loss function; Inverted normal loss function (INLF); and Revised inverted normal loss function (RINLF) is proposed.

The new method of quantitative risk assessment linking the likelihood and expected loss of failure is illustrated by two numeric examples. The results suggest that the revised inverted normal loss function (RINLF) be used in assessing manufacturing and environmental risks.

It gives decision‐makers a concrete tool to assess the likelihood and consequence of their processes. Linking the process capability indices and loss functions is particularly promising, as this provides a useful risk assessment tool for practitioners who want to reduce hazardous waste and manufacturing losses from their facilities.

The manufacturing and environmental risks are determined by paring the process capability indices and loss function. From the loss function‐based estimation, one can quantify the consequence of a manufacturing loss and get the severity rating in an objective way.

This paper discusses the optimization of the process parameters for the hybrid‐layered manufacturing (HLM) process during its weld layer deposition with subsequent surface machining in attaining the desired accuracy and contour profile of the deposited weld layer thickness.

The HLM process integrates the synergic metal inert gas (MIG) – metal active gas (MAG) welding process for depositing the metal layer of a desired slice thickness and perform the computer numerical control (CNC) machining process on the deposited layer to enhance both the surface quality and dimensional accuracy of the deposited layer. For the HLM process the weld bead geometry plays a vital role in determination of the layer thickness, surface quality, build time, heat input into the deposited layer and the hardness attained by the prototype. A feasible weld bead width and heights are to be formulated for the exterior contour weld path deposition and for the interior weld cladding. Thus, Taguchi methodology was employed with minimum number of trails as compared with classical statistical experiments. This study systematically reveals the complex cause‐effect relationships between design parameters and performance.

Statistical design of experiments using orthogonal arrays and signal‐to‐noise (S/N) ratios are performed to constitute the core of the robust design procedure. Experimental confirmations of the performance characteristic using the derived optimal levels of process parameters are provided to confirm the effectiveness of this approach.

The welding parameters such as current, voltage, arc length, wire feed rates, wire stick‐out distance, shielding gas, filler wire diameter, weld speed, etc. will influence on the deposited weld bead geometry. Further investigations are to be carried out during adaptive layer deposition on the induced thermal stresses and its influence on the hardness of the deposited weld layer.

This paper describes a low cost direct rapid tooling process, HLM. This unique methodology would reduce the cost and time to make molds and dies that are used in batch production.

Recent years have seen mounting interest in measuring process performance in the manufacturing industry. Analysis of process capability indices allows a production department to trace and improve a poor process to enhance quality and satisfy customers. Process capability analysis can also serve as an important reference in determining strategies to improve global product quality. Since C_p and C_pk failed to account for process centering, index C_pm was developed, which considers process centering and is suitable for processes of the nominal‐the‐best type. Other indices like C_pu and C_pl also exist, and are used for unilateral specification. Chou developed a procedure using estimators of C_p, C_pu and C_pl to allow practitioners to determine whether two processes are equally capable. For bilateral specification processes, index C_p fails to measure process yield and process centering, and thus the index C_pm is used to develop a similar procedure to help practitioners determine whether or not two processes are equally capable. Naturally, decisions made using the procedure to select the better supplier are more reliable than decisions made using other methods.

Assessing image quality is a difficult task. Different demands need distinct criteria, so it is not realistic to decide which contrast enhancement method is better only through one criterion. The main purpose is to propose an efficient scheme to effectively evaluate image quality. Furthermore, the idea can be applied in other fields.

To objectively and quantitatively assess image quality, the authors integrate four criteria into one composite criterion and use it to evaluate seven existing contrast enhancement methods. The mechanism of integration is through a newly proposed way of computing a grey relational grade (GRGd), called the consistent grey relational grade (CGRGd).

In this paper, the authors propose the CGRGd, which is more efficient and consistent than other existing GRGds. When applied to image quality evaluation, the proposed CGRGd can effectively choose the best method than others. The results also indicate that the proposed CGRGd combined with appropriate criteria can be widely used in the field of multiple criteria.

The proposed CGRGd is a new approach to the problem of multi-criteria evaluation, and its application to the evaluation of image quality is a novel idea. For readers interested in the field of multi-criteria decision-making, the CGRGd provides an efficient and effective alternative.

The process capability indices have been widely used to measure process capability and performance. In this paper, we proposed a new process capability index which is based on an actual dollar loss by defects. The new index is similar to the Taguchi’s loss function and fully incorporates the distribution of quality attribute in a process. The strength of the index is to apply itself to non‐normal or asymmetric distributions. Numerical examples were presented to show superiority of the new index against Cp, Cpk, and Cpm which are the most widely used process capability indices.