Exploitation of the advanced manufacturing machine tool evaluation model under objective-grey information: a knowledge-based cluster with the grey relational analysis approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zitong He ◽  
Xiaolin Ma ◽  
Jie Luo ◽  
Anoop Kumar Sahu ◽  
Atul kumar Sahu ◽  
...  

PurposeAdvanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.Design/methodology/approachThe authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.FindingsThe presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.Originality/valueThe DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaohui Guo ◽  
Atul kumar Sahu ◽  
Nitin Kumar Sahu ◽  
Anoop Kumar Sahu

PurposeIn the presented research work, the authors fabricated the multiple MS plate (Grade: IS 2062) specimens and applied a novel integrated computational TRIFMRG approach with grey relational analysis (GRA) toward solving weld bead optimization problem in MIG welding procedure. The objective of research is to determine the optimum setting between MIG welding input process parameters, e.g. welding current, open circuit voltage and thickness of plate in attaining high tensile strength with weld bead geometry quality characteristics, e.g. bead width, reinforcement, penetration and dilution in investigating define MS specimens.Design/methodology/approachThe Taguchi's L9 orthogonal array (OA) design is respected to conduct the experiments on MS plate specimens to attain output objectives. Later, the evaluated multiple output objectives are transformed into single response by applying a novel integrated computational TRIFMRG approach with GRA. Thereafter, the outset of signal-to-noise ratio (S/N ratio) accompanied by ANOVA (Analysis of variance) is explored to optimize objective function.FindingsThe computed results are confirmed by conducting the experiments on same identical specimens. The outcome of the confirmation tests yielded an improvement of 0.24454, 0.372486, 0.686635 and 0.4106846 in grey relational grade (GRG), overall ratio index, reference grade and full multiplicative index, respectively, after validating the results.Originality/valueIn the presented work, the authors constructed a novel integrated computational TRIFMRG approach via clustering GRA, overall ratio index (ORI), full multiplicative index (FMI) with GRA-reference grade (RG) and tested as well as applied with Taguchi concept to attain objective of the research work.


2021 ◽  
Vol 11 (5) ◽  
pp. 2344
Author(s):  
Srikanth Vuppala ◽  
Riyaaz Uddien Shaik ◽  
Marco Stoller

Olive oil production is one of the important industrial sectors within the agro-food framework of the Mediterranean region, economically important to the people working in this sector, although there is also a threat to the environment due to residues. The main wastes of the olive oil extraction process are olive mill wastewater (OMW) and olive husks which also require proper treatment before dismissal. In this research work, the main goal is to introduce grey relational analysis, a technique for multi-response optimization, to the coagulation and flocculation process of OMW to select the optimum coagulant dosage. The coagulation and flocculation process was carried out by adding aluminum sulfate (Alum) to the waste stream in different dosages, starting from 100 to 2000 mg/L. In previous research work, optimization of this process on OMW was briefly discussed, but there is no literature available that reports the optimal coagulant dosage verified through the grey relational analysis method; therefore, this method was applied for selecting the best operating conditions for lowering a combination of multi-responses such as chemical oxygen demand (COD), total organic carbon (TOC), total phenols and turbidity. From the analysis, the 600 mg/L coagulant dosage appears to be top ranked, which obtained a higher grey relational grade. The implementation of statistical techniques in OMW treatment can enhance the efficiency of this process, which in turn supports the preparation of waste streams for further purification processes in a sustainable way.


2020 ◽  
Vol 44 (4) ◽  
pp. 239-249
Author(s):  
Pravin Pawar ◽  
Amaresh Kumar ◽  
Raj Ballav

The electrochemical discharge machining process (ECDM) is a hybrid advanced technology integrated with electrochemical and electro-discharge processes has used for the manufacturing of non-conducting along with conducting materials. The silicon carbide is non-conducting material which has widely used in various fields such as automobile, aviation, medical, nuclear reactor, and missile. The machining of silicon carbide is a challenging task by using non-conventional along with conventional machining processes due to its physical properties. The current research work shows the machining of Silicon carbide material by using fabricated ECDM machine setup with gunmetal tool material. The Taguchi L27 orthogonal array technique is applied for experimental work. The grey relational analysis optimization is applied for the investigation of optimum input factors for better output responses. The input process factors like electrolyte concentration, applied voltage, and rotation of tool and outcome results such as machined depth and the diameter of hole were checked after drilling of silicon carbide material. The experimental results indicate the electrolyte concentration is the leading factor for diameter of hole and depth of machined hole subsequent to voltage and tool rotation.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lan Xu ◽  
Yu Zhang

PurposeSmart senior care industry in China currently faces a series of practical difficulties such as an imbalance in the demand and supply structure, service products unable to cater to the actual needs of the elderly and a low degree of marketization. This study therefore proposes using grey relational analysis and the Fuzzy-quality function development (QFD) quality improvement method to help solve these problems.Design/methodology/approachThe proposed method converts the fuzzy requirements of the elderly into the technical characteristics of technologically augmented senior care service products. It then, uses the QFD relationship matrix, combined with grey relational analysis, to analyze the relationship between the needs of elderly and the converted technical characteristics, and subsequently identifies key technical characteristics.FindingsResults show that an improvement in the smart senior care service platform according to the differences of the elderly's preferences can significantly improve users' satisfaction with the service in addition to enhancing market competitiveness of the technologically assisted senior care service products.Originality/valueA novel method to improve the need of smart senior care is proposed by considering age difference. The proposed grey relational analysis and Fuzzy-QFD quality improvement method can help improve the service quality of the smart senior care service platform.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.


2014 ◽  
Vol 4 (2) ◽  
pp. 232-249
Author(s):  
Yow-jyy Joyce Lee ◽  
Lawrence W. Lan

Purpose – The purpose of this paper is to propose a formative assessment framework to expose individual student's cognitive learning difficulties in English public speaking. The paper aims to provide student feedback and information during the teaching and learning process. A grey student-construct (S-C) chart is developed to represent the students’ cognitive mapping of the speech difficulties in relation to their overall speech conceptualization. This grey S-C chart can facilitate the instructors to ameliorate the classroom teaching and learning performance in English public speaking. Design/methodology/approach – In total, 26 students in a class of English Speech and Rhetoric participate in the experiment – each student views the online video segments of a great speaker's speech, and then decides what segments would best support the speaking skill constructs and also reflects on his/her own difficulties in the same constructs. The grey relational analysis (GRA) method is used to analyze the empirical data. The individual student's construct localization grey relation grade values are calculated to rank the grey relation for both students and constructs. Accordingly, a grey S-C matrix is constructed and a grey S-C chart can thus be developed. Findings – The grey S-C chart manifestly displays the cognitive difficulties in sequences of both students and constructs. Practical implications – According to the grey S-C chart, the instructors may modify teaching strategies to enhance the overall classroom performance. The students may adjust learning strategies to eliminate their specific difficulties. Offering individualized advanced and remedial practices to those largely deviating from the norm is also possible. Originality/value – The study is the first of its kind to apply the GRA method to expose individual student's cognitive learning difficulties in English public speaking. The grey S-C chart is novel in education literature, which can reveal individual student's learning difficulty patterns.


2017 ◽  
Vol 7 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Engin Duran ◽  
Burcu Uzgur Duran ◽  
Diyar Akay ◽  
Fatih Emre Boran

Purpose It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators. Design/methodology/approach To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis. Findings The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings. Practical implications These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate. Originality/value There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.


2019 ◽  
Vol 969 ◽  
pp. 678-684 ◽  
Author(s):  
Sarat Kumar Sahoo ◽  
A. Bara ◽  
A.K. Sahu ◽  
S.S. Mahapatra ◽  
D.S. Kiran ◽  
...  

In this research work, an efficient optimization technique, grey relational analysis (GRA) has been used to for optimization of wire electrical discharge machining process of Titanium (grade 2) by considering multiple output parameters. This technique combines Taguchi’s orthogonal array with grey relational analysis for the design of the experiment. The central focus of this research is to achieve improved Kerf width, surface roughness and cutting speed. GRA method is implemented to decide the best input parameter that optimizes the output parameters. This study has been conducted by applying Taguchi’s L9 orthogonal array. Each experiment has been conducted in altered conditions of input variables. For the optimization of multiple criteria, GRA is suggested as a suitable technique for the optimization of complex interrelationships between multi-performance characteristics. By analysis of variance (ANOVA) it is found that the percentage of contribution of peak current on overall performance is maximum i.e.73.1%.


2020 ◽  
Vol 16 (5) ◽  
pp. 937-949
Author(s):  
Alagappan K M ◽  
Vijayaraghavan S ◽  
Jenarthanan M P ◽  
Giridharan R

PurposeThe purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.Design/methodology/approachThe contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.FindingsThe optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.Originality/valueOptimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.


2017 ◽  
Vol 24 (3) ◽  
pp. 651-665 ◽  
Author(s):  
Farshad Faezy Razi ◽  
Seyed Hooman Shariat

Purpose The purpose of this paper is twofold: the selection of project portfolios through hybrid artificial neural network algorithms, feature selection based on grey relational analysis, decision tree and regression; and the identification of the features affecting project portfolio selection using the artificial neural network algorithm, decision tree and regression. The authors also aim to classify the available options using the decision tree algorithm. Design/methodology/approach In order to achieve the research goals, a project-oriented organization was selected and studied. In all, 49 project management indicators were chosen from A Guide to the Project Management Body of Knowledge (PMBOK Guide), and the most important indicators were identified using a feature selection algorithm and decision tree. After the extraction of rules, decision rule-based multi-criteria decision making matrices were produced. Each matrix was ranked through grey relational analysis, similarity to ideal solution method and multi-criteria optimization. Finally, a model for choosing the best ranking method was designed and implemented using the genetic algorithm. To analyze the responses, stability of the classes was investigated. Findings The results showed that projects ranked based on neural network weights by the grey relational analysis method prove to be better options for the selection of a project portfolio. The process of identification of the features affecting project portfolio selection resulted in the following factors: scope management, project charter, project management plan, stakeholders and risk. Originality/value This study presents the most effective features affecting project portfolio selection which is highly impressive in organizational decision making and must be considered seriously. Deploying sensitivity analysis, which is an innovation in such studies, played a constructive role in examining the accuracy and reliability of the proposed models, and it can be firmly argued that the results have had an important role in validating the findings of this study.


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