Application of fuzzy MOORA method in the design and fabrication of an automated hammering machine

2020 ◽  
Vol 18 (1) ◽  
pp. 37-49
Author(s):  
Ikuobase Emovon ◽  
Oghenenyerovwho Stephen Okpako ◽  
Edith Edjokpa
Keyword(s):  
Material Selection ◽  
Content Type ◽  
Performance Effectiveness ◽  
Alternative Materials ◽  
Fuzzy Gra ◽  
Optimal Material ◽  
Selection Methodology ◽  
Grey Relational ◽  
Moora Method ◽  
Fuzzy Moora

Purpose In most developing countries riveting, upset forging and punching operations among others are performed using manual hammering technique. The use of the manual method increases production time and reduces efficiency. The use of the manual approach is predominantly due to the high cost of imported automated hammering machines (AHM) which the majority of the end-users are incapable of acquiring. The purpose of this paper, therefore, is to produce an AHM that is affordable using an effective material selection methodology in the design and fabrication process. Design/methodology/approach The material selection methodology proposed is the fuzzy multi-objective optimisation on the basis of the ratio analysis (MOORA) method. The tool was used to evaluate and determine the optimum material for the major of the components of the AHM from amongst alternative materials while considering several decision criteria. A case study of the shaft was applied to demonstrate the suitability of the proposed technique. The AHM components design is then carried out and machine fabricated and tested to ascertain performance effectiveness. Findings The result of the fuzzy MOORA evaluation showed that alloy steel is the optimal material for the shaft. The fuzzy MOORA approach was compared with the fuzzy Vlsekriterijumska Optimizacija Ikompromisno Resenje (VIKOR) and fuzzy grey relational analysis (GRA) methods to validate the proposed method. The fuzzy MOORA method produces completely the same result with the fuzzy VIKOR and fuzzy GRA methods. The machine was then designed, constructed and tested and found to be effective for the purpose of the design. Originality/value This is significant as no such study has been published by any other researcher to the best of our knowledge in this area.

scholarly journals Material Selection of Green Design Processes for Car Body via considering Environment Property

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Yongfeng Pu ◽  
Fangwu Ma ◽  
Lu Han ◽  
Guowang Wang
Keyword(s):  
Material Selection ◽  
Low Carbon ◽  
Analytic Hierarchy ◽  
Lightweight Material ◽  
Car Body ◽  
Vehicle Production ◽  
Reduce Emissions ◽  
Optimal Material ◽  
Grey Relational ◽  
Selection Of

Facing serious environmental degradation and its resulting of climate warming, how to conserve energy and reduce emissions becomes a serious issue for government supervisors and modern vehicle enterprises. Reducing the mass of a vehicle is one of the most effective ways to reduce emissions and improve fuel utilization, essential to persist the low-carbon and sustainable-development bases in industrial production processes. When it comes to the selection of lightweight material for a car body in the processes of vehicle production, it is essential to comprehensively evaluate multiple relevant attributes in order to select the optimal material from several alternatives. Thus, it can be seen as a multicriterion decision-making (MCDM) problem. However, it is difficult to consider both the uncertainty of the expert’s preference and the imprecision of the attribute estimate. Considering this, this paper uses the method integrating grey relational analysis (GRA) with analytic hierarchy process (AHP) to solve the problem of lightweight material selection for a car body. The AHP method is used to determine the weight of each attribute, and the GRA method is to select the optimal material among several alternatives. Finally, a case study is applied to verify the practicability of the proposed approach. The result shows that the proposed multicriterion decision method provides a precise and objective foundation for making decisions about the material selection issue.

Research on Material Selection with Multi-Attribute Decision Method and G1 Method

2014 ◽  
Vol 952 ◽  
pp. 20-24 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Topsis Method ◽  
Attribute Weight ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Optimal Material ◽  
Selection Of ◽  
Better Than

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Many factors (attributes) need to be considered in material selection process, and thus material selection problem is a multi-attribute decision making (MADM) problem. This paper proposes a new MADM method for material selection problem. G1 method does not need to test consistency of the judgment matrix. Thus it is better than AHP. In this paper, firstly, we use the G1 method to determine the attribute weight. Then TOPSIS method is used to calculate the closeness of the candidate materials with respect positive solution. A practical material selection case is used to demonstrate the effectiveness and feasibility of the proposed method.

The role of robotics in additive manufacturing: review of the AM processes and introduction of an intelligent system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
J. Norberto Pires ◽  
Amin S. Azar ◽  
Filipe Nogueira ◽  
Carlos Ye Zhu ◽  
Ricardo Branco ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Computer Aided Design ◽  
Intelligent System ◽  
Material Selection ◽  
High Strength Steels ◽  
Industrial Applications ◽  
Layer By Layer ◽  
Content Type ◽  
Functional Components

Purpose Additive manufacturing (AM) is a rapidly evolving manufacturing process, which refers to a set of technologies that add materials layer-by-layer to create functional components. AM technologies have received an enormous attention from both academia and industry, and they are being successfully used in various applications, such as rapid prototyping, tooling, direct manufacturing and repair, among others. AM does not necessarily imply building parts, as it also refers to innovation in materials, system and part designs, novel combination of properties and interplay between systems and materials. The most exciting features of AM are related to the development of radically new systems and materials that can be used in advanced products with the aim of reducing costs, manufacturing difficulties, weight, waste and energy consumption. It is essential to develop an advanced production system that assists the user through the process, from the computer-aided design model to functional components. The challenges faced in the research and development and operational phase of producing those parts include requiring the capacity to simulate and observe the building process and, more importantly, being able to introduce the production changes in a real-time fashion. This paper aims to review the role of robotics in various AM technologies to underline its importance, followed by an introduction of a novel and intelligent system for directed energy deposition (DED) technology. Design/methodology/approach AM presents intrinsic advantages when compared to the conventional processes. Nevertheless, its industrial integration remains as a challenge due to equipment and process complexities. DED technologies are among the most sophisticated concepts that have the potential of transforming the current material processing practices. Findings The objective of this paper is identifying the fundamental features of an intelligent DED platform, capable of handling the science and operational aspects of the advanced AM applications. Consequently, we introduce and discuss a novel robotic AM system, designed for processing metals and alloys such as aluminium alloys, high-strength steels, stainless steels, titanium alloys, magnesium alloys, nickel-based superalloys and other metallic alloys for various applications. A few demonstrators are presented and briefly discussed, to present the usefulness of the introduced system and underlying concept. The main design objective of the presented intelligent robotic AM system is to implement a design-and-produce strategy. This means that the system should allow the user to focus on the knowledge-based tasks, e.g. the tasks of designing the part, material selection, simulating the deposition process and anticipating the metallurgical properties of the final part, as the rest would be handled automatically. Research limitations/implications This paper reviews a few AM technologies, where robotics is a central part of the process, such as vat photopolymerization, material jetting, binder jetting, material extrusion, powder bed fusion, DED and sheet lamination. This paper aims to influence the development of robot-based AM systems for industrial applications such as part production, automotive, medical, aerospace and defence sectors. Originality/value The presented intelligent system is an original development that is designed and built by the co-authors J. Norberto Pires, Amin S. Azar and Trayana Tankova.

Corrosion of a chrome-moly pipe transporting sulfuric acid in a demineralization section: a failure analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Andres Marquez ◽  
Chris Maharaj
Keyword(s):  
Sulfuric Acid ◽  
Material Selection ◽  
Real Life ◽  
Main Idea ◽  
Petrochemical Plant ◽  
Material Loss ◽  
Corrosion Failure ◽  
Content Type ◽  
Characterization Methods ◽  
X Ray

Purpose The purpose of this study was to carry out an analysis of the corrosion failure on a chrome-moly pipeline transporting highly concentrated sulfuric acid in a demineralization section at a petrochemical plant, along with the feasibility of using inhibitors to minimize the corrosive effects of sulfuric acid. Design/methodology/approach X-ray fluorescence spectroscopy, high-resolution optical microscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy and accelerated corrosion experiments (ACE) were performed. Findings Erosion-corrosion failure was confirmed by the significant reduction in thickness of the internal surface of the material exposed to sulfuric acid, as well as the formation of an oxide scale/layer. ACE accurately predicted high material loss from exposure to sulfuric acid. Moreover, adding ascorbic acid as a corrosion inhibitor (even at low concentrations) was found to reduce the oxidation by more than 50% in the presence of sulfuric acid. Originality/value The main idea/purpose of this work relies on the analysis of recurrent real-life corrosion-attributed failures that are common in industry but are not properly addressed for a variety of reasons, poor management and lack of corrosion preventive strategies being the main ones. This study once again highlights readily available solutions/implementations that are capable of not only addressing technically the issue investigated but also, and as important, economically. By using microscopic imaging, reliable well-tested and widely used characterization methods, all combined with basic experiments and tests, the nature of the repetitive failure investigated was clearly demonstrated as well as readily available alternatives to minimize it in the short term. Nevertheless, implementing material selection techniques appropriately as effective corrosion prevention/control and cost-saving strategies must be enforced in any process.

Modeling of the machining parameters in turning of Al-5052/TiC/SiC composites: a statistical modeling approach using grey relational analysis (GRA) and response surface methodology (RSM)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Venkateshwar Reddy Pathapalli ◽  
Meenakshi Reddy Reddigari ◽  
Eswara Kumar Anna ◽  
P. Srinivasa Rao ◽  
D V. Ramana Reddy
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Content Type ◽  
Relational Analysis ◽  
Desirability Approach ◽  
Grey Relational ◽  
Grey Taguchi

PurposeMetal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.Design/methodology/approachThe combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.FindingsThe contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.Practical implicationsThe results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.Originality/valueThe originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.

Generative design and analysis of a double-wishbone suspension assembly: a methodology for developing constraint oriented solutions for optimum material distribution

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aayush Bhat ◽  
Vyom Gupta ◽  
Savitoj Singh Aulakh ◽  
Renold S. Elsen
Keyword(s):  
Design Methodology ◽  
Manufacturing Industry ◽  
Optimization Technique ◽  
Design Solution ◽  
Material Distribution ◽  
Generative Design ◽  
Trade Off ◽  
Content Type ◽  
Life Study ◽  
Optimal Material

Purpose The purpose of this paper is to implement the generative design as an optimization technique to achieve a reasonable trade-off between weight and reliability for the control arm plate of a double-wishbone suspension assembly of a Formula Student race car. Design/methodology/approach The generative design methodology is applied to develop a low-weight design alternative to a standard control arm plate design. A static stress simulation and a fatigue life study are developed to assess the response of the plate against the loading criteria and to ensure that the plate sustains the theoretically determined number of loading cycles. Findings The approach implemented provides a justifiable outcome for a weight-factor of safety trade-off. In addition to optimal material distribution, the generative design methodology provides several design outcomes, for different materials and fabrication techniques. This enables the selection of the best possible outcome for several structural requirements. Research limitations/implications This technique can be used for applications with pre-defined constraints, such as packaging and loading, usually observed in load-bearing components developed in the automotive and aerospace sectors of the manufacturing industry. Practical implications Using this technique can provide an alternative design solution to long periods spent in the design phase, because of its ability to generate several possible outcomes in just a fraction of time. Originality/value The proposed research provides a means of developing optimized designs and provides techniques in which the design developed and chosen can be structurally analyzed.

Selection of selective laser sintering materials for different applications

2015 ◽  
Vol 21 (6) ◽  
pp. 630-648 ◽  
Author(s):  
Sunil Kumar Tiwari ◽  
Sarang Pande ◽  
Sanat Agrawal ◽  
Santosh M. Bobade
Keyword(s):  
Process Parameters ◽  
High Performance ◽  
Material Selection ◽  
Selective Laser Sintering ◽  
Laser Sintering ◽  
Optimal Process ◽  
Content Type ◽  
Volume Production ◽  
High Performance Application ◽  
Selection Of

Purpose – The purpose of this paper is to propose and evaluate the selection of materials for the selective laser sintering (SLS) process, which is used for low-volume production in the engineering (e.g. light weight machines, architectural modelling, high performance application, manufacturing of fuel cell, etc.), medical and many others (e.g. art and hobbies, etc.) with a keen focus on meeting customer requirements. Design/methodology/approach – The work starts with understanding the optimal process parameters, an appropriate consolidation mechanism to control microstructure, and selection of appropriate materials satisfying the property requirement for specific application area that leads to optimization of materials. Findings – Fabricating the parts using optimal process parameters, appropriate consolidation mechanism and selecting the appropriate material considering the property requirement of applications can improve part characteristics, increase acceptability, sustainability, life cycle and reliability of the SLS-fabricated parts. Originality/value – The newly proposed material selection system based on properties requirement of applications has been proven, especially in cases where non-experts or student need to select SLS process materials according to the property requirement of applications. The selection of materials based on property requirement of application may be used by practitioners from not only the engineering field, medical field and many others like art and hobbies but also academics who wish to select materials of SLS process for different applications.

scholarly journals AN INTEGRATED INTELLIGENT SYSTEM FOR CONSTRUCTION INDUSTRY: A CASE STUDY OF RAISED FLOOR MATERIAL

2018 ◽  
Vol 24 (5) ◽  
pp. 1866-1884 ◽  
Author(s):  
Abdullah Cemil Ilce ◽  
Kadir Ozkaya
Keyword(s):  
Intelligent System ◽  
Material Selection ◽  
Valuable Insight ◽  
Analytic Hierarchy ◽  
Decision Methods ◽  
Practical Guidelines ◽  
Quantitative Analysis Method ◽  
Decision Group ◽  
Fuzzy Moora ◽  
Bidding Process

This paper aims to introduce a quantitative method to builders for the most appropriate material selections based on multiple attributes and integrate decision group member opinions throughout bidding process. In this respect, a new model used together with the Analytic Hierarchy Process (AHP) and fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), multi-criteria decision methods are proposed. In a real decision process, there are many uncertainties and ambiguities. In fact decision makers cannot always provide practical guidelines and especially precise judgments due to time limitations. The intelligent model proposed demonstrates that the AHP and fuzzy MOORA approach can not only be used easily to imitate the decision duration in the material selection but also the results obtained from this work provide contractors valuable insight into the material selection problem. At the same time, the quantitative analysis method based on the appropriately raised floor materials along the bidding process enables the builders to use their restricted resources more expeditiously and enhances considerably the possibility of winning agreement, as one of the most striking points deduced from the present study. In short, the model with AHP and fuzzy MOORA approaches can assist the builders to improve resolutions for the bidding.

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