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.

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.

Material Selection Decision-Making Method for Multi-material Lightweight Automotive Body Driven by Performance

2021 ◽  
pp. 146442072110556
Author(s):  
Dengfeng Wang ◽  
Shenhua Li
Keyword(s):  
Decision Making ◽  
Material Selection ◽  
The Body ◽  
Analytic Hierarchy ◽  
Weighting Method ◽  
Lightweight Material ◽  
Automotive Body ◽  
Selection Decision ◽  
Hierarchy Process ◽  
Selection Of

This work proposes a material selection decision-making method for multi-material lightweight body driven by performance to achieve that the right materials are used for the correct positions of the automotive body. The internal relationship between performance and mass, cross-sectional shape, wall thickness parameters, and material properties of a thin-walled structure is studied. The lightweight material indices driven by performance are then established. The lightweight material indices and material price are taken as the decision-making criteria for the material selection of automotive body components. A hybrid weighting method integrated with the analytic hierarchy process, fuzzy analytic hierarchy process, and quality function deployment is proposed. The difficulty of quantitatively evaluating the performance requirements of different components of the body is solved using the proposed weighting method combined with the numerical analytical results of the component performance under multiple operating conditions of the automotive body. Then, the weight of the decision-making criteria for material selection is calculated. Grey relational analysis is used to make multicriteria decision-making on a variety of candidate materials to select the best material for body components. After the lightweight material selection of the front longitudinal beam of the automotive body, the frontal collision safety performance of the body is effectively improved, and the mass of the front longitudinal beam is reduced by 45%. Material selection result of the front longitudinal beam indicates that the proposed material selection decision-making method can effectively achieve the fast material selection of components in different positions of the body.

Turning inserts the selection approach based on fuzzy comprehensive evaluation

2022 ◽  
pp. 095440622110653
Author(s):  
Yunliang Huo ◽  
Ji Xiong ◽  
Yu Ze ◽  
Sitao Chen ◽  
Zhixing Guo
Keyword(s):  
Intelligent System ◽  
Comprehensive Evaluation ◽  
Low Carbon Steel ◽  
Fuzzy Comprehensive Evaluation ◽  
Rake Angle ◽  
Low Carbon ◽  
Tool Selection ◽  
Nose Radius ◽  
Environmental Index ◽  
Analytic Hierarchy

Tool selection is a multi-criteria decision-making problem in the presence of various selection criteria and a set of alternatives, but previous works are limited to evaluating the tools within the workshop tool library. To intelligently select proper inserts across suppliers under the Internet environment, an insert data format based on ISO 513 was established, and a framework was then designed to obtain a set of alternatives from different suppliers based on fuzzy intervals. Then, knowledge was described with convenient language and the simple membership function to build an intelligent system, which would infer the matching degree of insert characteristics to the machining conditions. Furthermore, analytic hierarchy process was applied to sort the alternatives. Finally, the case study shows that compared with previous works and machinists, this work not only obtains a set of alternatives from all suppliers who uploaded their product data with the designed format but comprehensively evaluates the insert (take finishing low-carbon steel as an example, both cemented carbide and cermet are recommended, the nose radius reduces 25%, the environmental index increases 25%, while the rake reduces 11.25%, when compared with machinists who tend to select the larger rake angle foe finishing). A platform was also developed based on Visual Studio 2015 and SQL Server 2012 to improve selection efficiency for inexperienced CNC operators, purchasers, and vendors.

Strategy of Green Design on Intelligent Energy-Saving Product under Eco-Design Requirements for Energy-Using Product (EuP)

2013 ◽  
Vol 311 ◽  
pp. 398-403
Author(s):  
Jui Che Tu ◽  
Yu Chen Huang ◽  
Chuan Ying Hsu ◽  
Tung Che Wu
Keyword(s):  
Energy Saving ◽  
Product Design ◽  
Intelligent System ◽  
Comprehensive Evaluation ◽  
Design Strategy ◽  
Green Design ◽  
The European Union ◽  
Analytic Hierarchy ◽  
Design Requirements ◽  
Industry Needs

With the threat of global warming nowadays in the 21st century, the European Union has set the standard “Eco-Design Requirements for Energy-using Product(EuP)” for controlling the development of consumptive electronic machinery and products. Therefore, the trend of green design sees the instruction of EuP as the main direction for energy-saving. Considering the factors, undergoing the comprehensive evaluation and development process, the industry needs to draw up the corresponding design strategy in response to the new situation. Therefore, to optimize the green design strategy, the designers can replace hardware with the intelligent system to develop more optimal energy-saving products. Following the ecological instructions of energy-saving of EuP as direction, this study combined the advantage of the intelligent system and green design in order to optimize strategy of green design on intelligent energy-saving product under eco-design requirements for energy-using product (EuP). The evaluation factors were included in the strategies of intelligent energy-saving product design by analyzing the product users’ cognition, needs, habit and etc. Furthermore, through the Fuzzy Analytic Hierarchy Process (FAHP), the priority and the important factors of green design were analyzed. By examining the green design strategy on energy-using product, industry needs to think the energy-saving conditions and the key factors on deciding process. Eventually, the efficiency of product design for environment can be fulfilled successfully.

Multicriteria Evaluation of the Selection of Green Glazing Material by Using the Analytic Hierarchy Process (AHP)

2011 ◽  
Vol 224 ◽  
pp. 152-158 ◽  
Author(s):  
Cheng Chen Chen ◽  
Che Ming Chiang ◽  
Richard S. Horng ◽  
Shin Ku Lee
Keyword(s):  
Analytic Hierarchy Process ◽  
Negative Impact ◽  
Material Selection ◽  
Selection Criterion ◽  
Living Environment ◽  
Impact Factors ◽  
Hazardous Substance ◽  
Analytic Hierarchy ◽  
Glass Material ◽  
Hierarchy Process

The window glazing system provides comfortable living environment for residents and also exhibits the esthetics of architectural design. Its quality is dependent upon glass material selection; there are many factors determining glazing material selection, which might further affects the building safety and energy savings. An analytic hierarchy process (AHP) is used to analyze the trade-off of these impact factors. In the survey, both positive and negative impact factors on the glazing material selection are considered. The results, based on 40 expertise questionnaires, indicated that “performance”, in overall, was perceived to be most important core selection criterion for the green glazing material, but among all assessed items, “hazardous substance release” was concerned the most. The “appearance” was regarded as a minor factor in this analysis. In addition, BIPV alternative was also ranked in the first position regardless of criteria weight variations. The results provide valuable information for building material manufacturers, architects and interior designers in selecting glass material in their the glazing system.

scholarly journals Application of multiple criteria decision methods to optimise learning scenarios

2016 ◽  
Vol 57 ◽  
Author(s):  
Julija Kurilova ◽  
Eugenijus Kurilovas
Keyword(s):  
Comparative Analysis ◽  
Quality Evaluation ◽  
Fuzzy Numbers ◽  
Analytic Hierarchy ◽  
Personalised Learning ◽  
Decision Methods ◽  
Learning Scenarios ◽  
Optimisation Methods ◽  
Hierarchy Process

In the paper, learning scenarios (units) quality evaluation and optimisation problems are analysed. Learning scenarios optimisation is referred here as its personalisation according to learners needs. In the paper, comparative analysis of two popular optimisation methods based on Fuzzy numbers theory and Analytic Hierarchy Process is performed, aiming to measure what method is the most suitable to evaluate the quality of personalised learning scenarios. Learning scenarios quality is referred here as its suitability to learners needs. Research results show that Fuzzy numbers theorybased methods are more suitable to evaluate the quality of personalised learning scenarios.

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