Clustering and selection of knowledge meshes of knowledgeable manufacturing systems based on decomposition of fuzzy relational data

2014 ◽  
Vol 229 (9) ◽  
pp. 1622-1634 ◽  
Author(s):  
Hong-Sen Yan ◽  
Ren-Zi Yang
Keyword(s):  
Manufacturing Systems ◽  
Relational Data ◽  
Knowledgeable Manufacturing ◽  
Selection Of

An application of grey based decision making approach for the selection of manufacturing system

2014 ◽  
Vol 4 (3) ◽  
pp. 447-462 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
G. Anand
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Strategic Decision ◽  
Decision Matrix ◽  
Content Type ◽  
Manufacturing Organization ◽  
Decision Making Model ◽  
Selection Of

Purpose – In the current customer-driven market, the manufacturers have to be highly responsive and flexible to deliver a variety of products. Hence, to meet this dynamic and uncertain market changes, the production system, which enables the manufacturing of such variety of products should be able to meet such diverse, dynamic changes. Hence, selecting a suitable manufacturing system is a key strategic decision for today's manufacturing organization, which needs to survive in these uncertain market conditions. Hence, the purpose of this paper is to present a decision-making model for selecting the best manufacturing system and also discuss the criteria on the basis of which the management can select the same. Design/methodology/approach – A case of small- and medium-sized company is presented, in which the management is deciding to establish a most suitable manufacturing system. To supplement this, a suitable multi-criteria decision-making model (MCDM), the grey approach is used to analyze manufacturing system alternatives based on various decision criteria to arrive a comparative ranking. Findings – An extensive analysis of grey-based decision-making model described grey decision matrix, grey normalized decision matrix, grey weighted normalized decision matrix and grey possibility degrees for three alternatives revealed that lean manufacturing systems was found to be the most suitable manufacturing system among three alternatives for a given case. Research limitations/implications – The same study can be extended by including sub-criteria with main criteria for selection of manufacturing system by utilizing two MCDM techniques such as AHP or ANP with Grey approach. Practical implications – The Grey approach has been discussed in a detailed way and it will be useful for the managers to use this approach as a tool for solving similar type of decision-making problems in their organizations in the future. Originality/value – Although, the problem of selecting a suitable manufacturing system is often addressed both in practice and research, very few reports are available in the literature of Grey-based decision models that demonstrated its application for selecting a suitable manufacturing systems.

scholarly journals Evolutionary Algorithms for Robust Density-Based Data Clustering

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Amit Banerjee
Keyword(s):  
Evolutionary Algorithms ◽  
Evolutionary Computation ◽  
Data Clustering ◽  
Relational Data ◽  
Clustering Methods ◽  
Density Based Clustering ◽  
Selection Of

Density-based clustering methods are known to be robust against outliers in data; however, they are sensitive to user-specified parameters, the selection of which is not trivial. Moreover, relational data clustering is an area that has received considerably less attention than object data clustering. In this paper, two approaches to robust density-based clustering for relational data using evolutionary computation are investigated.

scholarly journals Selection of a data exchange format for industry 4.0 manufacturing systems

2016 ◽  
Author(s):  
Ricardo Silva Peres ◽  
Mafalda Parreira-Rocha ◽  
Andre Dionisio Rocha ◽  
Jose Barbosa ◽  
Paulo Leitao ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Data Exchange ◽  
Manufacturing Systems ◽  
Data Exchange Format ◽  
Exchange Format ◽  
Selection Of

An integrated fuzzy-based multi-criteria decision-making approach for the selection of an effective manufacturing system

2018 ◽  
Vol 25 (1) ◽  
pp. 280-296 ◽  
Author(s):  
Ram Prakash ◽  
Sandeep Singhal ◽  
Ashish Agarwal
Keyword(s):  
Decision Making ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Sustainable Growth ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Manufacturing Company ◽  
Selection Of

Purpose The research paper presents analysis and prioritization of barriers influencing the improvement in the effectiveness of manufacturing system. The purpose of this paper is to develop an integrated fuzzy-based multi-criteria decision-making (F-MCDM) framework to assist management of the case company in the selection of most effective manufacturing system. The framework helps in prioritizing the manufacturing systems on the basis of their effectiveness affected by the barriers. Design/methodology/approach In this paper, on the basis of experts’ opinion, five barriers have been identified in a brain-storming session. The problem of prioritization of manufacturing system is a multi-criteria decision-making (MCDM) problem and hence is solved by using the F-MCDM approach using dominance matrix. Findings Manufacturing systems’ effectiveness for Indian industries is influenced by barriers. The prioritization of manufacturing systems depends on qualitative factor decision-making criteria. Among the manufacturing systems, leagile manufacturing system is given the highest priority followed by lean manufacturing system, agile manufacturing system, flexible manufacturing system and cellular manufacturing system. Research limitations/implications The selection of an appropriate manufacturing system plays a vital role for sustainable growth of the manufacturing company. In the present work, barriers which influence the effectiveness of manufacturing system have been identified. On the basis of degree of influence of barriers on the effectiveness of the manufacturing system, five alternative manufacturing systems are prioritized. The framework will help the management of the case company to take reasonable decision for the adoption of the appropriate manufacturing system. Practical implications The results of the research work are very useful for the manufacturing companies interested in analyzing the alternative manufacturing systems on the basis of their effectiveness and their sensitivity toward various barriers. The management of Indian manufacturing company will take decision to adopt a manufacturing system whose effectiveness is least sensitive toward barriers. Effectiveness of such manufacturing system will improve with time without having retardation due to barriers. With improved effectiveness of the manufacturing system, the manufacturing company would be able to survive with global competition. The result of the present work is based on the inputs from the case company and may vary for the other manufacturing company. In the present work, only five alternative manufacturing systems and five barriers have been considered. To obtain the better result, MCDM approach with more number of alternative manufacturing systems and barriers might be considered. Originality/value The research work is based on the fuzzy analytic hierarchy process framework and on the case study conducted by the authors. The work carried out is original in nature and based on the real-life case study.

A Concurrent Design Exploration Method for Realizing Networked Manufacturing Systems

2017 ◽  
Author(s):  
Jelena Milisavljevic ◽  
Sesh Commuri ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Manufacturing Systems ◽  
Concurrent Design ◽  
Networked Manufacturing ◽  
Multistage Manufacturing ◽  
Traditional Design ◽  
Design Variables ◽  
And Control ◽  
Automotive Panel ◽  
Selection Of

Multistage manufacturing processes (MMPs) are networked manufacturing systems consisting of multiple operational stations that have characteristics of mechanical and control systems. Common challenges in the design of MMPs are the selection of sensors and tools as this not only affects the dimensional quality of the finished product, but also influences the computational complexity in representing and analyzing the problem. Imprecise or incomplete information results in uncertainty in the models used to represent the MMP and limit the use of traditional design approaches. In this paper, an exploration method for the concurrent design (CDEM) of MMPs under uncertainty is presented wherein the attributes of tools and sensors are treated as design variables, thereby allowing flexibility in a design process. The proposed method is illustrated using an example of automotive panel stamping process. Our focus in this paper is on the method rather than the results per se.

scholarly journals Categorization of Anomalies in Smart Manufacturing Systems to Support the Selection of Detection Mechanisms

2017 ◽  
Vol 2 (4) ◽  
pp. 1885-1892 ◽  
Author(s):  
Felipe Lopez ◽  
Miguel Saez ◽  
Yuru Shao ◽  
Efe C. Balta ◽  
James Moyne ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Detection Mechanisms ◽  
Smart Manufacturing Systems ◽  
Selection Of
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