A hybrid method for the selection of facility layout using experimental design and grey relational analysis: A case study

2019 ◽  
Vol 15 (2) ◽  
pp. 101-110 ◽  
Author(s):  
S.M. Vadivel ◽  
A.H. Sequeira
Keyword(s):  
Experimental Design ◽  
Hybrid Method ◽  
Grey Relational Analysis ◽  
Facility Layout ◽  
Relational Analysis ◽  
Grey Relational ◽  
Selection Of

Design for Product Adaptability

2007 ◽  
Author(s):  
Y. Li ◽  
D. Xue ◽  
P. Gu
Keyword(s):  
Life Cycle ◽  
Grey Relational Analysis ◽  
Design Approach ◽  
Analysis Method ◽  
Adaptable Design ◽  
Evaluation Measures ◽  
Relational Analysis ◽  
Design Paradigm ◽  
Grey Relational

Adaptable design is a new design paradigm to create designs and products that can be easily changed to satisfy different requirements. Adaptable design aims at identifying the designs and products considering functionality, manufacturing efforts, customization and environment friendliness. This research focuses on adaptable design considering product adaptability. In this work, product adaptability is evaluated by three measures including extendibility of functions, upgradeability of modules, and customizability of components. Various design candidates created in adaptable design are evaluated by different life-cycle evaluation measures including product adaptability of design, part and assembly costs of manufacturing, and operationability by customers. Since different evaluation measures are modeled in different units, the grey relational analysis method is employed to integrate the different evaluation measures for prioritizing different design candidates. A case study is given to demonstrate the effectiveness of the introduced adaptable design approach.

scholarly journals Integrated analytical hierarchy process and grey relational analysis approach to measure supply chain complexity

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sujan Piya ◽  
Ahm Shamsuzzoha ◽  
Mohammed Khadem ◽  
Mahmoud Al Kindi
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Analytical Hierarchy Process ◽  
Grey Relational Analysis ◽  
Extensive Literature ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Hierarchy Process

PurposeThe purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC).Design/methodology/approachThrough extensive literature review, the authors discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study.FindingsThe authors identified 22 drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing and company culture.Originality/valueIn this paper, the authors propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors' knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC.

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