Development of AHP Framework of Sustainable Product Design and Manufacturing of Electric Vehicle

Askary, Zareef; Singh, Abhishek; Gupta, Sumit; Shukla, Rohit; Jaiswal, Piyush

doi:10.1007/978-981-13-6469-3_37

Cited by 8 publications

(3 citation statements)

References 13 publications

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“…The promotion of electric vehicles is considered a critical aspect of government policy to move to a green mobility system to reduce vehicle emissions and meet the challenges of sustainable energy development in the transport sector. The AHP framework is developed for the sustainable product design and manufacturing of electric vehicles [6]. The analysis of the transition to two-wheel electric vehicles in areas where motorcycles and motorpowered mopeds are used in large numbers for vehicles is presented in [27].…”

Section: Discussionmentioning

confidence: 99%

“…The relative importance of criteria and subcriteria concerning the research objective are defined and ranked by Saaty scale of pairwise comparison. This scale consists of nine intensities of importance, five primary (1,3,5,7,9) and four intermediate (2,4,6,8). The meanings of each intensity of importance are 1 -equal importance, 2 -weak or slight, 3 -moderate importance, 4 -moderate plus, 5 -strong importance, 6 -strong plus, 7 -very strong or demonstrated importance, 8 -very, very strong, 9 -extreme importance.…”

Section: The Ahp Methods -Methodologymentioning

confidence: 99%

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Multi-Criteria Decision-Making on Road Transport Vehicles by the AHP Method

Barić

Zeljko

2021

The Archives of Automotive Engineering – Archiwum Motoryzacji

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Decision-making processes require the selection of appropriate and choose the optimal solution for implementation. This means that different criteria and their sub-criteria evaluate various alternatives of possible solutions to determine the optimal solution. The research focuses on an Analytic Hierarchy Process (AHP) as one of the multi-criteria decision-making (MCDM) methods and its implementation to evaluate road transport vehicles. The AHP is one of the most used methods for evaluating projects in transport and traffic area. This paper presents a comprehensive review of studies on road transport vehicles evaluated by the AHP method. To gather research articles for the study, several databases such as Web of Science and Scopus were searched. The focus of the research is on road transport vehicles but the performance of the AHP method in the road sector, in general, is briefly reviewed. The results show that most of the studies use AHP for the evaluation of electric and autonomous vehicles. Finally, research results are discussed and recommendations for future research are proposed.

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Section: Discussionmentioning

confidence: 99%

Section: The Ahp Methods -Methodologymentioning

confidence: 99%

Multi-Criteria Decision-Making on Road Transport Vehicles by the AHP Method

Barić

Zeljko

2021

The Archives of Automotive Engineering – Archiwum Motoryzacji

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“…The fourth level refers to supporting analysts in solving a considered problem, for instance, design optimization, energy optimization, and quality improvement. Data-driven approaches dedicated to the evaluation of sustainable manufacturing and product development are often based on methodologies referred to as an analytical hierarchy process [38][39][40][41] and a multi-criteria decision analysis [25,[42][43][44][45][46].…”

Section: Data-driven Approaches and Business Analyticsmentioning

confidence: 99%

Predictive and Prescriptive Analytics in Identifying Opportunities for Improving Sustainable Manufacturing

Relich

2023

Sustainability

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Environmental issues and sustainability performance are more and more significant in today’s business world. A growing number of manufacturing companies are searching for changes to improve their sustainability in the areas of products and manufacturing processes. These changes should be introduced in the design process and affect the whole product life cycle. This paper is concerned with developing a method based on predictive and prescriptive analytics to identify opportunities for increasing sustainable manufacturing through changes incorporated at the product design stage. Predictive analytics uses parametric models obtained from regression analysis and artificial neural networks in order to predict sustainability performance. In turn, prescriptive analytics refers to the identification of opportunities for improving sustainability performance in manufacturing, and it is based on a constraint programming implemented within a constraint satisfaction problem (CSP). The specification of sustainability performance in terms of a CSP provides a pertinent framework for identifying all admissible solutions (if there are any) of the considered problem. The identified opportunities for improving sustainability performance are dedicated to specialists in product development, and aim to reduce both resources used in manufacturing and negative effects on the environment. The applicability of the proposed method is illustrated through reducing the number of defective products in manufacturing.

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