Minimizing the trade-off between sustainability and cost effective performance by using autonomous vehicles

Gružauskas, Valentas; Baskutis, Saulius; Navickas, Valentinas

doi:10.1016/j.jclepro.2018.02.302

Cited by 127 publications

(77 citation statements)

References 25 publications

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“…Green manufacturing has been addressed to be the future as it helps the company as well as the environment in the long run. Small and medium enterprises are recommended to implement blockchain technology by forming a logistics cluster and sharing autonomous transportation and warehousing for achieving long term sustainable advantage ( Gružauskas et al, 2018 ). “Physical Internet”, a new concept which can help the SC to solve data trust issues, would provide a larger customer base, and help move towards a more digitized infrastructure.…”

Section: Discussion and Future Research Agendamentioning

confidence: 99%

Blockchain technology in supply chain operations: Applications, challenges and research opportunities

Dutta

Choi

Somani

et al. 2020

Transportation Research Part E: Logistics and Transportation Re

964

402

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Highlights Evaluate 178 research articles in the field of blockchain implementation in supply chains. Identify the current trends of research on blockchain in different domains of supply chain operations. Examine various supply chain functions that can be enhanced through blockchain technology. Present strong excerpts of blockchain applications in supply chains across various industrial sectors. Suggest managerial implications, highlight challenges and build a future research agenda.

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Section: Discussion and Future Research Agendamentioning

confidence: 99%

Blockchain technology in supply chain operations: Applications, challenges and research opportunities

Dutta

Choi

Somani

et al. 2020

Transportation Research Part E: Logistics and Transportation Re

964

402

View full text Add to dashboard Cite

show abstract

“…Communication with suppliers encourages heterogeneous resource transportation, which reduces transportation frequencies and distance [12]. Additionally, this platform promotes autonomous vehicles, enabling optimized routes with transportation reduction [27,103,118]. As illustrated by [103], the level of CO 2 emissions can be decreased by approximately 22%, attributed to the information transparency and big data analytics [103].…”

Section: Cps and Connection Level (Iiot)mentioning

confidence: 99%

Environmental Sustainability of Digitalization in Manufacturing: A Review

2020

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The rapid development and implementation of digitalization in manufacturing has enormous impact on the environment. It is still unclear whether digitalization has positive or negative environmental impact from applications in manufacturing. Therefore, this study aims to discuss the overall implications of digitalization on environmental sustainability through a literature study, within the scope of manufacturing (product design, production, transportation, and customer service). The analysis and categorization of selected articles resulted in two main findings: (1) Digitalization in manufacturing contributes positively to environmental sustainability by increasing resource and information efficiency as a result of applying Industry 4.0 technologies throughout the product lifecycle; (2) the negative environmental burden of digitalization is primarily due to increased resource and energy use, as well as waste and emissions from manufacturing, use, and disposal of the hardware (the technology lifecycle). Based on these findings, a lifecycle perspective is proposed, considering the environmental impacts from both the product and technology lifecycles. This study identified key implications of digitalization on environmental sustainability in manufacturing to increase awareness of both the positive and negative impacts of digitalization and thereby support decision making to invest in new digital technologies.

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“…• The inability to produce mass-customized products (IoT, AM) [59]-which refers to the difficulty of the company in developing highly flexible and adaptive manufacturing processes capable of manufacturing customized products with an efficiency comparable to mass production. • Legislation restrictions for robotics in the joint integration of IoT, BDA, and robotics [60]-which refers to the limited implementation of robots in companies (e.g., autonomous vehicles) due to a lack of regulated legislation that would enable their implementation. • The lack of financial resources for the joint implementation of the CPS, IoT, and cloud computing [61]-refers to the need to invest substantial financial resources in the implementation of these three technologies, where it should be stressed that the current technological solutions are not affordable for SMEs.…”

Section: B Managerial Industry 40 Implementation Challenges Analysismentioning

confidence: 99%

Industry 4.0 Implementation Challenges and Opportunities: A Managerial Perspective

Bajić

Rikalović

Suzić

et al. 2021

IEEE Systems Journal

139

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Industry 4.0 is a concept aimed at achieving the integration of physical parts of the manufacturing process (i.e., complex machinery, various devices, and sensors) and cyber parts (i.e., advanced software) via networks and driven by Industry 4.0 technology categories used for prediction, control, maintenance, and integration of manufacturing processes. Industry 4.0, which is expected to have a great impact on manufacturing systems in the future, is attracting attention in both industry and academia. Although academic research on Industry 4.0 is growing exponentially, evidence of Industry 4.0 implementation in practice is still scarce. Moreover, the challenges industry faces when implementing the Industry 4.0 concept seem to be even less addressed. At the start of the present survey, a preliminary literature review identified a lack of comprehensive analysis of the Industry 4.0 implementation challenges. Thus, the purpose of the present article is to provide an overview of the reported Industry 4.0 implementation challenges in the relevant literature by conducting a systematic literature review. Specifically, while the present study differentiates between managerial and technological Industry 4.0 implementation challenges, the focus of the present article is on the managerial Industry 4.0 implementation challenges. This overview is performed by deriving an inductively coded Industry 4.0 technology framework that classifies Industry 4.0 technologies into ten categories: cyber physical systems, Internet of Things, big data analytics, cloud computing, fog and edge computing, augmented and virtual reality, robotics, cyber security, semantic web technologies, and additive manufacturing. The present article identifies, codes, and defines the managerial Industry 4.0 implementation challenges and derives opportunities for overcoming them.

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Minimizing the trade-off between sustainability and cost effective performance by using autonomous vehicles

Cited by 127 publications

References 25 publications

Blockchain technology in supply chain operations: Applications, challenges and research opportunities

Blockchain technology in supply chain operations: Applications, challenges and research opportunities

Environmental Sustainability of Digitalization in Manufacturing: A Review

Industry 4.0 Implementation Challenges and Opportunities: A Managerial Perspective

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