Requirement Analysis for the Design of Smart Logistics in SMEs

Dallasega, Patrick; Woschank, Manuel; Zsifkovits, Helmut; Tippayawong, Korrakot Yaibuathet; Brown, Christopher

doi:10.1007/978-3-030-25425-4_5

Cited by 26 publications

(32 citation statements)

References 16 publications

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“…Furthermore, information exchange is established through the usage of modern information and communication technologies (ICT), data networks, actors and sensors, and automatic identification and material tracking technologies. Moreover, automated transport, transition, and storage systems, supported by autonomous transport vehicles, should enable a partial and/or complete self-control of systems [2, [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

Woschank¹,

Rauch

Zsifkovits³

2020

Sustainability

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195

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Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics.

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Section: Introductionmentioning

confidence: 99%

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

Woschank¹,

Rauch

Zsifkovits³

2020

Sustainability

Self Cite

195

View full text Add to dashboard Cite

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“…Another very important social aspect of such smart environment is how the intelligent machines will affect the labor market [20][21][22][23][24]. This topic has basically been examined from two perspectives; firstly, by describing requirements towards workers in I4.0 [20][21][22][23][24]; secondly, by examining the standpoint of workers and their outlook or current state of mind [20,25]. Regarding the I4.0 environment, the authors can conclude that there is a growing trend in the literature highlighting the importance of sustainable development and management [26].…”

Section: Introductionmentioning

confidence: 99%

Industry 4.0—Awareness in South India

et al. 2020

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Industry 4.0 (I4.0) approaches, frameworks, and technologies have gained an increasing relevance in order to gain sustainable and competitive advantages for industrial enterprises and for small and medium enterprises (SMEs), as well. Contrary to previous studies, which are mainly focused on companies, we conducted a questionnaire-based survey on inhabitants, in an attempt to examine general awareness about I4.0 concepts, in the region of South India. Our findings revealed a rather poor informational level of I4.0 concept and its components, which consequently leads to inadequate future actions and expectations. Moreover, respondents with prior information about I4.0 framework tend to have rather positive opinions and expectations of possible future trends. We emphasize that insufficient knowledge of the potential workforce regarding I4.0 concepts, especially in a region with ascending demographic development, can be considered as one of the main barriers for a successful and sustainable future development towards the 4th industrial revolution.

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“…In the case of logistics management, Industry 4.0 can fulfill the needs of Smart Logistics [42,[68][69][70]. However, in the case of LSPs, limited research has clearly demonstrated the benefits of implementing the Industry 4.0 concept [71,72], especially for re-designing service to accommodate customer needs depending on their lifecycle stages.…”

Section: Discussionmentioning

confidence: 99%

On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs

2020

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Improving service logistics is crucial in order to reciprocate customer needs. The paper aims to validate the Logistics Service Provider (LSP) Lifecycle Model for re-designing logistics service in three LSP case studies in Thailand. The lifecycle-stage evaluation was adapted to identify the current status in its lifecycle. Afterward, logistics service strategies were implemented according to the voice of the customer by Quality Function Deployment (QFD). The study combined the Logistics Service Provider (LSP) Lifecycle Model with the application of Industry 4.0 (I4.0) to improve service logistics. Case studies showed the implementation of the service logistics strategies with the feasibility solution of Industry 4.0.Sustainability 2020, 12, 2394 2 of 17 real-time information, and Circular Economy (CE) [21] are now among the basic customer requirements. Furthermore, customer behavior has changed too. Quick and immediate responses are expected. Information Technology (IT) has been increasingly used in the global business to satisfy the customer in terms of supply [22,23]. Today, Industry 4.0 is being used to accomplish the customer target, operation, and improvement in manufacturing [24,25]. Some examples of the advancement of Industry 4.0 are applying to self-learning automation, big data analytics, real-time information, Internet of Things (IoT), and smart sensors [26,27]. This improvement expands to the logistics industry in the form of, for example, on-demand delivery which offers an abrupt response to the customer [28,29]. The trend has changed rapidly around the world and the logistics service is demanded to support it. Therefore, LSPs need to innovate and create new service to address these complicated customer trends [30]. This paper demonstrates the use of the LSP Lifecycle Model to re-design the logistics service using three case-study LSPs in Thailand. It aims to address the research questions of whether the developed LSP Lifecycle Model is valid and if the Industry 4.0 concept is applicable and can be beneficial for LSPs. Firstly, the study identified the stage of the service. Secondly, services were re-designed using QFD. Thirdly, customer requirements were prioritized using the Multiple-Criteria Decision-Making (MCDM) tool. Finally, the Industry 4.0 concept was mapped to address these demands. Literature Review

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Requirement Analysis for the Design of Smart Logistics in SMEs

Cited by 26 publications

References 16 publications

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

Industry 4.0—Awareness in South India

On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs

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