Artificial Intelligence Applications for Increasing Resource Efficiency in Manufacturing Companies—A Comprehensive Review

Waltersmann, Lara; Kiemel, Steffen; Stuhlsatz, Julian; Sauer, Alexander; Miehe, Robert

doi:10.3390/su13126689

Cited by 56 publications

(27 citation statements)

References 93 publications

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“…The concept of intelligence mainly derives from “intelligent manufacturing”, Wright and Bourne (1988) first proposed this idea in their work Manufacturing Intelligence, in which they argued intelligent manufacturing is a complete systemic project to implement batch production with the help of integrated systems, robot applications, software systems, and other technologies. Under the background of Industry 4.0, where the deep combination of intelligent technology and the real economy is imperative (Waltersmann et al, 2021), research interests increasingly concentrate on the economic effect of industrial intelligence, such as labor force structure and employment (Acemoglu & Restrepo, 2020; Agrawal et al, 2019; Sun & Hou, 2019), the geography of companies (Wang, Jiang, & Dong, 2022), industrial development (Tang & Chi, 2022), and so forth. For instance, Acemoglu and Restrepo (2018) argue enterprises will invest in automation technology and intelligent production to alleviate the decline in productivity caused by the labor shortage, and there is a certain substitution effect and productivity effect of intelligence along with the deep integration of intelligence into the real economy.…”

Section: Literature Review and Theoretical Analysismentioning

confidence: 99%

Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Tian

Qin

Cheng

et al. 2023

Sustainable Development

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Global climate change is becoming an increasingly serious issue. China, the largest carbon emitter, has a long way towards its sustainable development goals (SDGs) and take on its carbon reduction responsibility, especially in the industrial sector. In this vein, industrial intelligence, a key driver in the “Industry 4.0 era”, offers an opportunity in this carbon reduction campaign. This paper seeks to examine the influences of industrial intelligence on carbon emissions, their heterogeneous characteristics and transmission mechanisms, and the moderating role of human capital. Therefore, we properly probed theoretical aspects, and then we used China's provincial data from 2006 to 2019 and a number of tests, namely the fixed effect model, the two‐stage test, and the moderating effect model, to test the relevant assumptions. We first unfolded that industrial intelligence can significantly mitigate carbon emissions. Specifically, the heterogeneous analysis found that carbon reduction efforts are more pronounced in China's central and western regions and resource‐based regions. We further highlight the mechanism identification, which reveals that industrial structure upgrading and technological innovation are the main channels for industrial intelligence to abate CO2 emissions. Importantly, we pinpoint the role of human capital, which positively moderates the relationship between industrial intelligence and carbon emissions and can well amplify the industrial structure effect of industrial intelligence. These results are conducive to accurately assessing the environmental benefits of industrial intelligence and providing policy enlightenment for China to alleviate carbon emissions, and they will also offer a reference for other developing countries to learn from.

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Section: Literature Review and Theoretical Analysismentioning

confidence: 99%

Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Tian

Qin

Cheng

et al. 2023

Sustainable Development

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“…37 to 45 in the report of AIDA (2022). Also, Waltersmann et al (2021, pp. 66–89) stresses the importance of sustainability in AI solutions in both Green AI AND Green by AI, supporting the importance of our wide meaning of “Green AI.”…”

Section: Notesmentioning

confidence: 99%

“…7. “[T]he sustainability improvement of AI applications themselves (Green AI) and by AI (Green by AI). (Waltersmann et al , 2021, pp. 66–89).…”

Section: Notesmentioning

confidence: 99%

Sustainable city planning and public administration assisted by green AI: attendant legal challenges under Japanese law

Matsuo¹,

Iwamitsu

2022

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Purpose The purpose of this paper is to present the legal conditions under which governments may use green artificial intelligence (AI) in city planning. Although Japan was one of the early countries to release its general AI principles, it has been relatively slow in establishing conditions where administrative agencies may use AI. Granted, there have been some recent scholarship that discusses the usage of AI in general under Japanese administrative law, but the use of green AI in city planning under Japanese law has not yet been discussed. Hence, this paper intends to focus on green AI in city planning and discuss the conditions for usage based on different categories of AI. Design/methodology/approach This paper conducts a legal analysis on the utilization of AI for the purpose of sustainable city planning and administration in Japan. The approach of this paper is to summarize the existing scholarship in Japanese administrative law and analyse the new elements in the new field of green AI in city planning. This paper is not a natural science paper. The social science method of jurisprudence is used. This paper cites only public sources, and no informal literature has been referenced. Findings This paper establishes the conditions where Japanese central and local government may use green AI in city planning from a legal viewpoint based on three categories. The categories are green AI usage in city planning concerning things, green AI usage in city planning concerning people and green AI usage in city planning concerning automated decision-making. Research limitations This research is limited to an analysis of Japanese law, which means that issues other than law are not included in this paper. Further, although general legal issues are discussed, this paper is intended to discuss Japanese law issues only, and foreign laws are not discussed. Therefore, this paper mostly cites Japanese language papers published in domestic journals. Practical implications The intended practical implication of this paper is to allow central and local governments to determine – based on the proposed categories – whether green AI can be used for city planning purposes and under which conditions. The authors hope that this will assist the Japanese government in establishing rules on the usage of AI by governmental agencies and allow for the greater actual usage by Japanese central and local governments of green AI in future city planning. Social implications As the theme of this paper deals with governmental use (and the function of a government is to serve society), the social implications at issue can be said to be equivalent to the practical implication. Originality/value There have been articles discussing Japanese administrative law restrictions on AI in general. However, as of now, to the best of the authors’ knowledge, there have been no articles published focusing on green AI used for city planning. The authors note that the green AI used for city planning would have different legal implications from AI’s usage by the government in general, such as the chatbot used by the agencies or lethal autonomous weapons by the military force. Therefore, this paper is original in focusing on green AI used for city planning.

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“…In turn, Rouhiainen [15] defines AI as "the ability of machines to use algorithms, learn from data and use what they have learned in decision-making just as a human being would" [15] (p. 17). Moreover, Waltersmann [16] define AI as an activity dedicated to manufacturing intelligent machines, with intelligence being the quality that allows this entity to function properly.…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

The 4.0 Industry Technologies and Their Impact in the Continuous Improvement and the Organizational Results: An Empirical Approach

et al. 2021

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This study analyses the relationships between the technologies of Industry 4.0, continuous improvement, and the business results. To carry out this study, 109 questionnaires to companies of different sectors were collected, but an indispensable condition to take into account was the fact that these companies develop themselves their logistics management. The analysis of the results obtained through the Partial Least Squares (PLS) methodology argues that there is a positive relationship between 4.0 Industry and continuous improvement processes, as well as between continuous improvement processes and organizational results, although it cannot be concluded that a direct relationship between 4.0 Industry and organizational results exists, which means that there are other variables, such as continuous improvement, mediating between them. With this work, there is already an accredited reference of the relationship, which has been verified to exist, between the Industry 4.0, the continuous improvement, and the business results.

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Artificial Intelligence Applications for Increasing Resource Efficiency in Manufacturing Companies—A Comprehensive Review

Cited by 56 publications

References 93 publications

Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Sustainable city planning and public administration assisted by green AI: attendant legal challenges under Japanese law

The 4.0 Industry Technologies and Their Impact in the Continuous Improvement and the Organizational Results: An Empirical Approach

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