scholarly journals Industry 4.0 Technology Implementation Impact to Industrial Sustainable Energy in Indonesia: A Model Conceptualization

2019 ◽  
Vol 156 ◽  
pp. 227-233 ◽  
Author(s):  
Akhmad Hidayatno ◽  
Arry Rahmawan Destyanto ◽  
Christin Arauna Hulu
2020 ◽  
Vol 51 (11) ◽  
pp. 14-25
Author(s):  
Krisztina Demeter ◽  
Dávid Losonci ◽  
Róbert Marciniak ◽  
Judit Nagy ◽  
Péter Móricz ◽  
...  

In the last few years, the management literature has become noisy with Industry 4.0 (I4.0). Although several concepts and typologies intend to make the phenomenon more understandable, these endeavours generally focus on technological aspects or specific issues. Therefore, integrated approaches of the I4.0 transformation on the business side and a comprehensive investigation of this phenomenon on the academic side are still needed. This paper synthetizes the lessons of 15 case studies from five sectors (automotive, FMCG, logistics services, retail, and business services) and places them in a triadic framework of technology, strategy, and organization. The case studies are based on interviews, internal documents and public information. This paper reveals that the analysed companies focus on I4.0 technologies that are substantially related to the development of core activities. Companies in a highly competitive global environment (e.g., automotive industry and business services) are more prepared and progress faster with I4.0 technology implementation.


2020 ◽  
Vol 11 (8) ◽  
pp. 1463
Author(s):  
Mohammed Ali Berawi ◽  
Nyoman Suwartha ◽  
Isti Surjandari ◽  
T. Yuri M. Zagloel ◽  
Muhamad Asvial ◽  
...  

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chiara Cimini ◽  
Albachiara Boffelli ◽  
Alexandra Lagorio ◽  
Matteo Kalchschmidt ◽  
Roberto Pinto

PurposeThis article aims to investigate the organisational implications of adopting Industry 4.0 (I4.0) technologies, giving specific attention to operations. The paper addresses these implications in two directions: organisational prerequisites for, and consequences of, I4.0 technologies.Design/methodology/approachThe research is based on a multiple case study of Italian small and medium enterprises (SMEs) in manufacturing. Ten case studies have been developed through interviews, company visits and secondary data collection.FindingsThe multiple case study results show that: (1) a lean organisational structure supports effective adoption of I4.0 technologies; (2) introducing such technologies is linked to developing a new kind of job profile (i.e. the “Autonomous Operative Job Profile”); and (3) higher levels of technology adoption create a higher need for non-technical competences.Research limitations/implicationsA limitation of this research relates to the highly heterogeneous maturity levels of the sampled companies, due to the relative newness of the I4.0 paradigm. Future research could, therefore, longitudinally analyse the technology integration process within organisations.Practical implicationsThis research provides preliminary evidence about how organisations and technologies co-evolve, thus suggesting that managers should co-design these areas. It also demonstrates the extreme importance of designing a structured process and a clear set of human resource management tools to favour SME organisational development.Originality/valueThe study is built upon a conceptual framework derived from the sociotechnical perspective that analyses the interconnections between technology implementation and organisational change. From the results, three research propositions are derived to be tested on a larger scale.


2020 ◽  
Vol 20 (2) ◽  
pp. 304-326
Author(s):  
Angélica Pott de Medeiros ◽  
Rosalia Aldraci Barbosa Lavarda ◽  
Rolf Hermann Erdmann

2021 ◽  
Vol 11 (3) ◽  
pp. 451-466
Author(s):  
Omar Alexánder León-García ◽  
Mónica Yamile Bermúdez-Segura

Industry 4.0 is a manufacturing concept that has gained strength in organizations because it delves into industrial automation, digitization, and new technology implementation to improve working conditions and productivity. This article aims to contribute to the current debate on industry 4.0 while providing an overview of barriers and facilitators. Based on documentary analysis of 49 articles written between 2014 and 2020, six categories related to barriers were identified: security, costs, human talent, organizational resistance, and use of technologies; and eight as driving forces of Industry 4.0 implementation: technological pre-existence, management commitment, efficiency, competitiveness, sustainability, competent employees, and government policies.


Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 222
Author(s):  
Piotr Marciniak ◽  
Robert Stanisławski

As part of the assumptions of Industry 4.0. many modern technologies are developing. One of them is robotic process automation (RPA). It allows the replacement of human labor with robots, thus increasing the production capacity of enterprises. In practice, the implementation of RPA takes place through two solutions (models): using the services of an external entity offering RPA (service insourcing) or creating your own center of excellence (CoE). The use of both solutions is influenced by numerous conditions (determinants), among which we can mention benefits on the one hand and threats on the other. They are very different and depend on the model used. In this article, attempts were made to identify and determine their impact on the selection of the appropriate model from the point of view of the company (the purpose of the article). The research used two cases of entities implementing RPA on the basis of opposites, i.e., two different models, in which the discussed technology is treated as an important element of their automation. The achieved results indicate that there is no universalism, and their dominant feature is individualism concerning both enterprises and the solutions they implement. This is undoubtedly the effect of the currently too shallow RPA market, as well as the small number of entities using technologies based on intelligent systems. This is a serious research gap, which along with RPA growth will be reduced as a result of more and more intensive research in this field.


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