3D printing: A new pacesetter of industry 4.0 set to reduce the pollution of logistics cost
DOI:
https://doi.org/10.61841/vtzqkd48Keywords:
3D printing,, industrial 4.0,, logistics cost,, collaborative innovationAbstract
This paper explores the evolution of printing created by the revolution of industry 4.0 in which 3D printing technology emerges as one of the trendsetter’s for the purpose of reducing logistics cost. Despite of the existence of technology during the third industrial revolution, 3D printing only emerged into extensive manufacturing digitalization in the fourth industrialization. Manufacturing and the logistics activities have constantly improvised through innovative measures to enhance processes to become more lean and agile. However, conventional manufacturing is less flexible, creates excessive wastages, can only achieve economies of scale when producing large quantity of products and longer time is taken to produce a new product. Breakthroughs in information technology, mobile communications and robotics have led to the growing use of digital technologies in factories around the world. This transformation has come to be known as Industry 4.0 or the Fourth industrial revolution. As such, 3D printing being part of the 4.0 revolution holds the ability to reduce costs that surfaces in logistics activities which could also improve manufacturing cost ultimately
Downloads
References
Collado, S., & Corraliza, J., A. (2017). Children’s Perceived Restoration and Pro-Environmental Beliefs. Journal of ASIAN Behavioural Studies, 2(2), 1-12.
[2] Mehdi K., & Koorosh, A. (2015). Achievement to Environmental Components of Educational Spaces for Iranian Trainable Children with Intellectual Disability. Procedia - Social and Behavioral Sciences, 201, 9-18.
[3] Bishop, K., & Said, I., (2017). Challenges of Participatory Qualitative Research in a Malaysian and Australian Hospital. Asian Journal of Environment-Behaviour Studies, 2(4), 1-11.
[4] Anna Azzi, Daria Battini, Maurizio Faccio, Alessandro Persona, Fabio Sgarbossa, (2014) "Inventory holding costs measurement: a multi-case study", The International Journal of Logistics Management, Vol. 25 Issue: 1, pp.109-132.
[5] Axsäter, S. (2014), “An improved decision rule for emergency replenishments”, International Journal of Production Economics, Vol. 157, pp. 313-317.
[6] B.Tjahjono, et. al, 2017, What does Industry 4.0 mean to Supply Chain, Manufacturing Engineering Society International Conference, MESIC 2017, pp 28-30.
[7] Bala,P.K.(2009b),“Dataminingforretailinventorymanagement”,inAo,S.I.andGelman,L.(Eds), Advances in Electrical Engineering and Computational Science, LNEE Series, Vol. 39, Springer, New York, NY, pp. 587-98.
[8] Bauernhansl, T., ten Hompel, M., Vogel-Heuser, B., 2014. Industrie 4.0 in Produktion, Automatisierung und Logistik. Wiesbaden, Springer.
[9] Brettel, M.,et al., 2014. How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective. International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering. 8(1), p. 37.
[10] Cachon, P. G., 2012. What Is Interesting in Operations Management? Manufacturing & Service Operations Management, 14(2), pp. 166-169.
[11] D. Uckelmann, 2008 Definition Approach to Smart Logistics, Wireless Advanced Network.
[12] Daugherty, P.J., Chen, H. and Ferrin, B.G. (2011), “Organizational structure and logistics service innovation”, International Journal of Logistics Management, Vol. 22 No. 1, pp. 26-51.
[13] Defee, C.C., Williams, B., Randall, W.S. and Thomas, R. (2010), “An inventory of theory in logistics and SCM research”, International Journal of Logistics Management, Vol. 21 No. 3, pp. 404-489.
[14] Dilupa Nakandala, Henry Lau, Jingjing Zhang, (2017) "Strategic hybrid lateral transshipment for cost- optimized inventory management", Industrial Management & Data Systems, Vol. 117 Issue: 8, pp.1632-1649.
[15] Dimitrios P. Koumanakos, (2008) "The effect of inventory management on firm performance", International Journal of Productivity and Performance Management, Vol. 57 Issue: 5, pp.355-369.
[16] Feldmann, C., & Pumpe, A. (2017). A holistic decision framework for 3D printing investments in global supply chains. Transportation Research Procedia. Volume 25, 2017, Pages 677-694.
[17] H. W. Lin, S. V Nagalingam, S.S. Kuik, T. Murata, Int. J. Prod. Econ. 136 (1) (2012) 1–12.
[18] In J.P. Müller, W. Ketter, G. Kaminka, G. Wargner, N. Bulling (Eds.), A Multi agent System Perspective on Industry 4.0 Supply Networks, Multi agent Systems Technologies, 2015.
[19] Kapetaniou, Rieple, Pilkington, Frendsen & Pisano, (2018).Technological Forecasting and Social Change, Volume 128, March 2018, Pages 22-35.
[20] Lee, S.M., Olson, D.L., Trimi, S., (2012), Co-innovation: Convergenomics, collaboration, and co-creation for organizational values, Management Decision, Vol. 50, Iss: 5, pp. 817- 831.
[21] Limbourg, S., Giang, H., & Cools, M. (2016). Logistics Service Quality: The Case of Da Nang City. Procedia Engineering, 142, 124-130.
[22] M.K. Poetz, M. Schreier The value of crowdsourcing: can users really compete with professionals in generating new product ideas? J. Prod. Innovation Management, 29 (2) (2012), pp. 245-256.
[23] Pia Hurmelinna‐Laukkanen, (2011) "Enabling collaborative innovation – knowledge protection for knowledge sharing", European Journal of Innovation Management, Vol. 14 Issue: 3, pp.303-321.
[24] Porter, M.E., Heppelmann, J.E., 2015. Wie smarte Produkte den Wettbewerb verändern. Harvard Business Manager.12/2014, p.1ff.
[25] Randall, W.S., Nowicki, D.R. and Hawkins, T.G. (2011), “Explaining the effectiveness of performance-based logistics: a quantitative examination”, International Journal of Logistics Management, Vol. 22 No. 3, pp. 324- 348.
[26] Seidscher, A. and Minner, S. (2013), “A semi-Markov decision problem for proactive and reactive
transshipments between multiple warehouses”, European Journal of Operational Research, Vol. 230 No. 1, pp. 42-52.
[27] Y. Jin, S. Ji, T. Li et al., “The impact and countermeasures of 3D printing on logistics industry,” Techno Economics & Management Research, vol. 8, pp. 105–108, 2014.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
