Abstract
Autonomous production control (APC) aims at improving production systems performance through fast and flexible reaction to changes in dynamic production environments. APC shifts the power of decision from a central planning unit, towards single intelligent and distributed logistic objects that can cope with the rising complexity of today’s manufacturing systems. The purpose of this research is to analyse the current state of art on APC in discrete manufacturing industries, throughout a systematic literature review. The study’s objectives were to: (1) identify specialists in APC; and (2) identify theoretical developments and practical implementations. The reviewed was obtained by searching the Scopus database - a total of 49 papers have been analysed. The findings revealed that there is not much work carried out on APC until now, and that most of the contributions are theoretical. It is hoped that this literature review will contribute to enhance research in this science field.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hu, S.J.: Evolving paradigms of manufacturing: From mass production to mass customization and personalization. Procedia CIRP 7, 3–8 (2013)
Niehues, M., Blum, M., Teschemacher, U., Reinhart, G.: Adaptive job shop control based on permanent order sequencing: balancing between knowledge-based control and complete rescheduling. Prod. Eng., 1–7 (2017)
Scholz-Reiter, B., Dashkowskiy, S., Görges, M., Jagalski, T., Naujok, L.: Autonomous decision policies for networks of production systems. In: Decision Policies for Production Networks, pp. 235–263 (2012)
Roblek, V., Meško, M., Krapež, A.: A complex view of industry 4.0. SAGE Open 6(2), 215824401665398 (2016)
Khan, A., Turowski, K.: A perspective on industry 4.0: from challenges to opportunities in production systems. In: Proceedings of the International Conference on Internet of Things and Big Data, no. IoTBD, pp. 441–448 (2016)
Taphorn, C.: Factors for a decentralized production and sequence planning from the perspective of products and resources. In: FAIM 2014 – Proceedings of the 24th International Conference on Flexible Automation and Intelligent Manufacturing. Advanced Manufacturing Enterprise Transforming, vol. 9, pp. 1057–1063 (2014)
Mulrow, C.D.: Systematic reviews: rationale for systematic reviews. BMJ 309(6954), 597 (1994)
Durach, C.F., Kembro, J., Wieland, A.: A new paradigm for systematic literature reviews in supply chain management. J. Supply Chain Manag. 53(4), 67–85 (2017)
Thomé, A.M.T., Scavarda, L.F., Scavarda, A.J.: Conducting systematic literature review in operations management. Prod. Plan. Control 27(5), 408–420 (2016)
Wong, D.: VOSviewer. Tech. Serv. Q. 35(2), 219–220 (2018)
Scholz-Reiter, B., Nathansen, K.: Non-linear dynamics in production systems. ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetr. 94(12), 746–753 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Martins, L., Fernandes, N.O., Varela, M.L.R. (2019). Autonomous Production Control: A Literature Review. In: Machado, J., Soares, F., Veiga, G. (eds) Innovation, Engineering and Entrepreneurship. HELIX 2018. Lecture Notes in Electrical Engineering, vol 505. Springer, Cham. https://doi.org/10.1007/978-3-319-91334-6_58
Download citation
DOI: https://doi.org/10.1007/978-3-319-91334-6_58
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91333-9
Online ISBN: 978-3-319-91334-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)