Abstract
Since the beginning of the first industrial revolution, engineers were always attempting to resolve problems related to the operation of machinery and their maintenance. They also aimed at the improvement of the efficiency of manufacturing processes and generally at the organization of the production and other relative subjects. As it was anticipated, systematic approaches for the scientific study of industry-related problems were established and the solutions were proposed. However, after the introduction of computers and development of computational methods, a new promising era for solving industry-related problems emerged, as advanced computational techniques were capable of providing approximate but significantly accurate solutions. Especially, when it is desired to increase the efficiency of manufacturing processes by determining the optimum process parameters or when the solution of hard production-based problems, such as scheduling, is required, optimization methods can be employed.
Keywords
- Industry-related Problems
- Smart Factory
- Swarm Intelligence-based Method
- Teaching–learning-based Optimization Method
- Imperialist Competitive Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Hermann M, Pentek T, Otto B (2016) Design principles for industrie 4.0 scenarios. In: 2016 49th Hawaii international conference on system sciences (HICSS). Koloa, USA, pp 3928–3937
Qian F, Zhong W, Du W (2017) Fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Engineering 3:154–160
Roblek V, Meško M, Krapež A (2016) A complex view of industry 4.0. SAGE Open 6:2158244016653987
Kagermann H, Wolf-Dieter L, Wahlster W (2011) Industrie 4.0: Mit dem Internet der Dinge auf dem Weg zur 4. industriellen Revolution. VDI Nachrichten 13:11
Liu Y, Xu X (2016) Industry 4.0 and cloud manufacturing: a comparative analysis. J Manuf Sci Eng 139:34701–34708
Aiman Kamarul Bahrin M, Othman F, Hayati Nor Azli N, Farihin Talib M (2016) Industry 4.0: a review on industrial automation and robotic. Jurnal Teknologi 78:137–143
Thoben K-D, Wiesner S, Wuest T (2017) “Industrie 4.0” and smart manufacturing—a review of research issues and application examples. Int J Autom Technol 11(1):4–16
Zhong RY, Xu X, Klotz E, Newman ST (2017) Intelligent manufacturing in the context of industry 4.0: a review. Engineering 3:616–630
Lu Y (2017) Industry 4.0: a survey on technologies, applications and open research issues. J Ind Inf Integr 6:1–10
Wang S, Wan J, Zhang D, Li D, Zhang C (2016) Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput Netw 101:158–168
Shrouf F, Ordieres J, Miragliotta G (2014) Smart factories in industry 4.0: a review of the concept and of energy management approached in production based on the internet of things paradigm. In: 2014 IEEE international conference on industrial engineering and engineering management. Bandar Sunway, Malaysia, pp 697–701
Tamás P, Illes B, Dobos P (2016) Waste reduction possibilities for manufacturing systems in the industry 4.0. IOP Conf Ser Mater Sci Eng 161(1):012074
Liao Y, Deschamps F, de Loures EFR, Ramos LFP (2017) Past, present and future of Industry 4.0—a systematic literature review and research agenda proposal. Int J Prod Res 55:3609–3629
Illés B, Tamás P, Dobos P, Skapinyecz R (2017) New challenges for quality assurance of manufacturing processes in industry 4.0. Solid State Phenom 261:481–486
Tamás Péter, Illes B (2016) Process improvement trends for manufacturing systems in industry 4.0. Acad J Manuf Eng 14:119–125
Rao SS (2009) Introduction to optimization. Wiley, Hoboken
Lin M-H, Tsai J-F, Yu C-S (2012) A review of deterministic optimization methods in engineering and management. J Math Probl Eng 756023
Rothlauf F (2011) Design of modern heuristics: principles and application, 1st edn. Springer Publishing Company Inc., Berlin
Wang X, Damodaran M (2000) Comparison of deterministic and stochastic optimization algorithms for generic wing design problems. J Aircr 37:929–932
El-Ghazali T (2009) Metaheuristics: from design to implementation. Wiley Publishing, Hoboken
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 The Author(s)
About this chapter
Cite this chapter
Karkalos, N.E., Markopoulos, A.P., Davim, J.P. (2019). General Aspects of the Application of Computational Methods in Industry 4.0. In: Computational Methods for Application in Industry 4.0. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-92393-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-92393-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-92392-5
Online ISBN: 978-3-319-92393-2
eBook Packages: EngineeringEngineering (R0)