Abstract
Smart factories have already become a key theme in the manufacturing industry. Advanced IT technology, industrial engineering, and management know-how will be combined to improve all areas of manufacturing. Improving productivity is the most important goal for a factory. However, this is only part of the overall goal of corporate management. Corporate management pursues a greater goal of optimizing all of the company’s resources to reduce losses, increase profits and achieve sustainable growth. All companies should achieve smart factories to prevent unnecessary waste of time and resources and maximize profits by increasing productivity. This paper deals with the integration effect of the major fundamental system, including the Manufacturing Execution System that operates production, and the method of measuring it. When integrating core systems to maximize successful inventory management and revenue, a method of assessing them is required. Here it would be appropriate to have an evaluation method in which scores are given and calculated differently depending on the results and functional priorities obtained by the system. This approach will help solve the problem of which systems each company will use and integrate when introducing smart factories.
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
Similar content being viewed by others
References
Wang, S., et al.: Implementing smart factory of industrie 4.0: an outlook. Int. J. Distrib. Sensor Networks 12(1), 3159805 (2016)
Meyr, H., Wagner, M., Rohde, J.: Structure of advanced planning systems. In: Supply Chain Management and Advanced Planning, pp. 99–106. Springer, Berlin, Heidelberg (2015). https://doi.org/10.1007/978-3-642-55309-7_5
Rashid, M.A., Riaz, Z., Turan, E., Haskilic, V., Sunje, A., Khan, N.: Smart factory: E-business perspective of enhanced ERP in aircraft manufacturing industry. In: 2012 Proceedings of PICMET 2012: Technology Management for Emerging Technologies, pp. 3262–3275. IEEE, July 2012
Zhong, R.Y., et al.: RFID-enabled real-time manufacturing execution system for mass-customization production. Robot. Comput.-Integr. Manuf. 29(2), 283–292 (2013)
Liboni, L.B., Cezarino, L.O., Jabbour, C.J.C., Oliveira, B.G., Stefanelli, N.O.: Smart industry and the pathways to HRM 4.0: implications for SCM. Supply Chain Manage. Int. J. 24(1), 124–146 (2019)
Stark, J.: Product Lifecycle Management, vol. 1, pp. 1–29. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24436-5_1
Lech, M.M., et al.: Quality management system with human-machine interface for industrial automation. U.S. Patent No. 6,539,271, 25 Mar 2003
Schulze, B.D.: System and method for automated monitoring and assessment of fabrication facility. U.S. Patent No. 6,671,570. 30 Dec 2003
Kerry, J., Butler, P. (eds.): Smart Packaging Technologies for Fast Moving Consumer Goods. John Wiley & Sons, New York (2008)
Kho, J.S., Jeong, J.: On reflecting optimal inventory of profit and loss perspective for production planning. Procedia Comput. Sci. 155, 722–727 (2019)
Unver, H.O.: An ISA-95-based manufacturing intelligence system in support of lean initiatives. Int. J. Adv. Manuf. Technol. 65(5–8), 853–866 (2013)
Hao, Y., et al.: Designing of cloud-based virtual factory information system. In: Advances in Sustainable and Competitive Manufacturing Systems, pp. 415–426. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-319-00557-7_34
Ge, Z.: Distributed predictive modeling framework for prediction and diagnosis of key performance index in plant-wide processes. J. Process Control 65, 107–117 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Kho, J.S., Jeong, J. (2020). System Integration and Functional Priorities to Maximize Profit and Loss for Smart Factory. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12253. Springer, Cham. https://doi.org/10.1007/978-3-030-58814-4_49
Download citation
DOI: https://doi.org/10.1007/978-3-030-58814-4_49
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-58813-7
Online ISBN: 978-3-030-58814-4
eBook Packages: Computer ScienceComputer Science (R0)