Optimization of e-document workflow for order calculation

Authors

DOI:

https://doi.org/10.15587/2312-8372.2018.134982

Keywords:

e-document management, order calculation, enterprise of machine-building industry, automation of enterprise management, optimization of business processes

Abstract

The object of research is automated control systems at enterprises of the machine-building industry. One of the most problematic places is the calculation of the cost of an order in the presence of a large number of orders of various types, which is typical for modern enterprises. In the course of the research, an analysis of the systems for calculating the cost of an order is carried out and the features of the formation of the order are determined at machine-building enterprises. Ways of optimization of electronic document circulation by application of the concept of use of the automated calculation of cost of the order on the basis of formation of the data on separate production units or sets are offered. The concept of calculating the cost of using each production unit for manufacturing the order provides a flexible tool for the management of the company. This allows to create an unlimited number and variety of models of technological units in an automated control system, to supplement and improve parameters for a more accurate determination of the cost of production. To do this, use directories of operations that contain information about the necessary equipment, tools, supplies, the necessary skills of workers to fulfill the order, the cost of their work and the like. The next step is the modernization of the order generation algorithm, requiring the introduction of changes in the automated enterprise management system. The proposed concept of using automated calculation of the cost of an order based on the formation of data for individual production units or sets allows to significantly reduce the cost of maintaining the planning and economic department. When ordering documentation, an analysis of available consumables is conducted, the necessary information is sent to the procurement department, the necessary equipment is selected taking into account the loading of individual devices in a certain period of time. Also, the processing time for orders and the submission of commercial offers is reduced. This opens up new opportunities for the company to participate in tender proposals and to identify the optimal variant of the offer, instantly calculating several quality-price options for manufacturing products.

Author Biography

Dmytro Nechepurenko, Zaporizhzhia National University, 66, Zhukovsky str., Zaporizhzhia, Ukraine, 69063

Postgraduate Student

Department of Business Administration and Foreign Economic Activity Management

References

  1. Nazarenko, A. (2012). Osobennosti elektronnogo dokumentooborota v mashinostroenii. Ratsional'noe Upravlenie Predpriyatiem, 2, 24–27.
  2. Shevchenko, O. V. (2015). Metodychni pidkhody do vyznachennia stratehichnykh napriamiv udoskonalennia systemy dokumentatsiinoho zabezpechennia komertsii Ukrainy. Derzhava ta rehiony. Seriia: Sotsialni komunikatsii, 2 (22), 9–16.
  3. Fabozzi, F. J., Drake, P. P., Polimeni, R. S. (Eds.). (2015). Job Order and Process Costing. The Complete CFO Handbook, 667–701. doi: http://doi.org/10.1002/9781119198055.ch21
  4. Cost Estimating, Job-Order Costing, and Activity-Based Costing. (2003). Integral Logistics Management. Boca Raton. doi: http://doi.org/10.1201/9780203488188.ch15
  5. Novak, P., Popesko, B. (2014). Cost Variability and Cost Behaviour in Manufacturing Enterprises. Economics & Sociology, 7 (4), 89–103. doi: http://doi.org/10.14254/2071-789x.2014/7-4/6
  6. Liu, Y. H. (2013). Applied Technology in the Grid Workflow Quality of Service Calculation and Estimation. Advanced Materials Research, 859, 531–536. doi: http://doi.org/10.4028/www.scientific.net/amr.859.531
  7. Rahman, H., Sarker, R., Essam, D. (2013). Permutation Flow Shop Scheduling with dynamic job order arrival. 2013 IEEE Conference on Cybernetics and Intelligent Systems (CIS), 325–331. doi: http://doi.org/10.1109/iccis.2013.6751574
  8. Muthu Palanivel, P. B., Karkuzhali, S. (2018). Automated Enterprise Resource Planning Using Total Production Control System. International Journal of Applied Engineering Research, 13 (9), 7142–7148.
  9. Iwasaki, Y., Suzuki, I., Yamamoto, M., Furukawa, M. (2012). Job-Shop Scheduling Approach to Order-Picking Problem. ASME/ISCIE 2012 International Symposium on Flexible Automation, 30–35. doi: http://doi.org/10.1115/isfa2012-7213
  10. Suteu, M. D., Mester, L.-E., Bugnar, N.-G., Andreescu, N. A., Petrica, D. M. (2016). The impact of costing methods on profitability of enterprises operating in the embroidery industry. Tekstil ve Konfeksiyon, 26 (3), 239–243.
  11. Sun, A. Y. T., Yazdani, A., Overend, J. D. (2005). Achievement assessment for enterprise resource planning (ERP) system implementations based on critical success factors (CSFs). International Journal of Production Economics, 98 (2), 189–203. doi: http://doi.org/10.1016/j.ijpe.2004.05.013
  12. Somers, T. M., Nelson, K. (2001). The impact of critical success factors across the stages of enterprise resource planning implementations. Proceedings of the 34th Annual Hawaii International Conference. Maui, 3–6. doi: http://doi.org/10.1109/hicss.2001.927129
  13. Morshchenok, T. S., Bila, A. O. (2014). Ekonomichna sutnist sobivartosti produktsii ta shliakhy znyzhennia. Ekonomichnyi visnyk Zaporizkoi derzhavnoi inzhenernoi akademii, 7, 58–65.
  14. Orlova, N., Mokhova, I. (2017). Introduction of Information Technologies in the System of Corporate Governance. Open Educational E-Environment of Modern University, 3, 355–365. doi: http://doi.org/10.28925/2414-0325.2017.3.55365

Downloads

Published

2018-01-23

How to Cite

Nechepurenko, D. (2018). Optimization of e-document workflow for order calculation. Technology Audit and Production Reserves, 3(4(41), 53–58. https://doi.org/10.15587/2312-8372.2018.134982

Issue

Vol. 3 No. 4(41) (2018): Economics of enterprises

Section

Economic Cybernetics: Original Research

License

Copyright (c) 2018 Dmytro Nechepurenko

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.