COMPUTER-AIDED MATERIAL DEMAND PLANNING USING ERP SYSTEMS AND BUSINESS INTELLIGENCE TECHNOLOGY

Wojciech DANILCZUK

danilczuk.wojciech@gmail.com
Lublin University of Technology, Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Nadbystrzycka 36, 20-618 Lublin (Poland)

Arkadiusz GOLA


Lublin University of Technology, Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Nadbystrzycka 36, 20-618 Lublin (Poland)

Abstract

Effective decision-making in industry conditions requires access and proper presentation of manufacturing data on the realised manufacturing process. Although the frequently applied ERP systems allow for recording economic events, their potential for decision support is limited. The article presents an original system for reporting manufacturing data based on Business Intelligence technology as a support for junior and middle management. As an example a possibility of utilising data from ERP systems to support decision-making in the field of purchases and logistics in  small and medium enterprises.


Keywords:

Decision Support Systems, material requirements planning, ERP, business intelligence

Alsoub, R.K., Alrawashdeh, T.A., & Althunibat, A. (2018). User acceptance for Enterprise Resource Planning Software Systems. International Journal of Innovative Computing Information and Control, 14(1), 297–307. http://doi.org/10.24507/ijicic.14.01.297
  Google Scholar

Aremu, A.Y., Shahzad, A., & Hassan, S. (2019). The Empirical Evidence of Enterprise Resource Planning System Adoption and Implementation on Firm’s Performance Among Medium-sized Enterprises. Global Business Review, UNSP 0972150919849751. http://doi.org/10.1177/0972150919849751
DOI: https://doi.org/10.1177/0972150919849751   Google Scholar

Bocewicz, G., Nielsen, I., & Banaszak, Z. (2016). Production Flows Scheduling Subject to Fuzzy Processing Time Constraints. International Journal of Computer Integrated Manufacturing, 29(10), 1105–1127. http://doi.org/10.1080/0951192X.2016.1145739
DOI: https://doi.org/10.1080/0951192X.2016.1145739   Google Scholar

Chang, Y.W. (2020). What drives organizations to switch to cloud ERP systems? The impacts of enablers and inhibitors. Journal of Enterprise Information Management, 33(3), 600–626. http://doi.org/10.1108/JEIM-06-2019-0148
DOI: https://doi.org/10.1108/JEIM-06-2019-0148   Google Scholar

Cieśla, B., & Gunia, G. (2019). Development of integrated management information systems in the context of Industry 4.0. Applied Computer Science, 15(4), 37–48. http://doi.org/10.23743/acs-2019-28
  Google Scholar

Danilczuk, W. (2019). Analiza danych produkcyjnych na podstawie transakcji w systemie ERP z wykorzystaniem technologii Business Intelligence. Autobusy – Technika, Eksploatacja, Systemy transportowe, 232(7/8), 62–65. http://doi.org/10.24136/attest.2019.192
  Google Scholar

De Oliveira, A., & De Almeida, J.R. (2019). Business Intelligence Application for Multidimensional Analysis Risks in Complex Projects. IT Professional, 21(6), 33–39. http://doi.org/10.1109/MITP.2018.2876931
DOI: https://doi.org/10.1109/MITP.2018.2876931   Google Scholar

Djiroun, R., Boukhalfa, K., & Alimazighi, Z. (2019). Designing data cubes in OLAP systems: a decision makers’ requirements-based approach. Cluster Computing – The Journal of Networks Software Tools and Applications, 22(3), 783–803. http://doi.org/10.1007/s10586-018-2883-7
DOI: https://doi.org/10.1007/s10586-018-2883-7   Google Scholar

George, A., Schmitz, K., & Storey, V.C. (2020). A Framework for Building Mature Business Intelligence and Analytics in Organizations. Journal of Database Management, 31(3), 14-39. http://doi.org/10.4018/JDM.2020070102
DOI: https://doi.org/10.4018/JDM.2020070102   Google Scholar

Gola, A. (2014). Economic aspects of manufacturing systems design. Actual Problems of Economics, 156(6), 205–212.
  Google Scholar

GUS (2020, August 7). Wykorzystanie technologii informacyjno-komunikacyjnych w jednostkach administracji publicznej, przedsiębiorstwach i gospodarstwach domowych w 2019 roku. Retrieved from https://stat.gov.pl/obszary-tematyczne/naukai-technika-spoleczenstwo-informacyjne/spoleczenstwo-informacyjne/wykorzystanietechnologii-informacyjno-komunikacyjnych-w-jednostkach-administracjipublicznej-przedsiebiorstwach-i-gospodarstwach-domowych-w-2019-roku,3,18.html
  Google Scholar

Huang, S.Y., Chiu, A.A., Chao, P.C., & Arniati, A. (2019). Critical Success Factors in Implementing Enterprise Resource Planning Systems for Sustainable Corporations. Sustainability, 11(23), 6785. http://doi.org/10.3390/su11236785
DOI: https://doi.org/10.3390/su11236785   Google Scholar

Januszewski, A. (2008). Funkcjonalność informatycznych systemów zarządzania: Tom 1 Zintegrowane systemy transakcyjne. Wydawnictwo Naukowe PWN.
  Google Scholar

Loudcher, S., Jakawat, W., Soriano Morales, E.P., & Favre, C. (2015). Combining OLAP and information networks for bibliographic data analysis: a survey. Scientometrics, 103, 471–487. http://doi.org/10.1007/s11192-015-1539-0
DOI: https://doi.org/10.1007/s11192-015-1539-0   Google Scholar

Meilin, W., Xiangwei, Z., & Qingyun, D. (2010). An Integration Methodology Based on SOA to Enable Real-Time Closed-Loop MRP between MES and ERP. 2010 International Conference on Computing, Control and Industrial Engineering, 1, 101–105. http://doi.org/10.1109/CCIE.2010.33
DOI: https://doi.org/10.1109/CCIE.2010.33   Google Scholar

Patalas-Maliszewska, J. (2012). Assessing the Impact of ERP Implementation in the Small Enterprises. Foundations of Management, 4(2), 51–62. http://doi.org/10.2478/fman2013-0010
DOI: https://doi.org/10.2478/fman-2013-0010   Google Scholar

Queiroz-Sousa, P.O., & Salgado, A.C. (2020). A review on OLAP Technologies Applied to Information Networks. ACM Transactions on Knowledge Discovery from Data, 14(1), 8. http://doi.org/10.1145/3370912
DOI: https://doi.org/10.1145/3370912   Google Scholar

Rodriguez, R., Molina-Castillo, F.J., & Svensson, G. (2020). Enterprise resource planning and business model innovation: process, evolution and outcome. European Journal of Innovation Management, 23(4), 728–752. http://doi.org/10.1108/IJIM-04-2019-0092
DOI: https://doi.org/10.1108/EJIM-04-2019-0092   Google Scholar

Sobaszek, Ł., Gola, A., & Kozłowski, E. (2018). Job-shop scheduling with machine breakdown prediction under completion time constraint. Annals of Computer Science and Information Systems, 15, 437–440. http://doi.org/10.15439/2018F83
DOI: https://doi.org/10.15439/2018F83   Google Scholar

Sobaszek, Ł., Gola, A., & Świć, A. (2020). Time-based machine failure prediction in multimachine manufacturing systems. Eksploatacja i Niezawodnosc – Maintenance and Reliability, 22(1), 52–62. http://doi.org/10.17531/ein.2020.1.7
DOI: https://doi.org/10.17531/ein.2020.1.7   Google Scholar

Świć, A., & Gola, A. (2013). Economic analysis of casing parts production in a flexible manufacturing system. Actual Problems of Economics, 141(3), 526–533.
  Google Scholar

Terkaj, W., Tolio, T., & Urgo, M. (2015). A virtual factory approach for in situ simulation to support production and maintenance planning. CIRP Annals Manufacturing Technology, 64(1), 451–454. http://doi.org/10.1016/j.cirp.2015.04.121
DOI: https://doi.org/10.1016/j.cirp.2015.04.121   Google Scholar

Vargas, M.A., & Comuzzi, M. (2020). A multi-dimensional model of Enterprise Resource Planning critical successes factors. Enterprise Information Systems, 14(1), 38–57. http://doi.org/10.1080/17517575.2019.1678072
DOI: https://doi.org/10.1080/17517575.2019.1678072   Google Scholar

Waters, D. (1996). Operations Mangement: Producing Goods and Services. Addison Wesley Longman Limited.
  Google Scholar

Yiu, L.M.D., Yeung, A.C.L., & Jong, A.P.L. (2020). Business intelligence systems and operational capability: an empirical analysis of high-tech sectors. Industrial Management & Data Systems, 120(6), 1195–1215. http://doi.org/10.1108/IMDS12-2019-0659
DOI: https://doi.org/10.1108/IMDS-12-2019-0659   Google Scholar

Zwolińska, B., Grzybowska, K., & Kubica, Ł. (2017). Shaping production change variability in relation to the utilized technology. 24th International Conference on Production Research, ICPR 2017, 155812, 51–56.
  Google Scholar

Download


Published
2020-09-30

Cited by

DANILCZUK, W. ., & GOLA, A. (2020). COMPUTER-AIDED MATERIAL DEMAND PLANNING USING ERP SYSTEMS AND BUSINESS INTELLIGENCE TECHNOLOGY. Applied Computer Science, 16(3), 42–55. https://doi.org/10.23743/acs-2020-20

Authors

Wojciech DANILCZUK 
danilczuk.wojciech@gmail.com
Lublin University of Technology, Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Nadbystrzycka 36, 20-618 Lublin Poland

Authors

Arkadiusz GOLA 

Lublin University of Technology, Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Nadbystrzycka 36, 20-618 Lublin Poland

Statistics

Abstract views: 324
PDF downloads: 17


License

Creative Commons License

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

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.


Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.