COMPUTER-AIDED MATERIAL DEMAND PLANNING USING ERP SYSTEMS AND BUSINESS INTELLIGENCE TECHNOLOGY
Wojciech DANILCZUK
danilczuk.wojciech@gmail.comLublin 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 intelligenceReferences
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
Authors
Wojciech DANILCZUKdanilczuk.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 GOLALublin University of Technology, Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Nadbystrzycka 36, 20-618 Lublin Poland
Statistics
Abstract views: 613PDF downloads: 105
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.
Most read articles by the same author(s)
- Jolanta Brzozowska, Arkadiusz Gola, COMPUTER AIDED ASSEMBLY PLANNING USING MS EXCEL SOFTWARE – A CASE STUDY , Applied Computer Science: Vol. 17 No. 2 (2021)
- Jolanta BRZOZOWSKA, Jakub PIZOŃ, Gulzhan BAYTIKENOVA, Arkadiusz GOLA, Alfiya ZAKIMOVA, Katarzyna PIOTROWSKA, DATA ENGINEERING IN CRISP-DM PROCESS PRODUCTION DATA – CASE STUDY , Applied Computer Science: Vol. 19 No. 3 (2023)
- Piotr WITTBRODT, Iwona ŁAPUŃKA, Gulzhan BAYTIKENOVA, Arkadiusz GOLA, Alfiya ZAKIMOVA, IDENTIFICATION OF THE IMPACT OF THE AVAILABILITY FACTOR ON THE EFFICIENCY OF PRODUCTION PROCESSES USING THE AHP AND FUZZY AHP METHODS , Applied Computer Science: Vol. 18 No. 4 (2022)
- Arkadiusz GOLA, Łukasz WIECHETEK, MODELLING AND SIMULATION OF PRODUCTION FLOW IN JOB-SHOP PRODUCTION SYSTEM WITH ENTERPRISE DYNAMICS SOFTWARE , Applied Computer Science: Vol. 13 No. 4 (2017)
- Wojciech DANILCZUK, THE USE OF SIMULATION ENVIRONMENT FOR SOLVING THE ASSEMBLY LINE BALANCING PROBLEM , Applied Computer Science: Vol. 14 No. 1 (2018)
Similar Articles
- Krzysztof OSTROWSKI, AN EFFECTIVE METAHEURISTIC FOR TOURIST TRIP PLANNING IN PUBLIC TRANSPORT NETWORKS , Applied Computer Science: Vol. 14 No. 2 (2018)
- Ihor PYSMENNYI, Anatolii PETRENKO, Roman KYSLYI, GRAPH-BASED FOG COMPUTING NETWORK MODEL , Applied Computer Science: Vol. 16 No. 4 (2020)
- Tilla IZSÁK, László MARÁK, Mihály ORMOS, EVALUATION OF SUPPORT VECTOR MACHINE BASED STOCK PRICE PREDICTION , Applied Computer Science: Vol. 19 No. 3 (2023)
- Fernando Andrés CEVALLOS SALAS, DIGITAL NEWS CLASSIFICATION AND PUNCTUACTION USING MACHINE LEARNING AND TEXT MINING TECHNIQUES , Applied Computer Science: Vol. 20 No. 2 (2024)
- Lubna RIYAZ, Muheet Ahmed BUTT, Majid ZAMAN, IMPROVING CORONARY HEART DISEASE PREDICTION BY OUTLIER ELIMINATION , Applied Computer Science: Vol. 18 No. 1 (2022)
- Kuppan Chetty RAMANATHAN, Manju MOHAN, Joshuva AROCKIA DHANRAJ, BACKWARD MOTION PLANNING AND CONTROL OF MULTIPLE MOBILE ROBOTS MOVING IN TIGHTLY COUPLED FORMATIONS , Applied Computer Science: Vol. 17 No. 3 (2021)
- Amina KINANE DAOUADJI, Fatima BENDELLA, IMPROVING E-LEARNING BY FACIAL EXPRESSION ANALYSIS , Applied Computer Science: Vol. 20 No. 2 (2024)
- Malek M. AL-NAWASHI , Obaida M. AL-HAZAIMEH, Mutaz Kh. KHAZAALEH , A NEW APPROACH FOR BREAST CANCER DETECTION- BASED MACHINE LEARNING TECHNIQUE , Applied Computer Science: Vol. 20 No. 1 (2024)
- Donatien Koulla Moulla, Ernest Mnkandla, Alain Abran, SYSTEMATIC LITERATURE REVIEW OF IOT METRICS , Applied Computer Science: Vol. 19 No. 1 (2023)
- Lei Liu, Eric B. Blancaflor, Mideth Abisado, A LIGHTWEIGHT MULTI-PERSON POSE ESTIMATION SCHEME BASED ON JETSON NANO , Applied Computer Science: Vol. 19 No. 1 (2023)
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
