An Integrated Enterprise Resources Planning (ERP) Framework forFlexible Manufacturing SystemsUsing Business Intelligence (BI)Tools

Document Type: Research Paper


Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran


Nowadays Business intelligence (BI) tools provide optimal decision making, analyzing, controlling and monitoring of operations in enterprise systems like enterprise resource planning (ERP) and mainly refer to strong decision making methods used in online analytical processing, reporting and data analysis, such as improve internal processes, analysis of resources, information needs analysis, reduce costs and increase revenue. The main purpose of paper is creating a unified framework for the application of BI in ERP systems which results of value-added inflexible manufacturing systems (FMS). In this paper, business process system and interaction between technology and environment byapplying BI in ERPsystems of companies that use flexible manufacturing systems have been presented. This paper is a comprehensive review of recent literature that examined the effects of BI systems on the fourlevels of Tenhialaet al.' Model (2015).This model based on cross-sectional data from 151 manufacturing plants proved that ERP is essential for the FMS. According to results of this paper, the answer to this question is important “How can we use the potential data, and intelligence of BI in ERP systems for the effective flexible manufacturing systems?” This study has four hypotheses to answer this question and based on results, all four hypotheses were confirmed. Finally, a model has been developed to determine the relationship between BI (as enabler of ERP) and FMS.


Main Subjects

Azma. F. and Mostafapour. M. A., (2012). Business intelligence as a key strategy for development organizations. Procedia Technology, Vol. 1, pp. 102-106.

Cheng. H., Lu. Y. C., and Sheu. C., (2009). An ontology-based business intelligence application in a financial knowledge management system, Expert Systems with Applications, Vol. 36(2), pp. 3614-3622.

Cochran. W. G., (1977). Sampling techniques (3rd ed.), New York: John Wiley & Sons.

Collins. R.S., Schmenner. R., (1993). Achieving rigid flexibility: Factory focus for the 1990s, European Management Journal, Vol. 11 (4), pp. 443-447.

Elbashir. M. Z., Collier. P. A. and Davern. M. J., (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, Vol. 9(3), pp. 135-153.

Ghazanfari. M., Jafari. M. and Rouhani. S., (2011). A tool to evaluate the business intelligence of enterprise systems, Scientia Iranica, Vol. 18 (6), pp. 1579–1590.

Goodale. J.C., Kuratko. D.F., Hornsby. J.S. and Covin. J.G., (2011). Operations management and corporate entrepreneurship: The moderating effect of operations control on the antecedents of corporate entrepreneurial activity in relation to innovation performance, Journal of Operations Management, Vol. 29 (1-2), pp. 116-127.

Gosling. J., Purvis. L., Naim. M. M., (2010). Supply chain flexibility as a determinant of supplier selection, International Journal of Production Economics, Vol. 128 (1), pp. 11–21.

Huang. X., Kristal. M. M., Schroeder. R. G., (2010). The impact of organizational structure on mass customization capability: A contingency view, Production and Operations Management, Vol. 19 (5), pp. 515-530.

Jacobs. M., (2008). Product Complexity: Theoretical Relationships to Demand and Supply Chain Costs, Publisher: ProQuest LLC.

Jiang. P., Zhang. C., Leng. J. and Zhang. J., (2015). Implementing a WebAPP-based Software Framework for Manufacturing Execution Systems, IFAC-PapersOnLine, Vol. 48 (3), pp. 388–393.

Jiang. W., (2014).Business Partnerships and Organizational Performance: The Role of Resources and Capabilities (Contributions to Management Science), Publisher: Springer-Verlag Berlin Heidelberg, 2014th Edition, DOI: 10.1007/978-3-642-53989-3.

Kahraman. C., Kaya. I. and Çevikcan. E., (2011). Intelligence decision systems in enterprise information management. Journal of Enterprise Information Management, Vol. 24(4), pp. 360-379.

Kelle. P. and Akbulut. A., (2005). The role of ERP tools in supply chain information sharing, cooperation, and cost optimization, International Journal of Production Economics, Vol. 93–94, pp. 41–52.

Liao. X., Li. Y., and Lu. B., (2007). A model for selecting an ERP system based on linguistic information processing, Information Systems, Vol. 32 (7), pp. 1005–1017.

Lubbe. R. H., Schölvincka. M. L., Kenemans. L. J. and Postma. A., (2006). Divergence of categorical and coordinate spatial processing assessed with ERPs, Neuropsychologia, Vol. 44 (9), pp. 1547–1559.

Mohammadi. M., Jafari. N., (2010).A new mathematical model for integrating lot sizing, loading, and scheduling decisions in flexible flow shops, The International Journal of Advanced Manufacturing Technology, Vol. 55 (5), pp. 709-721.

Movahedi. M. M. and Nouri Koupaei. M., (2011).A Framework for Applying ERP in Effective Implementation of TQM, Middle-East Journal of Scientific Research, Vol. 10 (4), pp. 489-495.

Naderi. B., Azab. A., (2015).Modeling and scheduling a flexible manufacturing cell with parallel processing capability, CIRP Journal of Manufacturing Science and Technology, Vol. 11, pp. 18-27.

Popovič. A., Turk. T. and Jaklič. J., (2010). Conceptual model of business value of business intelligence systems. Management: Journal of Contemporary Management, Vol.15 (1), pp. 5-30.

Powell. D., Alfnes. E., Strandhagen. J. O. and Dreyer. H., (2013). The concurrent application of lean production and ERP: Towards an ERP-based lean implementation process, Computers in Industry, Vol. 64 (3), pp. 324–335.

Rafie-Majd. Z., Mohammadi. M., Naderi. B., (2015).Solving the Multi-objective flexible job shop scheduling problem by the population-based algorithms, Applied mathematics in Engineering, Management and Technology, Vol. 3(2), pp. 148-155.

Sancheza. A., Oliveira. N., Barbosa. L. S., Henriques. P., (2015).A perspective on architectural re-engineering, Science of Computer Programming, Vol. 98 (4), pp. 764–784.

Sprock. T. and McGinnis. L. F., (2015). A Conceptual Model for Operational Control in Smart Manufacturing Systems, IFAC-PapersOnLine, Vol. 48 (3), pp. 1865–1869.

Tenhiala. A. and Helkio. P., (2015). Performance effects of using an ERP system for manufacturing planning and control under dynamic market requirements, Journal of Operations Management, Vol. 36, pp. 147–164.

Wang. T. G. and Chen. H. F., (2006). The influence of governance equilibrium on ERP project success, Decision Support Systems, Vol. 41 (4), pp. 708–727.

Wisdom Source, (2004). Knowledge management maturity (K3M), Wisdom source News, Vol. 2(1).

Worley. J. H., Chatha. K. A., Weston. R. H., Aguirre. O. and Grabot. B., (2005). Implementation and optimization of ERP systems: A better integration of processes, roles, knowledge and user competencies, Computers in Industry, Vol. 56(6), pp. 620–638.

Zali. M. R., Najafian. M., Colabi. A., (2014).System Dynamics Modeling in Entrepreneurship Research: A Review of the Literature, International Journal of Supply and Operations Management, Vol. 1 (3), pp. 347-370.

Zhang. D., Linderman. K., Schroeder. R. G., (2012). The moderating role of contextual factors on quality management practices, Journal of Operations Management, Vol. 30 (1-2), pp. 12-23.