Smoothing Short Duration Capacity Problems in Enterprise Resource Planning (ERP) Systems: An Algorithmic Approach

Abstract:

Successful implementation of ERP systems should take full advantage of the access to information, but not be constrained by many of the deficiencies associated with infinite capacity scheduling methodologies. In this paper an algorithm is developed which improves the performance of the ERP system. Lot sizing decisions based on capacity availability are used as an instrument to integrate more effectively capacity requirements planning (CRP) and Material Requirements Planning (MRP). MRP is a planning tool for a sub-set of manufacturing system specially in hierarchal multi-product, multi-period and multi-stage production planning and inventory control system. The Vehicle used for this integration is planned order release (POR) quantity. The algorithm requires minimal deviation from the MRP logic. In this sequential process MRP first issues the action notices and then the algorithm analyses the capacity situation in the work centers. The algorithm scans all planned order release quantities of lower level items in the action bucket before orders are released to the shop. For each item a delta value is computed identifying the degree orders are contributing to capacity problems. This delta is specific to each POR. The POR causing the highest overload and the one passing through the lowest utilized work centers are selected for a lot size decrease, respectively, an increase. After identifying the candidates, a series of checks analyses the suitability of the candidates for that change. The planned order release quantities of more items can be performed. Projected capacity profile after iteration will be updated and capacity requirements over a short duration are smoothed. The experiments are performed with MAP/3000 as a simulation model for this study. The developed algorithm is added to MAP/3000 as additional subroutines. The design of the experiments consists of a base test identifying the significance of different environmental parameters of MRP systems and a main test which performs a detailed evaluation. The results are evaluated using analysis of variance techniques. Most ERP systems built on the historical development of MRP and CRP systems, and the assumption of infinite capacity is affecting the performance of those systems badly. This paper is presenting an algorithm to smooth capacity problems by using the existed capacity.

• Periodical: Advanced Materials Research (Volume 933)
• Pages: 860-868
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.933.860
• Online since: May 2014
• Authors: Muneam Zamzeer Al-Magsoosi*
• Keywords: Algorithm (GA), CRP, ERP, MAP/3000, MRP, POR

References

[1] D. Gefen, , E Karahanna,., D Straub, and A. Ragowsky, A multi-level approach to measuring the benefits of an ERP system in manufacturing firms, Information Systems Management, (2005), p.18–25.

DOI: 10.1201/1078/44912.22.1.20051201/85735.3

[2] E. Umble, , R. Haft, and M. Umble,. Enterprise resource planning: Implementation procedures and critical success factors. European Journal of Operational Research, vol. 146, no. 2, (2003), pp: 241-257.

DOI: 10.1016/s0377-2217(02)00547-7

[3] F. Nah, and S. Delgado, Critical success factors for enterprise resource planning implementation and upgrade. Journal of Computer Information Systems, vol. 46, special issue, (2006), pp: 99-113.

DOI: 10.1080/08874417.2006.11645928

[4] V. Kumar, B. Maheshwari, and U. Kumar, An investigation of critical management issues in ERP implementation: empirical evidence from Canadian organizations. Technovation, vol. 23, no. 10, (2003), pp: 793-807.

DOI: 10.1016/s0166-4972(02)00015-9

[5] T. Lohand Koh, Critical elements for a successful enterprise resource planning implementation in small- and medium-sized enterprises, International Journal of Production Research vo. l42, no. 17), (2004), p.3433–3455.

DOI: 10.1080/00207540410001671679

[6] S. Shang , and P. Seddon, A comprehensive framework for assessing and managing the benefits of enterprise systems: the business manager's perspective. In: G. Shanks, P.B. Seddon and L.P. Willcocks, Editors, Second-wave Enterprise Resource Planning Systems: Implementing for Effectiveness, Cambridge University Press, UK (2003).

DOI: 10.1017/cbo9780511815072.004

[7] HYang and S. Druksler, Capacity Smoothing Factors, European Journal of Operations Research 103, 2006, pp: 130-145.

[8] P. Zhang and M. Zamzeer, An Attempt to smooth capacity load, Journal of Computer Information Systems, vol. 20, 2005, pp: 65- 80.

[9] E Duplaga,. And M. Aslani,. Implementing ERP in manufacturing, Information Systems Management, (2003), p.68–75.

[10] P. Bingi, , M. Sharma, and J. Godia, Critical issues affecting an ERP implementation, Information Systems Management 16 (3), (1999) p.7–14.

DOI: 10.1201/1078/43197.16.3.19990601/31310.2

[11] S. Bueno, and J. Salmeron, Fuzzy modeling Enterprise Resource Planning tool selection. Computer Standards and Interfaces, vol. 30, no. 3, (2008), pp: 137-147.

DOI: 10.1016/j.csi.2007.08.001

[12] V. Botta-Genoulaz, , P. Millet, and B. Grabot, A survey on the recent research literature on ERP systems. Computers in Industry, vol. 56, no. 6, (2005), pp: 510-522.

DOI: 10.1016/j.compind.2005.02.004

[13] C. Berchet, and G. Habchi,. The implementation and deployment of an ERP system: An industrial case study. Computers in Industry, vol. 56, no. 6 (2005), pp.588-605.

DOI: 10.1016/j.compind.2005.02.009

[14] M., Al-Mashari, A. Al-Mudimigh and M. Zairi, Enterprise resource planning: a taxonomy of critical factors, European Journal of Operations Research 146, (2003), p.352–364.

DOI: 10.1016/s0377-2217(02)00554-4