Skip to main content

Decision Support Tool for Manufacturing Execution Systems: Case Study from the Steel Industry

  • Conference paper
  • First Online:
Advanced Intelligent Systems for Sustainable Development (AI2SD’2020) (AI2SD 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1417))

  • 980 Accesses

Abstract

The acquisition of a business software solution is a very strategic project for companies. It is a process that involves many stakeholders, internal and external ones, and last for a couple months. The aim of our study is to develop a decision support tool for the evaluation of different Manufacturing Execution System (MES) solution alternatives for a company operating in the steel industry. The tool is based on a Multi Criteria Decision Making (MCDM) method called PAPRIKA. The competing solutions/suppliers were evaluated based on criteria related to the different solution functionalities, market references, Industry Expertise, Ease of Use and Ease of Integration. In order to make the process much convenient for the company subject to our case study, we used a software solution that implemented PAPRIKA. The ranking of the different competing solutions was provided and different criteria weights were calculated. Moreover, the performance of each solution against each criterion has also been demonstrated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    www.mesa.org.

  2. 2.

    www.1000minds.com.

References

  1. Akabane, G.K., Souza, C.P., Paulo, S., Marins, F.A.S.: Contributions of MES (Manufacturing Execution System) to improve manufacturing competitive priorities. Indep. J. Manag. Prod.  6(10) (2015). https://doi.org/10.14807/ijmp.v6i2.233

  2. Arica, E., Powell, D.J.: Status and future of manufacturing execution systems. In: 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, pp. 2000–2004. IEEE (2017)

    Google Scholar 

  3. Bhole, G.P.: Multi criteria decision making (MCDM) methods and its applications. IJRASET 6, 899–915 (2018). https://doi.org/10.22214/ijraset.2018.5145

  4. Chen, K.Y.: Performance measurement of implementing manufacturing execution system. In: Materials Science Forum, vol. 505–507, pp. 1117–1122 (2006)

    Google Scholar 

  5. Franzosa, R.: Magic quadrant for manufacturing execution systems. 35 (2017). https://www.gartner.com/en/documents/3833664/magic-quadrant-for-manufacturing-execution-systems   

  6. Hansen, P., Ombler, F.: A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives. J. Multi-Crit. Decis. Anal. 15, 87–107 (2008). https://doi.org/10.1002/mcda.428

    Article  Google Scholar 

  7. Kolios, A., Mytilinou, V., Lozano-Minguez, E., Salonitis, K.: A comparative study of multiple-criteria decision-making methods under stochastic inputs. Energies 9, 566 (2016). https://doi.org/10.3390/en9070566

    Article  Google Scholar 

  8. Mahmoud, M.I., Ammar, H.H., Hamdy, M.M., Eissa, M.H.: Production operation management using manufacturing execution systems (MES). In: 2015 11th International Computer Engineering Conference (ICENCO), Cairo, Egypt, pp. 111–116. IEEE (2015)

    Google Scholar 

  9. Mustajoki, J., Marttunen, M.: Comparison of multi-criteria decision analytical software for supporting environmental planning processes, Environ. Model. Softw. 93, 78–91 (2013). https://doi.org/10.1016/j.envsoft.2017.02.026

  10. Ratkevicius, D., Ratkevicius, C., Skyrius, R.: ERP selection criteria: Theoretical and practical views. Ekonomika 91, 20 (2012). https://doi.org/10.15388/Ekon.2012.0.893 

  11. Rosner, D., Meyuhas, A.: The Best MES Selection Process & Benchmark Survey for a Semiconductor Fab Case Study. 4 (2012)

    Google Scholar 

  12. Senvar, O., Tuzkaya, G., Kahraman, C.: Multi criteria supplier selection using fuzzy PROMETHEE method. In: Kahraman, C., Öztayşi, B. (eds.) Supply Chain Management Under Fuzziness. SFSC, vol. 313, pp. 21–34. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-53939-8_2

    Chapter  Google Scholar 

  13. Teknomo, K.: Analytical Hierarchy Process (AHP) Tutorial (2006). https://people.revoledu.com/kardi/tutorial/AHP

  14. Thokala, P., et al.: Multiple criteria decision analysis for health care decision making—an introduction: report 1 of the ISPOR MCDA emerging good practices task force. Value Health 19, 1–13 (2016). https://doi.org/10.1016/j.jval.2015.12.003

    Article  Google Scholar 

  15. Velasquez, M., Hester, P.T.: An analysis of multi-criteria decision-making methods. Int. J. Oper. Res. 10, 56–66 (2013)

    MathSciNet  Google Scholar 

  16. Wang, Q.F., Hong, C.Y.: MES system selection decision-making approach for automobile parts manufacturing enterprises. AMR 108–111, 736–740 (2010). https://doi.org/10.4028/www.scientific.net/AMR.108-111.736

    Article  Google Scholar 

  17. Yücel, M.G., Görener, A.: Decision Making for Company Acquisition by ELECTRE Method (2016). http://excelingtech.co.uk/

  18. Zhaoxu, S., Min, H.: Multi-criteria decision making based on PROMETHEE method. In: 2010 International Conference on Computing, Control and Industrial Engineering, Wuhan, China, pp. 416–418. IEEE (2010)

    Google Scholar 

  19. Introduction to multiple attribute decision-making (MADM) methods. In: Decision Making in the Manufacturing Environment. SSAM, pp. 27–41. Springer, London (2007). https://doi.org/10.1007/978-1-84628-819-7_3

  20. https://www.cgi.com/en/manufacturing/manufacturing-execution-systems

  21. Sevkli, M.: An application of the fuzzy ELECTRE method for supplier selection. Int. J. Prod. Res. 48, 3393–3405 (2010). https://doi.org/10.1080/00207540902814355

    Article  MATH  Google Scholar 

Download references

Acknowledgment

The author would like to express his deep gratitude to Mr. Paul Hansen and all 1000minds.com team for their support and assistance.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adil Aramja .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aramja, A., Kamach, O. (2022). Decision Support Tool for Manufacturing Execution Systems: Case Study from the Steel Industry. In: Kacprzyk, J., Balas, V.E., Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2020). AI2SD 2020. Advances in Intelligent Systems and Computing, vol 1417. Springer, Cham. https://doi.org/10.1007/978-3-030-90633-7_35

Download citation

Publish with us

Policies and ethics