Formulation of Qualification Criteria for Industrial Engineering Graduates as Production Supervisors in the Manufacturing Industry

Authors

  • Rahman Dwi Wahyudi Industrial Engineering Department, Universitas Surabaya
  • Evy Herowati Industrial Engineering Department, Universitas Surabaya
  • I Made Ronyastra Industrial Engineering Department, Universitas Surabaya
  • Jonathan Andersen Irawan Industrial Engineering Department, Universitas Surabaya

DOI:

https://doi.org/10.30996/heuristic.v22i2.132880

Keywords:

Competency Assessment; Industrial Engineer; Manufacturing Industry; Production Supervisor; Qualification Criteria

Abstract

The role of a production supervisor in manufacturing operations is a key factor in maintaining quality, stability, and the success of the production process. A production supervisor must maintain process effectiveness, output quality, and daily operational stability. Empirically, the scientific field that aligns with the scope of work of a production supervisor is Industrial Engineering. However, there is still a gap between the competencies of Industrial Engineering graduates and the qualifications required by companies for production supervisor positions. To fill this gap, this article aims to formulate qualification criteria for Industrial Engineering graduates interested in filling Production Supervisor positions in the manufacturing industry. The formulation of qualification criteria is based on job qualifications and requirements data from various types of manufacturers, collected through interviews with human resources department representatives and field observations. The research method used is a survey of experts experienced in the selection and development of human capital. Using the affinity diagram, the job qualifications and requirements are grouped into objective criteria, subjective criteria, and absolute requirements. Then, integrating the Pareto principle with the LINMAP method yields prominent qualification criteria. The results show that companies place the greatest emphasis on subjective qualifications, especially attitude (0,43) and software proficiency (0,43), followed by objective qualifications such as technical knowledge (0,36) and educational background (0,3).  These findings can be a basis for industry in the employee selection process and for universities in designing competency development programs and career preparation for Industrial Engineering students interested in careers as production supervisors.

 

Downloads

Download data is not yet available.

References

Setianto, “Pertumbuhan Ekonomi Indonesia Triwulan IV-2017,” Jakarta, 2018.

N. D. Pramusinto and A. Daerobi, “Labor Absorption of the Manufacturing Industry Sector in Indonesia,” Budapest Int. Res. Critics Institute-journal, vol. 3, no. 3, pp. 549–561, 2020.

A. D. Saputra, Aryani, S. Salsabila, R. P. Zalva, A. Maharani, and R. Yanuardi, “The Role of The Manufacturing on The Indonesian Economy,” Indones. J. Multidiscip. Sci., vol. 2, no. 1, pp. 157–166, 2023.

R. Haedzar P, S. Y. Kusumastuti, E. Nurfianingrum, and Syafri, “Labour Absorption in the Manufacturing Industry Sector in Central Java Province Indonesia,” Asean Int. J. Bus., no. 1, pp. 59–67, 2022.

A. Camuffo and F. Gerli, “The Competent Production Supervisor : A model for effective performance,” Massachusetts, 2005.

B. Colman and P. Willmot, “How Soft Are ‘ Soft Skills ’ in the Engineering Profession ?,” in SEFI Conference, 2016.

S. Darwish, “Mapping the job potential of the industrial engineer : a web-investigation S Darwish Management Engineering at the North West University Supervisor : Dr T Hattingh,” South Africa, 2022.

C. Bischof-dos-santos and E. De Oliveira, “Production Engineering Competencies in the Industry 4.0 context : Perspectives on the Brazilian labor market,” Production, 2020, doi: 10.1590/0103-6513.20190145.

H. Shafeek, M. Aman, and M. Marsudi, “From Traditional to Applied : A Case Study in Industrial Engineering Curriculum,” in International Conference on Advanced Information and Communication Technology for Education (ICAICTE 2013), 2013, pp. 461–470.

S. Pattanapairoj, K. Nitisiri, and K. Sethanan, “A Gap Study between Employers ’ Expectations in Thailand and Current Competence of Master ’ s Degree Students in Industrial Engineering under Industry 4 . 0,” Prod. Eng. Arch., vol. 27, no. 1, pp. 50–57, 2021, doi: 10.30657/pea.2021.27.7.

N. Chaengpromma and S. Pattanapairoj, “A gap study between industry expectations and current competencies of bachelor ’ s degree graduates in industrial engineering in Thailand 4 . 0 era : A case study of industrial engineering graduates of Khon Kaen University,” Cogent Educ., vol. 9, no. 1, 2022, doi: 10.1080/2331186X.2022.2093491.

D. I. Spang and B. C. College, “Curriculum Design and Assessment to Address the Industry Skills Gap,” in ASEE Annual Conference and Exposition, 2014.

M. I. Panjaitan, “Simple Additive Weighting ( SAW ) method in Determining Beneficiaries of Foundation Benefits,” J. Teknol. Komput., vol. 13, no. 1, pp. 19–25, 2019.

I. Al Khoiry and D. R. Amelia, “Exploring Simple Addictive Weighting (SAW) for Decision-Making,” J. INOVTEK POLBENG, vol. 8, no. 2, pp. 281–290, 2023.

R. Meri, “Simple Additive Weighting ( SAW ) Method on The Selection of New Teacher Candidates at Integrated Islamic Elementary School,” Int. J. Inf. Syst. Technol., vol. 4, no. 36, pp. 428–435, 2020.

A. Ibrahim and R. A. Surya, “The Implementation of Simple Additive Weighting ( SAW ) Method in Decision Support System for the Best School Selection in Jambi,” J. Phys. Conf. Ser., vol. 1338, pp. 1–7, 2019, doi: 10.1088/1742-6596/1338/1/012054.

A. Emrouznejad and M. Marra, “The state of the art development of AHP ( 1979 – 2017 ): a literature review with a social network analysis,” Int. J. Prod. Res., vol. 55, no. 22, pp. 6653–6675, 2017, doi: 10.1080/00207543.2017.1334976.

A. Darko, A. P. C. Chan, E. E. Ameyaw, E. K. Owusu, E. Pärn, and D. J. Edwards, “Review of Application Analytic Hierarchy Process (AHP) in Construction,” Int. J. Constr. Manag., vol. 19, no. 5, pp. 436–452, 2019, doi: https://doi.org/10.1080/15623599.2018.1452098.

E. E. Okon and O. V. Ihuoma, “On Application of E – LINMAP Model for Optimal Decision Making on Location of VIP Fast Food Restaurant in Akwa,” Sci. J. Appl. Math. Stat., vol. 4, no. 5, pp. 225–228, 2016, doi: 10.11648/j.sjams.20160405.15.

J. Wang and T. Chen, “A Novel Pythagorean Fuzzy LINMAP-Based Compromising Approach for Multiple Criteria Group Decision-Making with Preference Over Alternatives,” Int. J. of Computational Intell. Syst. Vol., vol. 13, no. 1, pp. 444–463, 2020, doi: https://doi.org/10.2991/ijcis.d.200408.001.

W. Zuo, D. Li, and G. Yu, “A General Multi-Attribute Multi-Scale Decision Making Method Based on Dynamic LINMAP for Property Perceived Service Quality Evaluation,” Technol. Econ. Dev. Econ., vol. 26, no. 5, pp. 1052–1073, 2020, doi: https://doi.org/10.3846/tede.2020.12726.

M. Ferrara, S. Rasouli, M. Khademi, and M. Salimi, “A robust optimization model for a decision-making problem : An application for stock market,” Oper. Res. Perspect., vol. 4, pp. 136–141, 2017, doi: https://doi.org/10.1016/j.orp.2017.10.001.

M. Karbasian, B. Khalili, C. Afraseab, and M. Khodadadi, “Assessing human performance influencing factors through LINMAP and Bayesian belief networks,” Sci. Iran., vol. 32, no. 4, p. 4571, 2025.

Downloads

Published

2026-01-19

How to Cite

Wahyudi, R. D., Herowati, E., Ronyastra, I. M., & Irawan, J. A. (2026). Formulation of Qualification Criteria for Industrial Engineering Graduates as Production Supervisors in the Manufacturing Industry. Heuristic, 22(2), 141–160. https://doi.org/10.30996/heuristic.v22i2.132880

Issue

Section

Articles