Research Article
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A Decision Support System For An Assignment and Rebalancing Problem in The Absence Of Staff

Year 2021, Volume: 3 Issue: 1, 192 - 220, 15.07.2021
https://doi.org/10.47898/ijeased.817062

Abstract

In today's intense competition environment, enterprises must use their production resources effectively in order to sustain their assets. The importance of this issue is increasing day by day. For this reason, enterprises are working to manage their resources in the best way with various methods. One of the most important sources for businesses is labor. It is necessary to make effective use of human factor in labor intensive enterprises. In addition, absence in the business is very common. In this study, a mathematical model was firstly proposed in order to assign the appropriate personnel instead of daily absentee staff in an automotive supplier industry and to distribute the work if necessary; afterwards, in order to answer the needs of the enterprise, the Decision Support System (DSS) has been designed. In the event that the personnel does not come to work in the operation with the proposed DSS, the most authorized personnel is assigned to the relevant work stations and the work is shared to the other stations where necessary. Therefore, with a systematic process management, sustaining of standard production and minimizing the losses which may occur are aimed.

Supporting Institution

Nursan Kablo Donanımları San. Tic. A.Ş

Project Number

1

Thanks

The authors would like to acknowledge the Nursan Kablo Donanımları A.Ş. involved in this research for the collaboration and support.

References

  • Aktaş, E., Ülengin, F. ve Önsel Şahin, Ş. (2007). A Decision Support System To Improve The Efficiency Of Resource Allocation In Healthcare Management, Socio-Economic Planning Sciences, 41, pp. 130-146.
  • Bulut, A. (2019). A Decision support system for an assignment and rebalancing problem in the absence of staff: A case study, Unpublished Master's Thesis (Supervisor Kırış, Ş.), Dumlupınar University Institute of Science, Kütahya.
  • Çetinyokuş, T., Gökçen, H. (2008). A decision support system and application for employee performance evaluation, Gazi Univ. Eng. Mime. Fak. Der. J. Fac. Eng. Arch. Gazi Univ. 23 (1), pp. 239-248.
  • De Bruecker, P., van den Bergh, J., Beliën, J. ve Demeulemeester, E. (2014). Workforce Planning Incorporating Skills: State Of The Art, European Journal of Operations Research, 243, 1‐16.
  • Dolgui, A., Kovalev, S., Kovalyov, M. Y., Malyutin, S., Soukhal, A. (2018). Optimal workforce assignment to operations of a paced assembly line”, European Journal of Operational Research 24(1), pp. 200-211.
  • Gomes da Silva, C., Figueira, J., Lisboa, J. ve Barman, S. (2006). An Interactive Decision Support System For An Aggregate Production Planning Model Based On Multiple Criteria Mixed Integer Linear Programming, Omega, 34(2), pp. 167–177.
  • Harjunkoski, I., Maravelias, C. T., Bongers, P., Castro, P. M., Engell, S. ve Grossmann, I. E. (2014). Scope For Industrial Applications Of Production Scheduling Models And Solution Methods, Computers and Chemical Engineering, 62, pp. 161–193.
  • Hidri, L., Labidi, M. (2016). Optimal physicians schedule in an Intensive Care Unit, IOP Conf. Series: Materials Science and Engineering 131, pp. 1-8 .
  • Johnes, J. (2015). Operational Research In Education, European Journal of Operations Research, 243 (3), pp. 683–696.
  • Li, G., Jiang, H. ve He, T. (2015). A Genetic Algorithm-based Decomposition Approach To Solve An Integrated Equipment-workforce-service Planning Problem, Omega, 50, pp. 1–17.
  • Polat, O., Mutlu, Ö., ve Özgörmüş, E. (2018). A Mathematical Model For Assembly Line Balancing Problem Type 2 Under Ergonomic Workload Constraint, The Ergonomics Open Journal, 11(1).
  • Sadjadi, S. J., Soltani, R., Izadkhah, M., Saberian, F. ve Darayi, M. (2011). A New Nonlinear Stochastic Staff Scheduling Model, Scientia Iranica,18(3), pp. 699–710.
  • Smet, P., Wauters, T., Mihaylov, M. ve Vanden Berghe, G. (2014). The Shift Minimisation Personnel Task Scheduling Problem: A New Hybrid Approach And Computational Insights, Omega, 46, pp. 64–7.3
  • Varlı, E., Eren, T. (2017). Hemşire Çizelgeleme Problemi ve Bir Hastanede Uygulama, Akademik Platform Mühendislik ve Fen Bilimleri Dergisi, 5(1), pp. 34-40.
  • Wong, T. C., Xu, M. ve Chin, K. S. (2014). A Two‐stage Heuristic Approach For Nurse Scheduling Problem: A Case Study In An Emergency Department, Computers and Operations Research, 51, pp. 99.

Personel Devamsızlığında Atama ve Dengeleme Problemi için Karar Destek Sistemi

Year 2021, Volume: 3 Issue: 1, 192 - 220, 15.07.2021
https://doi.org/10.47898/ijeased.817062

Abstract

Günümüzün yoğun rekabet ortamı içerisinde işletmelerin varlıklarını sürdürebilmeleri için üretim kaynaklarını etkin bir şekilde kullanmaları gerekmektedir. Gün geçtikçe bu konunun önemi daha da artmaktadır. Bu nedenle işletmeler, çeşitli yaklaşımlar ile kaynaklarını en iyi şekilde yönetebilmek adına çalışmalar yapmaktadırlar. İşletmeler için en önemli kaynaklardan birisi iş gücüdür. Emek yoğun çalışan işletmelerde insan faktöründen etkin olarak faydalanmak gerekmektedir. Bunun yanında işletmelerde işe gelmeme durumuyla da çok sık karşılaşılmaktadır. İşe gelmeyen personelin yerine çalışacak personelin atanması, özellikle küçük ve orta büyüklükteki işletmelerde, işletme yöneticilerinin kişisel görüşlerine göre yapılmakta olup, genellikle istenilen hedeflere ulaşılamamakta ve görünmeyen kayıplar oluşmaktadır. Bu çalışmada bir otomotiv yan sanayi işletmesinde günlük devamsızlık yapan personelin yerine uygun personelin atanması ve gerekli ise işlerin dağıtılması için öncelikle bir matematiksel model önerilmiş, ardından işletme ihtiyaçlarına daha rahat cevap verebilmesi amacıyla bir Karar Destek Sistemi (KDS) tasarlanmıştır. Önerilen KDS ile işletmede personelin işe gelmemesi durumunda ilgili çalışma istasyonlarına, mevcut ekip içerisinden en yetkin personel atanmakta ve gerekli durumlarda da işler diğer istasyonlara paylaştırılmaktadır. Böylece sistematik bir süreç yönetimi ile oluşabilecek kayıpların en küçüklenmesi ve standart üretimin devam etmesi amaçlanmaktadır.

Project Number

1

References

  • Aktaş, E., Ülengin, F. ve Önsel Şahin, Ş. (2007). A Decision Support System To Improve The Efficiency Of Resource Allocation In Healthcare Management, Socio-Economic Planning Sciences, 41, pp. 130-146.
  • Bulut, A. (2019). A Decision support system for an assignment and rebalancing problem in the absence of staff: A case study, Unpublished Master's Thesis (Supervisor Kırış, Ş.), Dumlupınar University Institute of Science, Kütahya.
  • Çetinyokuş, T., Gökçen, H. (2008). A decision support system and application for employee performance evaluation, Gazi Univ. Eng. Mime. Fak. Der. J. Fac. Eng. Arch. Gazi Univ. 23 (1), pp. 239-248.
  • De Bruecker, P., van den Bergh, J., Beliën, J. ve Demeulemeester, E. (2014). Workforce Planning Incorporating Skills: State Of The Art, European Journal of Operations Research, 243, 1‐16.
  • Dolgui, A., Kovalev, S., Kovalyov, M. Y., Malyutin, S., Soukhal, A. (2018). Optimal workforce assignment to operations of a paced assembly line”, European Journal of Operational Research 24(1), pp. 200-211.
  • Gomes da Silva, C., Figueira, J., Lisboa, J. ve Barman, S. (2006). An Interactive Decision Support System For An Aggregate Production Planning Model Based On Multiple Criteria Mixed Integer Linear Programming, Omega, 34(2), pp. 167–177.
  • Harjunkoski, I., Maravelias, C. T., Bongers, P., Castro, P. M., Engell, S. ve Grossmann, I. E. (2014). Scope For Industrial Applications Of Production Scheduling Models And Solution Methods, Computers and Chemical Engineering, 62, pp. 161–193.
  • Hidri, L., Labidi, M. (2016). Optimal physicians schedule in an Intensive Care Unit, IOP Conf. Series: Materials Science and Engineering 131, pp. 1-8 .
  • Johnes, J. (2015). Operational Research In Education, European Journal of Operations Research, 243 (3), pp. 683–696.
  • Li, G., Jiang, H. ve He, T. (2015). A Genetic Algorithm-based Decomposition Approach To Solve An Integrated Equipment-workforce-service Planning Problem, Omega, 50, pp. 1–17.
  • Polat, O., Mutlu, Ö., ve Özgörmüş, E. (2018). A Mathematical Model For Assembly Line Balancing Problem Type 2 Under Ergonomic Workload Constraint, The Ergonomics Open Journal, 11(1).
  • Sadjadi, S. J., Soltani, R., Izadkhah, M., Saberian, F. ve Darayi, M. (2011). A New Nonlinear Stochastic Staff Scheduling Model, Scientia Iranica,18(3), pp. 699–710.
  • Smet, P., Wauters, T., Mihaylov, M. ve Vanden Berghe, G. (2014). The Shift Minimisation Personnel Task Scheduling Problem: A New Hybrid Approach And Computational Insights, Omega, 46, pp. 64–7.3
  • Varlı, E., Eren, T. (2017). Hemşire Çizelgeleme Problemi ve Bir Hastanede Uygulama, Akademik Platform Mühendislik ve Fen Bilimleri Dergisi, 5(1), pp. 34-40.
  • Wong, T. C., Xu, M. ve Chin, K. S. (2014). A Two‐stage Heuristic Approach For Nurse Scheduling Problem: A Case Study In An Emergency Department, Computers and Operations Research, 51, pp. 99.
There are 15 citations in total.

Details

Primary Language English
Subjects Industrial Engineering
Journal Section Research Articles
Authors

Abdurrahim Bulut 0000-0003-0737-9394

Şafak Kırış 0000-0002-7041-4722

Project Number 1
Publication Date July 15, 2021
Submission Date October 27, 2020
Published in Issue Year 2021 Volume: 3 Issue: 1

Cite

APA Bulut, A., & Kırış, Ş. (2021). A Decision Support System For An Assignment and Rebalancing Problem in The Absence Of Staff. Uluslararası Doğu Anadolu Fen Mühendislik Ve Tasarım Dergisi, 3(1), 192-220. https://doi.org/10.47898/ijeased.817062