Sustainability performance measurement for Libyan Iron and Steel Company using Rough AHP
DOI:
https://doi.org/10.31181/jdaic1001202222bAbstract
The iron and steel industry plays a major role in Libyan urbanization. Iron and steel products are the main driving forces in the construction manufacturing sector in Libya. This research suggested a set of indicators to evaluate the sustainability of the iron and steel industry in Libya using a rough AHP model. Rough AHP analyses the relative importance of the criteria based on their preferences given by experts. The research results show that the most important criterion is costs followed by emission and waste. We have found that the rough AHP model can play an important role in improving indicators that quantify the advance towards sustainable development, especially when it is in a situation where complex environments (i.e., Libya) exist.
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Durmić, E. (2019). Evaluation of criteria for sustainable supplier selection using FUCOM method. Operational Research in Engineering Sciences: Theory and Applications, 2, 91-107.
Fleiter, T., Hirzel, S. & Worrell, E. (2012). The characteristics of energy-efficiency measures–a neglected dimension. Energy policy, 51, 502-513.
Fruehan, R. (2009). Research on sustainable steelmaking. Metallurgical and Materials Transactions B, 40, 123-133.
Rynikiewicz, C. (2008). The climate change challenge and transitions for radical changes in the European steel industry. Journal of Cleaner Production. 16, 781-789.
Naylor, D. (2005). Sustainability of ferrous metallurgy and the steel industry. Ironmaking & Steelmaking, 32, 97-100.
Singh, R. K., Murty, H. Gupta, S. & Dikshit, A. (2007) Development of composite sustainability performance index for steel industry. Ecological Indicators, 7, 565-588.
FU, B. HUANG, J., ZHANG, L., WANG, L. & LIU, P. (2012). Research on wastes emission standard and development trend in iron and steel industry in China. Wuhan Iron and Steel Corporation Technology, 6.
Zhang, B., Wang, Z., Yin, J., & Su, L. (2012). CO2 emission reduction within Chinese iron & steel industry: practices, determinants and performance. Journal of Cleaner Production, 33, 167-178.
Shetwan, A., Aifa, A. & Badi, I. (2018). Cost Minimization of Liquid Steel Production in Libyan Iron and Steel Company. The international journal of engineering and information technology. 5, 28-35.
Taib, M. (2011). The mineral industry of Libya. Minerals Yearbook Area Reports: International Review, Africa and the Middle East, 20.
Burchart-Korol, D. (2013). Life cycle assessment of steel production in Poland: a case study. Journal of Cleaner Production, 54, 235-243.
Florén, H., Frishammar, J. Löf, A. & Ericsson, M. (2018). Raw materials management in iron and steelmaking firms. Mineral Economics, 1-9.
Goffin, K. Szwejczewski, M. & C. New, C. (1997). Managing suppliers: when fewer can mean more. International Journal of Physical Distribution & Logistics Management, 27, 422-436.
De Boer, L. Labro, E. & Morlacchi, P. (2001). A review of methods supporting supplier selection. European journal of purchasing & supply management, 7, 75-89.
Govindan, K., Rajendran, S., Sarkis, K. & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66-83.
Chai, J., Liu, J. & Ngai, E. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications,. 40, 3872-3885.
Prakash, S., Soni, G. & Rathore, A. (2015). A grey based approach for assessment of risk associated with facility location in global supply chain. Grey Systems: Theory and Application, 5, 419-436.
Badi, I., Abdulshahed, A. & Shetwan, A. (2018). A case study of supplier selection for a steelmaking company in Libya by using the Combinative Distance-based ASsessment (CODAS) model. Decision Making: Applications in Management and Engineering, 1, 1-12.
Abdulshahed, A., Badi, I. & Blaow, M. (2017). A grey-based decision-making approach to the supplier selection problem in a steelmaking company: a case study in Libya. Grey Systems: Theory and Application, 7, 385-396.
Badi, I. & Pamucar, D. (2020). Supplier selection for steelmaking company by using combined Grey-MARCOS methods. Decision Making: Applications in Management and Engineering, 3, 37-48.
Liang, W., Huang, C., Lin, Y., Chang, T. & and Shih, M. (2013). The multi-objective label correcting algorithm for supply chain modeling. International Journal of Production Economics, 142, 172-178.
Ghodsypour, S & O'Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal of Production Economics, 56, 199-212.
Porras-Alvarado, J., Murphy, M., Wu, H., Han, Z. Zhang, Z. & and Arellano, M. (2017). An Analytical Hierarchy Process to Improve Project Prioritization in the Austin District. in Transportation Research Board 96th Annual Meeting.
Badi, I & Abdulshahed, A. (2019). Ranking the Libyan airlines by using full consistency method (FUCOM) and analytical hierarchy process (AHP). Operational Research in Engineering Sciences: Theory and Applications, 2, 1-14.
Saaty, T. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48, 9-26.
Saaty, T. (1979). Applications of analytical hierarchies. Mathematics and Computers in Simulation, 21, 1-20.
Chan F. & Chan, H. (2004). Development of the supplier selection model—a case study in the advanced technology industry. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 218, 1807-1824.
Chan, F., Chan, H., Ip, R. & Lau, H. (2007). A decision support system for supplier selection in the airline industry Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 221, 741-758.
Jiang, P., Fukuda, S., Hou, J. & Su, D. (2007). EJB-MVC oriented supplier selection system for mass customization. Journal of Manufacturing Technology Management, 18, 54-71.
Kuo, R., Chi, S. & Kao, S. (2002). A decision support system for selecting convenience store location through integration of fuzzy AHP and artificial neural network. Computers in Industry, 47, 199-214.
Jain, V., Sangaiah, A., Sakhuja, S., Thoduka, N. & Aggarwal, R. (2016). Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural Computing and Applications, 1-10.
Gold, S. & Awasthi, A. (2015). Sustainable global supplier selection extended towards sustainability risks from (1+ n) th tier suppliers using fuzzy AHP based approach. IFAC-PapersOnLine, 48, 966-971.
Liang, X., Wang, X., Shu, G., Wei, H., Tian, H. & Wang, X. (2015). A review and selection of engine waste heat recovery technologies using analytic hierarchy process and grey relational analysis. International Journal of Energy Research, 39, 453-471.
Yang C. & Chen, B. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis. Journal of Manufacturing Technology Management, 17, 926-941.
Bali, O., Kose, E. & Gumus, S. (2013). Green supplier selection based on IFS and GRA. Grey Systems: Theory and Application, 3, 158-176.
Zakeri, S. & Keramati, M. (2015). Systematic combination of fuzzy and grey numbers for supplier selection problem. Grey Systems: Theory and Application, 5, 313-343.
Roy, J., Adhikary, K., Kar, S. & Pamucar, D. (2018). A rough strength relational DEMATEL model for analysing the key success factors of hospital service quality. Decision Making: Applications in Management and Engineering, 1, 121-142.
Vasiljević, V., Fazlollahtabar, H., Stević, Z. & Vesković, S. (2018). A rough multicriteria approach for evaluation of the supplier criteria in automotive industry. Decision Making: Applications in Management and Engineering, 1, 82-96.
Zhai, L., Khoo, L. & Zhong, Z. (2009). A rough set based QFD approach to the management of imprecise design information in product development. Advanced Engineering Informatics, 23, 222-228.
Zhai, L., Khoo, L. & Zhong, Z. (2008). A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 37, 613-624.
Song, W., Ming, X. & Wu, Z. (2013). An integrated rough number-based approach to design concept evaluation under subjective environments. Journal of Engineering Design, 24, 320-341.
Pamučar, D., Stević, Z. & Zavadskas, E. K. (2018). Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages. Applied Soft Computing, 67, 141-163.
Zhu, G., Hu, J., Qi, J., Gu, C. & Peng, Y. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29, 408-418.
Stanković, M., Gladović, P. & Popović, V. (2019). Determining the importance of the criteria of traffic accessibility using fuzzy AHP and rough AHP method. Decision Making: Applications in Management and Engineering, 2, 86-104.
Stević, Z., Tanackov, I., Vasiljević, M. & Rikalović, A. (2017). Supplier evaluation criteria: AHP rough approach. in XVII International scientific conference on industrial systems, Novi Sad, 298-303.
Stevic, Z., Badi, I., Tanackov, I. & Milicic, G. (2017). Supplier selection in furniture production company using rough AHP and rough TOPSIS. VI International symposium of transport and communications, Serbia.
Bhattacharya, A., Mohapatra, P., Kumar, V., Dey, P. et al., (2014). Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach. Production Planning & Control, 25, 698-714.
Long, Y., Pan, J., Farooq, S. & Boer, H. (2016). A sustainability assessment system for Chinese iron and steel firms. Journal of Cleaner Production, 125, 133-144.
Strezov, V., Evans, A. & Evans, T. (2013). Defining sustainability indicators of iron and steel production Journal of cleaner production, 51,. 66-70.
Pan, H., Zhang, X., Wu, J., &Yang, G. (2016). Sustainability evaluation of a steel production system in China based on emergy. Journal of cleaner production, 112, 1498-1509.
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