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Employment of Set Operations to Improve LMP Assessments Design and Implementation

Authors

  • Malek Khalaf Albezuirat (show author details)

    Malek Khalaf Albezuirat

    School of Manufacturing Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia, Malaysia

    0000-0002-0067-8327

    Corresponding author

    • Rosmaini Ahmad (show author details)

      Rosmaini Ahmad

      School of Manufacturing Engineering, Universiti Malaysia Perlis, Kampus Alam Pauh Putra, 02600 Arau, Perlis Malaysia, Malaysia

      • Muhammad Iqbal Hussain (show author details)

        Muhammad Iqbal Hussain

        School of Manufacturing Engineering, Universiti Malaysia Perlis, Kampus Alam Pauh Putra, 02600 Arau, Perlis Malaysia, Malaysia

        • Falah Mustafa Al-Saraireh (show author details)

          Falah Mustafa Al-Saraireh

          Department of Mechanical Engineering, Mutah University, Mutah, Alkarak, Jordan, Jordan

          • Asia Khalaf Albzeirat (show author details)

            Asia Khalaf Albzeirat

            Department of Math, Mutah University, Mutah, Alkarak, Jordan, Jordan

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            Albezuirat, M. K., Ahmad, R., Hussain, M. I., Al-Saraireh, F. M., & Albzeirat, A. K. (2019). Employment of Set Operations to Improve LMP Assessments Design and Implementation. SEISENSE Journal of Management, 2(1), 33-46. https://doi.org/10.33215/sjom.v2i1.56

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            Abstract

            Objective - This paper aims to provide a new mathematical model for the construction of assessment tools for Lean Manufacturing Practices (LMP) through the integration process with the set operations. This study also strives to develop key elements to enhance the effectiveness of LMP assessments and their impact through mathematical interrelationship. 

            Problem - Previous studies have shown a lack of clear mathematical methodology to carry out a rigorous assessment of the LMP effects on the firm’s operational and financial performance. Therefore, this paper tries to address this aspect by developing new equations. 

            Design - The methodology of this study is based on the conversion of the linguistic description (companies, processes, waste, practices) into numerical measurement model by integrating with set theory. 

            Finding - The results show a set of relationships and equations that can be applied to be a fundamental basis for ensuring the effectiveness of the assessment. This paper may contribute to the improvement of LMP’s design and development.

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            Copyright (c) 2019 Malek Khalaf Albezuirat, Rosmaini Ahmad, Muhammad Iqbal Hussain, Falah Mustafa Al-Saraireh, Asia Khalaf Albzeirat

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            This work is licensed under a Creative Commons Attribution 4.0 International License.

            Published in

            Vol. 2 No. 1 (2019): SEISENSE Journal of Management View Issue

            Reads, last 12 months

            2025-122026-11

            Article history

            1. ReceivedNovember 30, 2018
            2. AcceptedDecember 27, 2018
            3. Published January 1, 2019

            References

            Albzeirat, M. K., Hussain, M. I., Ahmad, R., Al-Saraireh, F. M., & Ahmad, I. (2018). A Novel Mathematical Logic for Improvement Using Lean Manufacturing Practices. Journal of Advanced Manufacturing Systems, 17(03), 391-413. Doi: 10.1142/S0219686718500233. CrossrefGoogle Scholar

            Alefari, M., Salonitis, K., & Xu, Y. (2017). The role of leadership in implementing lean manufacturing. Procedia CIRP, 63, 756-761. Doi: 10.1016/j.procir.2017.03.169. CrossrefGoogle Scholar

            Alhuraish, I., Robledo, C., & Kobi, A. (2017). A comparative exploration of lean manufacturing and six sigma in terms of their critical success factors. Journal of cleaner production, 164, 325-337. Doi: 10.1016/j.jclepro.2017.06.146. CrossrefGoogle Scholar

            Alhuraish, I., Robledo, C., & Kobi, A. (2017). A comparative exploration of lean manufacturing and six sigma in terms of their critical success factors. Journal of cleaner production, 164, 325-337. Doi: 10.1016/j.ifacol.2016.07.550. CrossrefGoogle Scholar

            Arunagiri, P., & Gnanavelbabu, A. (2014). Identification of major lean production waste in automobile industries using weighted average method. Procedia Engineering, 97, 2167-2175. CrossrefGoogle Scholar

            Chen, J. C., Cheng, C. H., & Huang, P. B. (2013). Supply chain management with lean production and RFID application: A case study. Expert Systems with Applications, 40(9), 3389-3397. Doi: 10.1016/j.eswa.2012.12.047. CrossrefGoogle Scholar

            Cil, I., & Turkan, Y. S. (2013). An ANP-based assessment model for lean enterprise transformation. The International Journal of Advanced Manufacturing Technology, 64(5-8), 1113-1130. Doi : 10.1007/s00170-012-4047-x. CrossrefGoogle Scholar

            Dora, M., Kumar, M., Van Goubergen, D., Molnar, A., & Gellynck, X. (2013). Operational performance and critical success factors of lean manufacturing in European food processing SMEs. Trends in Food Science & Technology, 31(2), 156-164. Doi: 10.1016/j.tifs.2013.03.002. CrossrefGoogle Scholar

            Fullerton, R. R., Kennedy, F. A., & Widener, S. K. (2014). Lean manufacturing and firm performance: The incremental contribution of lean management accounting practices. Journal of Operations Management, 32(7-8), 414-428. CrossrefGoogle Scholar

            Godinho Filho, M., Ganga, G. M. D., & Gunasekaran, A. (2016). Lean manufacturing in Brazilian small and medium enterprises: implementation and effect on performance. International Journal of Production Research, 54(24), 7523-7545. Doi: 10.1080/00207543.2016.1201606. CrossrefGoogle Scholar

            Laureani, A., & Antony, J. (2017). Leadership characteristics for lean six sigma. Total Quality Management & Business Excellence, 28(3-4), 405-426. Doi: 10.1080/14783363.2015.1090291. CrossrefGoogle Scholar

            Negrão, L. L. L., Godinho Filho, M., & Marodin, G. (2017). Lean practices and their effect on performance: a literature review. Production Planning & Control, 28(1), 33-56. Doi: 10.1080/09537287.2016.1231853. CrossrefGoogle Scholar

            Pavnaskar, S. J., Gershenson, J. K., & Jambekar, A. B. (2003). Classification scheme for lean manufacturing tools. International Journal of Production Research, 41(13), 3075-3090. Doi: 10.1080/0020754021000049817. CrossrefGoogle Scholar

            Qureshi, M. I., Rasli, A. M., Jusoh, A., Kowang, T. O., & Bahru, U. J. (2015). Sustainability: A new manufacturing paradigm. Journal Teknologi, 77(22), 47-53. CrossrefGoogle Scholar

            Randhawa, J. S., & Ahuja, I. S. (2017). 5S–a quality improvement tool for sustainable performance: literature review and directions. International Journal of Quality & Reliability Management, 34(3), 334-361.Doi: 10.1108/IJQRM-03-2015-0045. CrossrefGoogle Scholar

            Siasos, G. I., Skondras, G. I., Gkanas, E., Hrissagis, K., & Makridis, S. S. (2017). The Benefits of Lean through an Analysis and Improvement of an Existing Production Line. Mater. Sci. Eng. Adv. Res, 2(1), 15-24.

            Tagge, E. P., Thirumoorthi, A. S., Lenart, J., Garberoglio, C., & Mitchell, K. W. (2017). Improving operating room efficiency in academic children's hospital using Lean Six Sigma methodology. Journal of pediatric surgery, 52(6), 1040-1044. Doi: 10.1016/j.jpedsurg.2017.03.035. CrossrefGoogle Scholar

            Taj, S., & Morosan, C. (2011). The impact of lean operations on the Chinese manufacturing performance. Journal of manufacturing technology management, 22(2), 223-240.Doi: 10.1108/17410381111102234. CrossrefGoogle Scholar

            Taj, S. (2008). Lean manufacturing performance in China: assessment of 65 manufacturing plants. Journal of Manufacturing Technology Management, 19(2), 217-234. CrossrefGoogle Scholar

            Thanki, S., Govindan, K., & Thakkar, J. (2016). An investigation on lean-green implementation practices in Indian SMEs using analytical hierarchy process (AHP) approach. Journal of Cleaner Production, 135, 284-298. Doi: 10.1016/j.jclepro.2016.06.105 CrossrefGoogle Scholar

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