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Parallel Machine Scheduling with WMSD Risk Considerations

Yıl 2019, Özel Sayı 2019, 336 - 342, 31.10.2019
https://doi.org/10.31590/ejosat.638286

Öz

This paper introduces the parallel machine scheduling problems with work related musculoskeletal disorder (WMSD) risk considerations. By the WMSD consideration, we mean that job processing times are an increasing function of occupational repetitive technical actions (OCRA) risk factor. The OCRA index was recruited for risk assessment of occupational repetitive technical actions. WMSD risks were modeled with cumulative mean value of OCRA index. Due to NP-Hard structure of parallel machine scheduling problems with WMSD considerations and learning rate, the solution cannot be found always. However, problem can be solved by transforming assignment problem. In spite of the fact that the computational effort remains O (n4), problem is solved within more efficient time. In this study, a model that includes learning effect and WMSD risk was proposed. WMSD risk was considered as cumulative mean of risk value throughout shift. In order to the balance between productivity and WMSD risk, jobs’ foreseeable cycle time (FCT) value was changed. It is aimed to decrease mean of risk along schedule without increasing total basic process time. The value of sacrifice from the FCT was compensating from job which have optimal, acceptable, borderline or slight risk level. Process time and risk values were recalculated by using new FCT value. Thus, balanced process times and risk values obtained. Proposed model was solved with Lingo software and sequence of jobs was obtained. Total flow time and mean of risk were compared for balanced and none balanced schedules. Total flow time and mean of risk belong to balanced schedule is smaller than none balanced schedule. It was shown that handled problem is solvable at the polynomial time and total flow time can be improved by bringing balance between WMSD risks and productivity.

Destekleyen Kurum

Erciyes University Scientific Research Projects Unit

Proje Numarası

FDK-2017-7265

Teşekkür

This study is supported by Erciyes University Scientific Research Projects Unit in the scope of “Scheduling under Ergonomic Risk Factors” coded FDK-2017-7265 project.

Kaynakça

  • Akyol, Ş. D., & Baykasoğlu, A. (2016). ErgoALWABP: a multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem under ergonomic risk factors. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-016-1246-6
  • Antwi-Afari, M. F., Li, H., Edwards, D. J., Pärn, E. A., Seo, J., & Wong, A. Y. L. (2017). Biomechanical analysis of risk factors for work-related musculoskeletal disorders during repetitive lifting task in construction workers. Automation in Construction, 83, 41-47. doi: https://doi.org/10.1016/j.autcon.2017.07.007
  • Arık, O. A., & Toksarı, M. D. (2017). Multi-objective fuzzy parallel machine scheduling problems under fuzzy job deterioration and learning effects. International Journal of Production Research, 1-18. doi: 10.1080/00207543.2017.1388932
  • Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1-13. doi: https://doi.org/10.1016/j.ejor.2015.12.023
  • Battini, D., Glock, C. H., Grosse, E. H., Persona, A., & Sgarbossa, F. (2015). Ergo-Lot-Sizing: Considering Ergonomics in Lot-Sizing Decisions. IFAC-PapersOnLine, 48(3), 326-331. doi: https://doi.org/10.1016/j.ifacol.2015.06.102
  • Biskup, D. (1999). Single-machine scheduling with learning considerations. European Journal of Operational Research, 115(1), 173-178. doi: https://doi.org/10.1016/S0377-2217(98)00246-X
  • Boenzi, F., Digiesi, S., Mossa, G., Mummolo, G., & Romano, V. A. (2013). Optimal Break and Job Rotation Schedules of High Repetitive – Low Load Manual Tasks in Assembly Lines: an OCRA – Based Approach. IFAC Proceedings Volumes, 46(9), 1896-1901. doi: https://doi.org/10.3182/20130619-3-RU-3018.00625
  • Fulmer, S., Buchholz, B., Scribani, M., & Jenkins, P. (2017). Musculoskeletal Disorders in Northeast Lobstermen. Safety and Health at Work, 8(3), 282-289. doi: https://doi.org/10.1016/j.shaw.2016.12.004
  • Hignett, S., & McAtamney, L. (2000). Rapid Entire Body Assessment (REBA). Applied Ergonomics, 31(2), 201-205. doi: https://doi.org/10.1016/S0003-6870(99)00039-3
  • Jiang, Z., Chen, F., & Kang, H. (2013). Single-machine scheduling problems with actual time-dependent and job-dependent learning effect. European Journal of Operational Research, 227(1), 76-80. doi: https://doi.org/10.1016/j.ejor.2012.12.007
  • Koulamas, C. (2017). Common due date assignment with generalized earliness/tardiness penalties. Computers & Industrial Engineering, 109, 79-83. doi: https://doi.org/10.1016/j.cie.2017.04.040
  • Koulamas, C., & Kyparisis, G. J. (2010). Single-machine scheduling problems with past-sequence-dependent delivery times. International Journal of Production Economics, 126(2), 264-266. doi: https://doi.org/10.1016/j.ijpe.2010.03.016
  • Lu, Y.-Y., Wang, J.-J., & Huang, X. (2015). Scheduling jobs with position and sum-of-processing-time based processing times. Applied Mathematical Modelling, 39(14), 4013-4021. doi: 10.1016/j.apm.2014.12.021
  • MacCarthy, B. L., Wilson, J. R., & Crawford, S. (2001). Human performance in industrial scheduling: A framework for understanding. Human Factors and Ergonomics in Manufacturing & Service Industries, 11(4), 299-320. doi: doi:10.1002/hfm.1016
  • McAtamney, L., & Nigel Corlett, E. (1993). RULA: a survey method for the investigation of work-related upper limb disorders. Applied Ergonomics, 24(2), 91-99. doi: https://doi.org/10.1016/0003-6870(93)90080-S
  • Micheli, G. J. L., & Marzorati, L. M. (2018). Beyond OCRA: Predictive UL-WMSD risk assessment for safe assembly design. International Journal of Industrial Ergonomics, 65, 74-83. doi: https://doi.org/10.1016/j.ergon.2017.07.005
  • Mosheiov, G., & Sidney, J. B. (2003). Scheduling with general job-dependent learning curves. European Journal of Operational Research, 147(3), 665-670. doi: https://doi.org/10.1016/S0377-2217(02)00358-2
  • Occhipinti, E. (1998). OCRA: a concise index for the assessment of exposure to repetitive movements of the upper limbs. Ergonomics, 41(9), 1290-1311. doi: 10.1080/001401398186315
  • Occhipinti, E., & Colombini, D. (2016). A toolkit for the analysis of biomechanical overload and prevention of WMSDs: Criteria, procedures and tool selection in a step-by-step approach. International Journal of Industrial Ergonomics, 52, 18-28. doi: https://doi.org/10.1016/j.ergon.2015.08.001
  • Oron, D. (2016). Scheduling controllable processing time jobs with position-dependent workloads. International Journal of Production Economics, 173, 153-160. doi: https://doi.org/10.1016/j.ijpe.2015.12.014
  • Otto, A., & Scholl, A. (2011). Incorporating ergonomic risks into assembly line balancing. European Journal of Operational Research, 212(2), 277-286. doi: 10.1016/j.ejor.2011.01.056
  • Schaub, K., Caragnano, G., Britzke, B., & Bruder, R. (2013). The European Assembly Worksheet. Theoretical Issues in Ergonomics Science, 14(6), 616-639. doi: 10.1080/1463922X.2012.678283
  • Şenyiğit, E., & Atici, U. (2017a). Computer-aided work related musculoskeletal disorder risk assessment tool: WMSD-RA. Paper presented at the International Symposium on Industry 4.0 and Applications, Karabuk,Turkey.
  • Şenyiğit, E., & Atici, U. (2017b). Ergo-Scheduling. New Trends and Issues Proceedings on Humanities and Social Sciences, 4(10), 208-217.
  • Şenyiğit, E., & Atici, U. (2018). Scheduling with Job Dependent Learning Effect and Ergonomic Risk Deterioration. Proceedings of the 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Ankara, Turkey, 63-66.
  • Toksari, M. D., & Arık, O. A. (2017). Single machine scheduling problems under position-dependent fuzzy learning effect with fuzzy processing times. Journal of Manufacturing Systems, 45, 159-179. doi: https://doi.org/10.1016/j.jmsy.2017.08.006
  • Toksarı, M. D., Oron, D., & Güner, E. (2009). Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning. Mathematical and Computer Modelling, 50(3-4), 401-406. doi: 10.1016/j.mcm.2009.05.026
  • TSE. (2011). Safety of machinery - Human physical performance Part-5: Risk assessment for repetitive handling at high frequency (Vol. TS EN 1005-5). Ankara.
  • Wang, J.-B. (2007). Single-machine scheduling problems with the effects of learning and deterioration. Omega, 35(4), 397-402. doi: https://doi.org/10.1016/j.omega.2005.07.008
  • Wang, J.-B. (2008). Single-machine scheduling with general learning functions. Computers & Mathematics with Applications, 56(8), 1941-1947. doi: https://doi.org/10.1016/j.camwa.2008.04.019
  • Wang, J.-B., Huang, X., Wang, X.-Y., Yin, N., & Wang, L.-Y. (2009). Learning effect and deteriorating jobs in the single machine scheduling problems. Applied Mathematical Modelling, 33(10), 3848-3853. doi: https://doi.org/10.1016/j.apm.2009.01.004
  • Wang, X.-R., Huang, X., & Wang, J.-B. (2011). Single-machine scheduling with linear decreasing deterioration to minimize earliness penalties. Applied Mathematical Modelling, 35(7), 3509-3515. doi: 10.1016/j.apm.2011.01.005
  • Yin, N., Kang, L., Sun, T.-C., Yue, C., & Wang, X.-R. (2014). Unrelated parallel machines scheduling with deteriorating jobs and resource dependent processing times. Applied Mathematical Modelling, 38(19), 4747-4755. doi: https://doi.org/10.1016/j.apm.2014.03.022

Parallel Machine Scheduling with WMSD Risk Considerations

Yıl 2019, Özel Sayı 2019, 336 - 342, 31.10.2019
https://doi.org/10.31590/ejosat.638286

Öz

This paper introduces the parallel machine scheduling problems with work related musculoskeletal disorder (WMSD) risk considerations. By the WMSD consideration, we mean that job processing times are an increasing function of occupational repetitive technical actions (OCRA) risk factor. The OCRA index was recruited for risk assessment of occupational repetitive technical actions. WMSD risks were modeled with cumulative mean value of OCRA index. Due to NP-Hard structure of parallel machine scheduling problems with WMSD considerations and learning rate, the solution cannot be found always. However, problem can be solved by transforming assignment problem. In spite of the fact that the computational effort remains O (n4), problem is solved within more efficient time. In this study, a model that includes learning effect and WMSD risk was proposed. WMSD risk was considered as cumulative mean of risk value throughout shift. In order to the balance between productivity and WMSD risk, jobs’ foreseeable cycle time (FCT) value was changed. It is aimed to decrease mean of risk along schedule without increasing total basic process time. The value of sacrifice from the FCT was compensating from job which have optimal, acceptable, borderline or slight risk level. Process time and risk values were recalculated by using new FCT value. Thus, balanced process times and risk values obtained. Proposed model was solved with Lingo software and sequence of jobs was obtained. Total flow time and mean of risk were compared for balanced and none balanced schedules. Total flow time and mean of risk belong to balanced schedule is smaller than none balanced schedule. It was shown that handled problem is solvable at the polynomial time and total flow time can be improved by bringing balance between WMSD risks and productivity.

Proje Numarası

FDK-2017-7265

Kaynakça

  • Akyol, Ş. D., & Baykasoğlu, A. (2016). ErgoALWABP: a multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem under ergonomic risk factors. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-016-1246-6
  • Antwi-Afari, M. F., Li, H., Edwards, D. J., Pärn, E. A., Seo, J., & Wong, A. Y. L. (2017). Biomechanical analysis of risk factors for work-related musculoskeletal disorders during repetitive lifting task in construction workers. Automation in Construction, 83, 41-47. doi: https://doi.org/10.1016/j.autcon.2017.07.007
  • Arık, O. A., & Toksarı, M. D. (2017). Multi-objective fuzzy parallel machine scheduling problems under fuzzy job deterioration and learning effects. International Journal of Production Research, 1-18. doi: 10.1080/00207543.2017.1388932
  • Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1-13. doi: https://doi.org/10.1016/j.ejor.2015.12.023
  • Battini, D., Glock, C. H., Grosse, E. H., Persona, A., & Sgarbossa, F. (2015). Ergo-Lot-Sizing: Considering Ergonomics in Lot-Sizing Decisions. IFAC-PapersOnLine, 48(3), 326-331. doi: https://doi.org/10.1016/j.ifacol.2015.06.102
  • Biskup, D. (1999). Single-machine scheduling with learning considerations. European Journal of Operational Research, 115(1), 173-178. doi: https://doi.org/10.1016/S0377-2217(98)00246-X
  • Boenzi, F., Digiesi, S., Mossa, G., Mummolo, G., & Romano, V. A. (2013). Optimal Break and Job Rotation Schedules of High Repetitive – Low Load Manual Tasks in Assembly Lines: an OCRA – Based Approach. IFAC Proceedings Volumes, 46(9), 1896-1901. doi: https://doi.org/10.3182/20130619-3-RU-3018.00625
  • Fulmer, S., Buchholz, B., Scribani, M., & Jenkins, P. (2017). Musculoskeletal Disorders in Northeast Lobstermen. Safety and Health at Work, 8(3), 282-289. doi: https://doi.org/10.1016/j.shaw.2016.12.004
  • Hignett, S., & McAtamney, L. (2000). Rapid Entire Body Assessment (REBA). Applied Ergonomics, 31(2), 201-205. doi: https://doi.org/10.1016/S0003-6870(99)00039-3
  • Jiang, Z., Chen, F., & Kang, H. (2013). Single-machine scheduling problems with actual time-dependent and job-dependent learning effect. European Journal of Operational Research, 227(1), 76-80. doi: https://doi.org/10.1016/j.ejor.2012.12.007
  • Koulamas, C. (2017). Common due date assignment with generalized earliness/tardiness penalties. Computers & Industrial Engineering, 109, 79-83. doi: https://doi.org/10.1016/j.cie.2017.04.040
  • Koulamas, C., & Kyparisis, G. J. (2010). Single-machine scheduling problems with past-sequence-dependent delivery times. International Journal of Production Economics, 126(2), 264-266. doi: https://doi.org/10.1016/j.ijpe.2010.03.016
  • Lu, Y.-Y., Wang, J.-J., & Huang, X. (2015). Scheduling jobs with position and sum-of-processing-time based processing times. Applied Mathematical Modelling, 39(14), 4013-4021. doi: 10.1016/j.apm.2014.12.021
  • MacCarthy, B. L., Wilson, J. R., & Crawford, S. (2001). Human performance in industrial scheduling: A framework for understanding. Human Factors and Ergonomics in Manufacturing & Service Industries, 11(4), 299-320. doi: doi:10.1002/hfm.1016
  • McAtamney, L., & Nigel Corlett, E. (1993). RULA: a survey method for the investigation of work-related upper limb disorders. Applied Ergonomics, 24(2), 91-99. doi: https://doi.org/10.1016/0003-6870(93)90080-S
  • Micheli, G. J. L., & Marzorati, L. M. (2018). Beyond OCRA: Predictive UL-WMSD risk assessment for safe assembly design. International Journal of Industrial Ergonomics, 65, 74-83. doi: https://doi.org/10.1016/j.ergon.2017.07.005
  • Mosheiov, G., & Sidney, J. B. (2003). Scheduling with general job-dependent learning curves. European Journal of Operational Research, 147(3), 665-670. doi: https://doi.org/10.1016/S0377-2217(02)00358-2
  • Occhipinti, E. (1998). OCRA: a concise index for the assessment of exposure to repetitive movements of the upper limbs. Ergonomics, 41(9), 1290-1311. doi: 10.1080/001401398186315
  • Occhipinti, E., & Colombini, D. (2016). A toolkit for the analysis of biomechanical overload and prevention of WMSDs: Criteria, procedures and tool selection in a step-by-step approach. International Journal of Industrial Ergonomics, 52, 18-28. doi: https://doi.org/10.1016/j.ergon.2015.08.001
  • Oron, D. (2016). Scheduling controllable processing time jobs with position-dependent workloads. International Journal of Production Economics, 173, 153-160. doi: https://doi.org/10.1016/j.ijpe.2015.12.014
  • Otto, A., & Scholl, A. (2011). Incorporating ergonomic risks into assembly line balancing. European Journal of Operational Research, 212(2), 277-286. doi: 10.1016/j.ejor.2011.01.056
  • Schaub, K., Caragnano, G., Britzke, B., & Bruder, R. (2013). The European Assembly Worksheet. Theoretical Issues in Ergonomics Science, 14(6), 616-639. doi: 10.1080/1463922X.2012.678283
  • Şenyiğit, E., & Atici, U. (2017a). Computer-aided work related musculoskeletal disorder risk assessment tool: WMSD-RA. Paper presented at the International Symposium on Industry 4.0 and Applications, Karabuk,Turkey.
  • Şenyiğit, E., & Atici, U. (2017b). Ergo-Scheduling. New Trends and Issues Proceedings on Humanities and Social Sciences, 4(10), 208-217.
  • Şenyiğit, E., & Atici, U. (2018). Scheduling with Job Dependent Learning Effect and Ergonomic Risk Deterioration. Proceedings of the 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Ankara, Turkey, 63-66.
  • Toksari, M. D., & Arık, O. A. (2017). Single machine scheduling problems under position-dependent fuzzy learning effect with fuzzy processing times. Journal of Manufacturing Systems, 45, 159-179. doi: https://doi.org/10.1016/j.jmsy.2017.08.006
  • Toksarı, M. D., Oron, D., & Güner, E. (2009). Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning. Mathematical and Computer Modelling, 50(3-4), 401-406. doi: 10.1016/j.mcm.2009.05.026
  • TSE. (2011). Safety of machinery - Human physical performance Part-5: Risk assessment for repetitive handling at high frequency (Vol. TS EN 1005-5). Ankara.
  • Wang, J.-B. (2007). Single-machine scheduling problems with the effects of learning and deterioration. Omega, 35(4), 397-402. doi: https://doi.org/10.1016/j.omega.2005.07.008
  • Wang, J.-B. (2008). Single-machine scheduling with general learning functions. Computers & Mathematics with Applications, 56(8), 1941-1947. doi: https://doi.org/10.1016/j.camwa.2008.04.019
  • Wang, J.-B., Huang, X., Wang, X.-Y., Yin, N., & Wang, L.-Y. (2009). Learning effect and deteriorating jobs in the single machine scheduling problems. Applied Mathematical Modelling, 33(10), 3848-3853. doi: https://doi.org/10.1016/j.apm.2009.01.004
  • Wang, X.-R., Huang, X., & Wang, J.-B. (2011). Single-machine scheduling with linear decreasing deterioration to minimize earliness penalties. Applied Mathematical Modelling, 35(7), 3509-3515. doi: 10.1016/j.apm.2011.01.005
  • Yin, N., Kang, L., Sun, T.-C., Yue, C., & Wang, X.-R. (2014). Unrelated parallel machines scheduling with deteriorating jobs and resource dependent processing times. Applied Mathematical Modelling, 38(19), 4747-4755. doi: https://doi.org/10.1016/j.apm.2014.03.022
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Ercan Şenyiğit 0000-0002-9388-2633

Uğur Atıcı Bu kişi benim

Proje Numarası FDK-2017-7265
Yayımlanma Tarihi 31 Ekim 2019
Yayımlandığı Sayı Yıl 2019 Özel Sayı 2019

Kaynak Göster

APA Şenyiğit, E., & Atıcı, U. (2019). Parallel Machine Scheduling with WMSD Risk Considerations. Avrupa Bilim Ve Teknoloji Dergisi336-342. https://doi.org/10.31590/ejosat.638286