Noise-safe job rotation in multi-workday scheduling considering skill and demand requirements

References

• Mehdizadeh A, Vinel A, Hu Q, et al. Job rotation and work-related musculoskeletal disorders: a fatigue-failure perspective. Ergonomics. 2020;63(4):461–476.
   PubMed Web of Science ®Google Scholar
• Srinakorn K, Olapiriyakul S. A workforce scheduling model to reduce occupational heat stress and labor cost. Asia-Pacific J Sci Technol. 2016;25(1):APST-25-01-04.
   Google Scholar
• Asawarungsaengkul K, Tuntitippawan N The optimal number of workers for job rotation to prevent workers from occupational hazards. RI2C 2019-2019 Res Invent Innov Congr; 2019. (RfC). doi:https://doi.org/10.1109/RI2C48728.2019.8999881.
   Google Scholar
• Yaoyuenyong S, Nanthavanij S. Heuristic job rotation procedures for reducing daily exposure to occupational hazards. Int J Occup Saf Ergon. 2008;14(2):195–206.
   PubMed Web of Science ®Google Scholar
• Tharmmaphornphilas W, Green B, Carnaha BJ, et al. Applying mathematical modeling to create job rotation schedules for minimizing occupational noise exposure. Am Ind Hyg Assoc J. 2003;64(3):401–405. .
   Google Scholar
• Gan WQ, Mannino DM. Occupational noise exposure, bilateral high-frequency hearing loss, and blood pressure. J Occup Environ Med. 2018;60(5):462–468. .
   PubMed Web of Science ®Google Scholar
• Li X, Dong Q, Wang B, et al. The influence of occupational noise exposure on cardiovascular and hearing conditions among industrial workers. Sci Rep. 2019;9(1):11524.
   PubMedGoogle Scholar
• Al-Dosky HM. Noise level and annoyance of Industrial factories in Duhok city. IOSR J Environ Sci Toxicol Food Technol. 2014;8(5):01–08. .
   Google Scholar
• Lie A, Skogstad M, Johannessen HA, et al. Occupational noise exposure and hearing: a systematic review. Int Arch Occup Environ Health. 2016;89(3):351–372.
   PubMed Web of Science ®Google Scholar
• Occupational Safety and Health Administration (OSHA). Occupational noise exposure. https://www.osha.gov/noise.
   Google Scholar
• World Health Organization (WHO). Global costs of unaddressed hearing loss and cost-effectiveness of interventions: a WHO report. Switzerland: Geneva; 2017.
   Google Scholar
• Rerkjirattikarn P, Satitanekchai S, Olapiriyakul S. Safe job rotation scheduling with minimum setup time. Asia-Pacific J Sci Technol. 2017;22(4):APST-22-04-03.
   Google Scholar
• Azizi N, Liang M. An integrated approach to worker assignment, workforce flexibility acquisition, and task rotation. J Oper Res Soc. 2013;64(2):260–275.
   Web of Science ®Google Scholar
• Rerkjirattikarn P, Satitanekchai S, Olapiriyakul S. Designing safe job rotation schedules with minimum productivity loss. J Supply Chain Oper Manag. 2016;14(2):48–60.
   Google Scholar
• Rerkjirattikal P, Olapiriyakul S. Overtime assignment and job satisfaction in noise-safe job rotation scheduling;2019. DOI:https://doi.org/10.1007/978-3-030-14815-7_3.
   Google Scholar
• Rerkjirattikal P, Wanwarn T, Starita S, et al. Heuristics for noise-safe job-rotation problems considering learning-forgetting and boredom-induced job dissatisfaction effects. Environ Eng Manag J. 2020;19(8):1325–1337.
   Web of Science ®Google Scholar
• Chu X, Gao D, Cheng S, et al. Worker assignment with learning-forgetting effect in cellular manufacturing system using adaptive memetic differential search algorithm. Comput Ind Eng. 2019;136:(July):381–396.
   Web of Science ®Google Scholar
• Rerkjirattikal P, Huynh VN, Olapiriyakul S, et al. A goal programming approach to nurse scheduling with individual preference satisfaction. Math Probl Eng. 2020;2020. DOI:https://doi.org/10.1155/2020/2379091
   Google Scholar
• Wang S-P, Hsieh Y-K, Zhuang Z-Y, et al. Solving an outpatient nurse scheduling problem by binary goal programming. J Ind Prod Eng. 2014;31(1):41–50.
   Google Scholar
• Huang YC, Hsieh YH, Hsia FY. A study on nurse day-off scheduling under the consideration of binary preference. J Ind Prod Eng. 2016;33(6):363–372.
   Web of Science ®Google Scholar
• Huang YC, Lee PT, Huang TL. A rostering optimization model for physician scheduling in medical department – a case study in district hospital. J Ind Prod Eng. 2016;33(8):533–557.
   Web of Science ®Google Scholar
• Katiraee N, Calzavara M, Finco S, et al. Consideration of workers’ differences in production systems modelling and design: state of the art and directions for future research. Int J Prod Res. 2021;59(11):3237–3268.
   Web of Science ®Google Scholar
• McDonald T, Ellis KP, Van Aken EM, et al. Development and application of a worker assignment model to evaluate a lean manufacturing cell. Int J Prod Res. 2009;47(9):2427–2447.
   Web of Science ®Google Scholar
• Azizi N, Zolfaghari S, Liang M. Modeling job rotation in manufacturing systems: the study of employee’s boredom and skill variations. Int J Prod Econ. 2010;123(1):69–85.
   Web of Science ®Google Scholar
• Polat O, Kalayci CB, Ö M, et al. A two-phase variable neighbourhood search algorithm for assembly line worker assignment and balancing problem type-II: an industrial case study. Int J Prod Res. 2016;54(3):722–741.
   Web of Science ®Google Scholar
• Samouei P, Ashayeri J. Developing optimization & robust models for a mixed-model assembly line balancing problem with semi-automated operations. Appl Math Model. 2019;72:259–275.
   Web of Science ®Google Scholar
• Song J, Lee C, Lee W, et al. Development of a job rotation scheduling algorithm for minimizing accumulated work load per body parts. Work. 2016;53(3):511–521.
   Google Scholar
• Asensio-Cuesta S, Diego-Mas JA, Cremades-Oliver LV, et al. A method to design job rotation schedules to prevent work-related musculoskeletal disorders in repetitive work. Int J Prod Res. 2012;50(24):7467–7478.
   Web of Science ®Google Scholar
• Asawarungsaengkul K, Nanthavanij S. Heuristic genetic algorithm for workforce scheduling with minimum total worker-location changeover. Int J Ind Eng Theory, Appl Pract. 2008;15(4):373–385.
   Google Scholar
• Asawarungsaengkul K, Nanthavanij S. Optimization approach to hazard prevention budgeting problem. Int J Ind Eng Theory Appl Pract. 2008;15(4):330–340.
   Google Scholar
• Wongwien T, Nanthavanij S. Priority-based ergonomic workforce scheduling for industrial workers performing hazardous jobs. J Ind Prod Eng. 2017;34(1):52–60.
   Web of Science ®Google Scholar
• Digiesi SD, Facchini F, Mossa G, et al. Balancing ergonomic risk of workers of an assembly line by job rotation: a MINLP model. Int J Ind Eng Manag. 2018;9(3):129–138.
   Google Scholar
• Dalle Mura M, Dini G. Optimizing ergonomics in assembly lines: a multi objective genetic algorithm. CIRP J Manuf Sci Technol. 2019;27:31–45.
   Web of Science ®Google Scholar
• Botti L, Calzavara M, Mora C. Modelling job rotation in manufacturing systems with aged workers. Int J Prod Res. 2021;59(8):2522–2536.
   Web of Science ®Google Scholar
• Adem A, Dağdeviren M. A job rotation‐scheduling model for blue‐collar employees’ hand–arm vibration levels in manufacturing firms. Hum Factors Ergon Manuf Serv Ind. hfm.20878; 2020.
   PubMed Web of Science ®Google Scholar
• Aryanezhad MB, Kheirkhah AS, Deljoo V, et al. Designing safe job rotation schedules based upon workers’ skills. Int J Adv Manuf Technol. 2009;41(1–2):193–199.
   Web of Science ®Google Scholar
• Nanthavanij S, Yaoyuenyong S, Jeenanunta C. Heuristic approach to workforce scheduling with combined safety and productivity objective. Int J Ind Eng Theory Appl Pract. 2010;17(4):319–333.
   Google Scholar
• Niakan F, Baboli A, Moyaux T, et al. A bi-objective model in sustainable dynamic cell formation problem with skill-based worker assignment. J Manuf Syst. 2016;38:46–62.
   Web of Science ®Google Scholar
• Murphy WJ, Franks JR. Revisiting the NIOSH criteria for a recommended standard: occupational noise exposure. J Acoust Soc Am. 2002;111(5):2397.
   Google Scholar
• ISO1999. Acoustics — estimation of noise-induced hearing. 3rd ed. Switzerland: ISO 1999; 2013.
   Google Scholar