title: Development of a job rotation scheduling algorithm for minimizing accumulated work load per body parts.
abstract: BACKGROUND
  For the successful implementation of job rotation, jobs should be scheduled systematically so that physical workload is evenly distributed with the use of various body parts. However, while the potential benefits are widely recognized by research and industry, there is still a need for a more effective and efficient algorithm that considers multiple work-related factors in job rotation scheduling.
  
  
  OBJECTIVE
  This study suggests a type of job rotation algorithm that aims to minimize musculoskeletal disorders with the approach of decreasing the overall workload.
  
  
  METHODS
  Multiple work characteristics are evaluated as inputs to the proposed algorithm. Important factors, such as physical workload on specific body parts, working height, involvement of heavy lifting, and worker characteristics such as physical disorders, are included in the algorithm. For evaluation of the overall workload in a given workplace, an objective function was defined to aggregate the scores from the individual factors. A case study, where the algorithm was applied at a workplace, is presented with an examination on its applicability and effectiveness.
  
  
  RESULTS
  With the application of the suggested algorithm in case study, the value of the final objective function, which is the weighted sum of the workload in various body parts, decreased by 71.7% when compared to a typical sequential assignment and by 84.9% when compared to a single job assignment, which is doing one job all day.
  
  
  CONCLUSIONS
  An algorithm was developed using the data from the ergonomic evaluation tool used in the plant and from the known factors related to workload. The algorithm was developed so that it can be efficiently applied with a small amount of required inputs, while covering a wide range of work-related factors. A case study showed that the algorithm was beneficial in determining a job rotation schedule aimed at minimizing workload across body parts.
authors.affiliation: CX Team, Samsung SDS, Seoul, South Korea.
authors.forename: JooBong
authors.initials: J
authors.lastname: Song
authors.affiliation: AgeLab, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Chaiwoo
authors.initials: C
authors.lastname: Lee
authors.affiliation: CX Team, Samsung SDS, Seoul, South Korea.
authors.forename: WonJung
authors.initials: W
authors.lastname: Lee
authors.affiliation: Department of Industrial and Management Engineering, Myongji University, Yongin, South Korea.
authors.forename: Sangwoo
authors.initials: S
authors.lastname: Bahn
authors.affiliation: Department of Computer Science Engineering, Seoul National University, Seoul, South Korea.
authors.forename: ChanJu
authors.initials: C
authors.lastname: Jung
authors.affiliation: CX Team, Samsung SDS, Seoul, South Korea.
authors.forename: Myung Hwan
authors.initials: MH
authors.lastname: Yun
mesh_terms: D000465:Algorithms; D006804:Ergonomics; D006801:Humans; D007866:Leg; D017770:Lifting; D018763:Muscle Fatigue; D009140:Musculoskeletal Diseases / Q000517:prevention & control*; D009333:Neck; D009784:Occupational Diseases / Q000517:prevention & control*; D010561:Personnel Staffing and Scheduling; D011187:Posture; D034941:Upper Extremity; D016526:Workload; D017132:Workplace / Q000458:organization & administration
keywords: Job rotation; ergonomic assessment tool; musculoskeletal disorders; physical workload