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Performance opportunity for workforce agility in collaborative and noncollaborative work systems
171
Citations
21
References
2001
Year
EngineeringProject ManagementHuman Resource ManagementOrganizational BehaviorOperations ResearchWorkforce AgilityAgile Software DevelopmentManagementSystems EngineeringCombinatorial OptimizationSerial Production SystemsMechanism DesignPerformance OpportunityCooperative Information SystemAgile Workforce PoliciesNoncollaborative Work SystemsScheduling (Computing)Computer ScienceTask AllocationWorkforce DevelopmentScheduling ProblemDistributed CollaborationAutomationProduction SchedulingBusinessScheduling (Production Processes)Work Group DynamicRemote Collaboration
To gain insight into the potential logistical benefits of worker cross-training and agile workforce policies, we study simple models of flexible workers in serial production systems. The primary control issue is how to assign workers to jobs/stations over time. Under assumptions of complete worker flexibility and collaborative work, we prove that a simple expedite policy minimizes along each sample path the cycle time (delay) for each job. Therefore, the expedite policy also minimizes work in process and maximizes throughput along every sample path. We also compute the performance improvement opportunity achievable using flexible workers as opposed to the optimal static allocation of workers. This enables us to examine th e factors that make workforce agility a potentially attractive strategy. We also consider the intuitive analog of the expedite policy for the noncollaborative work environment, which we call the pick-and-run policy; however, we demonstrate by counterexample that it is not always optimal. Finally, we extend some of our insights from the demand-constrained environment to a capacity-constrained environment operating under a CONstant WIP (CONWIP) protocol
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