This paper frames a model which summarizes the principal factors and relationships to incorporate human element, as per fatigue engagement, in the strategic and tactical decision making. A characterization of humans as per a dynamic interferer in system is presented. The findings are tested in an U-shaped assembly division of an international motor company. Dual-Resource Constrained sets are proposed. A Multi Agent model architecture, incorporating system dynamics modelling per humans, is implemented. ANOVA is executed for interaction analyses. Results designed optimal job sequence, rest break and task's sequence, recovery rate and load characters as per enhanced system's performances. Stable fatigued conditions are under complete recovery. Production rate in system is affected by fatigue that in turn increases with rise in switching rate. Chaotic market behavior prefers decentralized assignment of worker to task. Continuous switching suffers from learning attitude. Chaotic demand impairs fatigue across workforce reporting instable operator fatigue under different allocation rules. Under loudly physical tasks, random assignment is preferable for productivity outcomes. Autonomous control of workers at work considerably impairs fatigue under complete resting schema.

Incorporating the Human Factor within Manufacturing Dynamics

FRUGGIERO, FABIO;RIEMMA, Stefano;
2016

Abstract

This paper frames a model which summarizes the principal factors and relationships to incorporate human element, as per fatigue engagement, in the strategic and tactical decision making. A characterization of humans as per a dynamic interferer in system is presented. The findings are tested in an U-shaped assembly division of an international motor company. Dual-Resource Constrained sets are proposed. A Multi Agent model architecture, incorporating system dynamics modelling per humans, is implemented. ANOVA is executed for interaction analyses. Results designed optimal job sequence, rest break and task's sequence, recovery rate and load characters as per enhanced system's performances. Stable fatigued conditions are under complete recovery. Production rate in system is affected by fatigue that in turn increases with rise in switching rate. Chaotic market behavior prefers decentralized assignment of worker to task. Continuous switching suffers from learning attitude. Chaotic demand impairs fatigue across workforce reporting instable operator fatigue under different allocation rules. Under loudly physical tasks, random assignment is preferable for productivity outcomes. Autonomous control of workers at work considerably impairs fatigue under complete resting schema.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4683954
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