The evolution of production environments towards Industry 4.0 paradigm led to a work-load shift from physical to more cognitive activities, leading operators to perform tasks more cognitive-oriented. According to recent scientific studies, the typology of tasks as well as their complexity in smart factories will significantly change with the increased role of automation and artificial intelligence. Consistently to this trend, in the future work environments, operators will frequently interact with ever-smart machines. Under this perspective, the operators of smart factories, so-called “smart-operators”, will manage an increasing amount of information and data during the decision-making processes. In scientific literature many studies are available on the evaluation of the operators’ effort for the accomplishment of a physical-oriented task, but clear gaps are present for the evaluation of the operators’ capacities and effort involved in cognitive-oriented tasks. In this paper, an analytical model allowing to evaluate, based on the operator’s experience and on the complexity of the cognitive-oriented task to be performed, the Information Processing Rate (IPR) of a specific operator is presented. The results of the numerical experiment carried out proved the effectiveness of the model to provide the IPR of the operators by varying their experience and to evaluate if an operator is eligible for the accomplishment of a cognitive-oriented task. A potential application of the model is in the design phase of a cognitive-oriented task to predict the feasibility of its accomplishment by focusing on the capacities of operators.

A Model for the Evaluation of the Information Processing Rate of Smart Operators / Digiesi, Salvatore; Facchini, Francesco; Lucchese, Andrea; Mummolo, Giovanni. - ELETTRONICO. - (2022), pp. 236-244. (Intervento presentato al convegno IS: Industrial Innovation in Digital Age) [10.1007/978-3-030-97947-8_32].

A Model for the Evaluation of the Information Processing Rate of Smart Operators

Digiesi, Salvatore;Facchini, Francesco;Lucchese, Andrea
;
Mummolo, Giovanni
2022-01-01

Abstract

The evolution of production environments towards Industry 4.0 paradigm led to a work-load shift from physical to more cognitive activities, leading operators to perform tasks more cognitive-oriented. According to recent scientific studies, the typology of tasks as well as their complexity in smart factories will significantly change with the increased role of automation and artificial intelligence. Consistently to this trend, in the future work environments, operators will frequently interact with ever-smart machines. Under this perspective, the operators of smart factories, so-called “smart-operators”, will manage an increasing amount of information and data during the decision-making processes. In scientific literature many studies are available on the evaluation of the operators’ effort for the accomplishment of a physical-oriented task, but clear gaps are present for the evaluation of the operators’ capacities and effort involved in cognitive-oriented tasks. In this paper, an analytical model allowing to evaluate, based on the operator’s experience and on the complexity of the cognitive-oriented task to be performed, the Information Processing Rate (IPR) of a specific operator is presented. The results of the numerical experiment carried out proved the effectiveness of the model to provide the IPR of the operators by varying their experience and to evaluate if an operator is eligible for the accomplishment of a cognitive-oriented task. A potential application of the model is in the design phase of a cognitive-oriented task to predict the feasibility of its accomplishment by focusing on the capacities of operators.
2022
IS: Industrial Innovation in Digital Age
978-3-030-97946-1
978-3-030-97947-8
https://link.springer.com/book/10.1007/978-3-030-97947-8
A Model for the Evaluation of the Information Processing Rate of Smart Operators / Digiesi, Salvatore; Facchini, Francesco; Lucchese, Andrea; Mummolo, Giovanni. - ELETTRONICO. - (2022), pp. 236-244. (Intervento presentato al convegno IS: Industrial Innovation in Digital Age) [10.1007/978-3-030-97947-8_32].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/240081
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