The integration of digital tools and technologies within modern production systems has precipitated a paradigm shift within manufacturing companies, encompassing not only the management of operations but also the daily working environment. The integration of digital technologies as support tools in picking and assembly tasks has frequently led to an alteration of the neural patterns of operators exposed to an ever-increasing volume of data. In particular, this phenomenon of digitalisation has also influenced the Lean methodology, giving rise to the so-called “Digital Lean Manufacturing” paradigm. Over time, in fact, several Lean methods and tools have been integrated with a diverse range of technologies, often increasing in operational complexity, which does not really comply, though, with the original formulation of such Lean principles. The objective of this paper is, therefore, to examine the impact of digital technologies, and in particular of “pick-to-light” systems, on the perception of cognitive load of blue-collar workers when utilised as error-proofing tools (or, within the Lean context, as Poka-Yoke systems), through the analysis of a single case study of an Italian company specialised in the production of home automation and electronics devices. The proposed cognitive load evaluation framework demonstrates that reducing cognitive load is not always the best approach to achieving an efficient human-technology symbiotic system where technologies and operators collaborate. On the other hand, to attain an efficient human-technology system aligned with the principles of Kaizen, it is recommended to design technological operator-assistive systems that meticulously calibrate the cognitive load exerted on individuals by taking into account the level of familiarity of workers with the assigned task (the germane cognitive load) and with how information is presented to them (the extraneous cognitive load).

(2026). Assessing the Impact of Digital Lean Manufacturing Tools on Perceived Cognitive Workload: The Case of a “Pick-To-Light” Poka-Yoke 4.0 System . Retrieved from https://hdl.handle.net/10446/315185

Assessing the Impact of Digital Lean Manufacturing Tools on Perceived Cognitive Workload: The Case of a “Pick-To-Light” Poka-Yoke 4.0 System

Zanchi, Matteo;Gaiardelli, Paolo;
2026-01-01

Abstract

The integration of digital tools and technologies within modern production systems has precipitated a paradigm shift within manufacturing companies, encompassing not only the management of operations but also the daily working environment. The integration of digital technologies as support tools in picking and assembly tasks has frequently led to an alteration of the neural patterns of operators exposed to an ever-increasing volume of data. In particular, this phenomenon of digitalisation has also influenced the Lean methodology, giving rise to the so-called “Digital Lean Manufacturing” paradigm. Over time, in fact, several Lean methods and tools have been integrated with a diverse range of technologies, often increasing in operational complexity, which does not really comply, though, with the original formulation of such Lean principles. The objective of this paper is, therefore, to examine the impact of digital technologies, and in particular of “pick-to-light” systems, on the perception of cognitive load of blue-collar workers when utilised as error-proofing tools (or, within the Lean context, as Poka-Yoke systems), through the analysis of a single case study of an Italian company specialised in the production of home automation and electronics devices. The proposed cognitive load evaluation framework demonstrates that reducing cognitive load is not always the best approach to achieving an efficient human-technology symbiotic system where technologies and operators collaborate. On the other hand, to attain an efficient human-technology system aligned with the principles of Kaizen, it is recommended to design technological operator-assistive systems that meticulously calibrate the cognitive load exerted on individuals by taking into account the level of familiarity of workers with the assigned task (the germane cognitive load) and with how information is presented to them (the extraneous cognitive load).
2026
Zanchi, Matteo; Powell, Daryl J.; Gaiardelli, Paolo; Zouggar Amrani, Anne; Romero, David
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/315185
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