Human factors are fundamental for manufacturing sustainability, which is determined by social, economic and environmental performance. However, there is a lack of engineering methods and tools that are able to integrate their analysis with product and process optimisation according to sustainability principles. The present study proposes an analytical approach to support sustainable manufacturing (SM) by analysing the so-called user experience (UX) of manufacturing and assembly processes starting from the early design stages. Considering both behavioural and cognitive aspects of manufacturing UX and defining a corresponding model, it is possible to estimate the UX impact on manufacturing sustainability for a certain product and its related processes. The proposed method is implemented in a computer-based framework, which can be easily integrated with environmental and cost assessment tools to integrate all three SM aspects. Finally, a case study focused on automated machines is presented; the proposed approach was used to redesign the machine to improve its economic, environmental and human-related impacts. The industrial case study provides concrete evidence of the achievable benefits of applying the proposed model in manufacturing practice. Indeed, the case study demonstrated how the manufacturing and assembly process of a specific machine was optimised by simplifying the product structure, changing the adopted materials and creating more human-centred activities. The new solution is more sustainable due to time savings (−30%), cost reduction (−20%), reduced environmental impact (−25%) and improved UX (+30%).

User experience evaluation model for sustainable manufacturing / Peruzzini, Margherita; Pellicciari, Marcello. - In: INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING. - ISSN 1362-3052. - 31:6(2018), pp. 494-512. [10.1080/0951192X.2017.1305502]

User experience evaluation model for sustainable manufacturing

PERUZZINI, MARGHERITA;PELLICCIARI, Marcello
2018

Abstract

Human factors are fundamental for manufacturing sustainability, which is determined by social, economic and environmental performance. However, there is a lack of engineering methods and tools that are able to integrate their analysis with product and process optimisation according to sustainability principles. The present study proposes an analytical approach to support sustainable manufacturing (SM) by analysing the so-called user experience (UX) of manufacturing and assembly processes starting from the early design stages. Considering both behavioural and cognitive aspects of manufacturing UX and defining a corresponding model, it is possible to estimate the UX impact on manufacturing sustainability for a certain product and its related processes. The proposed method is implemented in a computer-based framework, which can be easily integrated with environmental and cost assessment tools to integrate all three SM aspects. Finally, a case study focused on automated machines is presented; the proposed approach was used to redesign the machine to improve its economic, environmental and human-related impacts. The industrial case study provides concrete evidence of the achievable benefits of applying the proposed model in manufacturing practice. Indeed, the case study demonstrated how the manufacturing and assembly process of a specific machine was optimised by simplifying the product structure, changing the adopted materials and creating more human-centred activities. The new solution is more sustainable due to time savings (−30%), cost reduction (−20%), reduced environmental impact (−25%) and improved UX (+30%).
2018
22-mar-2017
31
6
494
512
User experience evaluation model for sustainable manufacturing / Peruzzini, Margherita; Pellicciari, Marcello. - In: INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING. - ISSN 1362-3052. - 31:6(2018), pp. 494-512. [10.1080/0951192X.2017.1305502]
Peruzzini, Margherita; Pellicciari, Marcello
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1129724
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