In the production planning and control field, assessing the performance of a manufacturing system is a multi-dimensional problem in which neglected dimensions may lead to hidden inefficiencies and missed opportunities for gaining a competitive advantage. In this paper, a new data formalization method is proposed to model a manufacturing system by simultaneously considering value creation and technical, economic, and environmental performance. The proposed method combines the principles of Material Flow Analysis and a new data structure that exploits some characteristics of the Multi-layer Stream Mapping and the Enterprise Input-Output methods to obtain a data-driven approach, typical of Industry 4.0. The proposed method can deal with complex systems and allows to consider also non-value-added activities such as transport and inventories. The implementation of the method and its advantages are shown through a numerical example based on a recycled plastic pipeline manufacturing system. The method shows positive synergies and mutual benefits between sustainable production, lean principles, and data-driven approaches and technologies of Industry 4.0. The method improves the alignment of environmental, technical, economic, and value creation information between operational and strategical levels, removing redundancies in data collection, conditioning, and processing activities, thus reducing partial information, hidden risks and opportunities, and inconsistencies.

Technical, economic, and environmental performance assessment of manufacturing systems: the multi-layer enterprise input-output formalization method / Castiglione, C.; Pastore, E.; Alfieri, A.. - In: PRODUCTION PLANNING & CONTROL. - ISSN 0953-7287. - (2022), pp. 1-18. [10.1080/09537287.2022.2054743]

Technical, economic, and environmental performance assessment of manufacturing systems: the multi-layer enterprise input-output formalization method

Castiglione C.;Pastore E.;Alfieri A.
2022

Abstract

In the production planning and control field, assessing the performance of a manufacturing system is a multi-dimensional problem in which neglected dimensions may lead to hidden inefficiencies and missed opportunities for gaining a competitive advantage. In this paper, a new data formalization method is proposed to model a manufacturing system by simultaneously considering value creation and technical, economic, and environmental performance. The proposed method combines the principles of Material Flow Analysis and a new data structure that exploits some characteristics of the Multi-layer Stream Mapping and the Enterprise Input-Output methods to obtain a data-driven approach, typical of Industry 4.0. The proposed method can deal with complex systems and allows to consider also non-value-added activities such as transport and inventories. The implementation of the method and its advantages are shown through a numerical example based on a recycled plastic pipeline manufacturing system. The method shows positive synergies and mutual benefits between sustainable production, lean principles, and data-driven approaches and technologies of Industry 4.0. The method improves the alignment of environmental, technical, economic, and value creation information between operational and strategical levels, removing redundancies in data collection, conditioning, and processing activities, thus reducing partial information, hidden risks and opportunities, and inconsistencies.
File in questo prodotto:
File Dimensione Formato  
TPPC-2021-0480.R2_Proof_hi.pdf

Open Access dal 26/03/2023

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Creative commons
Dimensione 2.5 MB
Formato Adobe PDF
2.5 MB Adobe PDF Visualizza/Apri
Technical, economic, and environmental performance assessment of manufacturing systems.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 2.51 MB
Formato Adobe PDF
2.51 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2962822