Publication Cover
Production Planning & Control
The Management of Operations
Volume 35, 2024 - Issue 2
734
Views
10
CrossRef citations to date
0
Altmetric
Research Articles

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

ORCID Icon, ORCID Icon & ORCID Icon
Pages 133-150 | Received 14 Sep 2021, Accepted 15 Mar 2022, Published online: 25 Mar 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.

Acknowledgements

We would like to acknowledge the editor and the referees for their valuable feedback that helped us to improve the quality and clarity of the manuscript.

Additional information

Notes on contributors

Claudio Castiglione

Claudio Castiglione is a research fellow at Politecnico di Torino in Turin, Italy. He graduated in Management Engineering at Politecnico di Torino and got his PhD in Management, Production and Design at Politecnico di Torino in 2021. His research areas include production planning and control systems, system simulation and optimization, industrial symbiosis development, and performance assessment of manufacturing systems.

Erica Pastore

Erica Pastore is an assistant professor at Politecnico di Torino, in Turin, Italy. She graduated in Mathematical Engineering at Politecnico di Torino and got her Ph.D. in Management, Production and Design at Politecnico di Torino in 2018. Her research areas include production planning and control, system simulation optimization, production scheduling, and supply chain management.

Arianna Alfieri

Arianna Alfieri is a full professor at Politecnico di Torino at Turin, Italy, where she currently teaches production planning and control and system simulation. Her research area includes scheduling, supply chain management and system simulation.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 242.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.