Development of a conceptual method for sustainability assessment in manufacturing

Vikas Swarnakar, A. R. Singh, Jiju Antony, Anil Kr Tiwari, Elizabeth Cudney

Research output: Contribution to journalArticlepeer-review

Abstract

Manufacturing organizations continue to face challenges related to sustainability assessment in their current production process. This study aims to develop a structured conceptual method necessary for sustainability assessments of manufacturing processes. The development of the conceptual method was performed by integrating a new group of sustainability indicators into the value stream mapping. In this context, forty empirically tested sustainability indicators were identified in triple bottom line perspectives and formulated for the development of a conceptual method. The developed method was applied in two manufacturing organizations to evaluate its applicability. The findings of this study reveal the case organizations were sustainable in customer perspectives but not sustainable in triple bottom line dimensions perspectives. Moreover, a solution approach is provided by the experts to improve the manufacturing process sustainability. The proposed approach in this study also contributes by providing a reference for operation managers who may struggle to assess and enhance sustainability. Finally, this study contributes by encouraging practitioners and researchers to broaden the study in a similar field and explore the application of value stream mapping and appropriate indicators for sustainability assessment.

Original languageEnglish
Article number107403
JournalComputers and Industrial Engineering
Volume158
Early online date19 May 2021
DOIs
Publication statusPublished - Aug 2021

Keywords

  • Manufacturing process
  • Sustainability assessment
  • Sustainability indicators
  • Triple bottom line
  • Value stream mapping

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Fingerprint

Dive into the research topics of 'Development of a conceptual method for sustainability assessment in manufacturing'. Together they form a unique fingerprint.

Cite this