Digital transformation as a driver of operational sustainability in manufacturing: a systematic review (2015-2025)
Abstract
Objective: This research examines how the adoption of digital technologies-the Internet of Things (IoT), artificial intelligence, digital twins, and big data analytics-affects operational sustainability in the manufacturing sector.
Design/methodology: A systematic review was conducted in accordance with the PRISMA 2020 guidelines, consulting Scopus, ScienceDirect and Taylor & Francis for the period 2015-2025. Of 1,247 initial records, 50 studies passed the eligibility and methodological quality filters.
Findings: The evidence indicates that the joint implementation of several digital technologies produces reductions of between 20% and 35% in energy consumption and between 25% and 40% in material waste, according to the ranges reported in the primary studies. Digital twins had the greatest effects on process optimisation, followed by industrial IoT and artificial intelligence systems. Organisations that combined three or more complementary technologies achieved improvements 40%-60% greater than isolated implementations.
Originality: The work offers a structured synthesis of the specific mechanisms that connect digitalisation with concrete sustainability indicators and identifies knowledge gaps that guide future lines of research.
How strong is the evidence?
Evidence Hub reads this as a systematic review, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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