Digitalization and Industrial Energy Efficiency: Examining Whether Smart Manufacturing Accelerates Corporate Decarbonization

Manufacturers are adopting sensors, industrial internet of things platforms, manufacturing execution systems, digital twins, predictive maintenance, and artificial intelligence analytics, and these technologies are widely presented as a route to lower energy use and lower emissions. They can reduce energy per unit of output by making waste visible, tightening process control, and avoiding degraded equipment operation, and they can lower the carbon content of each unit of energy by enabling load shifting and renewable integration. The same technologies can also raise yield, capacity, and throughput, and a larger output can offset the savings. This study builds an evidence
based framework for asking whether smart manufacturing accelerates corporate decarbonization.The evidence does not support a universal decarbonization effect: direct plant level evidence linking smart manufacturing to absolute corporate emissions is thin, the net energy effect of digital technology is described as conditional by several reviews,
and the strongest empirical regularities concern the role of management capability and the economics of adoption. The paper therefore proposes a dual mechanism model in which smart manufacturing lowers emissions through product mix, energy efficiency, and carbon factor effects while also raising emissions through an output scale effect.
It formalizes the net decarbonization effect as an exact four term accounting decomposition, derives a break even condition for output growth and a rebound rate, and develops research propositions, an empirical design, and a Smart Manufacturing Decarbonization Index (SMDI) for plant level research. The central implication is that smart manufacturing accelerates decarbonization only when its efficiency, mix, and carbon factor gains outweigh the additional emissions created by higher output.