State space modelling carbon emission dynamics of machining workshop based on carbon efficiency

Abstract

With increasing pressure to deal with climate change, to reduce carbon emissions has been one major challenge for manufacturing enterprises even though they face unprecedented levels of business competition. This paper proposes a state space model for evaluating carbon emission dynamics of a machining workshop based on carbon efficiency. A general hierarchical analysis framework for carbon emission dynamics for a three-level structure machining workshop is initially established from three perspectives: organisation, control loop and resource coupling input and output flow. Within this framework, carbon efficiency measuring emission dynamics is defined systematically, which reflects the balancing trends between benefit output (desired output) and emission output (undesired output) of any level system in a machining workshop. In order to evaluate the balancing trends, a state space based conceptual model is proposed. A state space model module for individual machine which consists of two sub-models, namely production process state space and emission process state space, forms the basic element of this conceptual model. A carbon emission dynamics profile based on carbon efficiency from machine tool level to workshop level is then determined through module integration. Finally, an experimental study is carried out to illustrate its feasibility and applicability of evaluating carbon emission dynamics through aligning economic and environmental dimension.

Keywords:

• state space model
• machining workshop
• carbon emission dynamics
• carbon efficiency
• smart energy efficient manufacturing

Acknowledgement

The authors would like to thank the support from the National Natural Science Foundation of China (NSFC) (NO.51475096), the NSFC-GuangDong Collaborative Fund (NO. U1501248), and China Postdoctoral Science Foundation (NO.2016M602443)

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by NSFC-GuangDong Collaborative Fund [U1501248];National Natural Science Foundation of China (NSFC) [51475096];the China Postdoctoral Science Foundation [2016M602443]