How to design a production process with low carbon emissions and low environmental impact as well as high manufacturing performance is a key factor in the success of low-carbon production. It is important to address concerns about climate change for the large carbon emission source manufacturing industries because of their high energy consumption and environmental impact during the manufacturing stage of the production life cycle. In this paper, methodology for determining a production process is developed. This methodology integrates process determination from three different levels: new production processing, selected production processing and batch production processing. This approach is taken within a manufacturing enterprise based on prior research. The methodology is aimed at providing decision support for implementing Environmentally Benign Manufacturing (EBM) and low-carbon production to improve the environmental performance of the manufacturing industry. At the first level, a decision-making model for new production processes based on the Genetic Simulated Annealing Algorithm (GSAA) is presented. The decision-making model considers not only the traditional factors, such as time, quality and cost, but also energy and resource consumption and environmental impact, which are different from the traditional methods. At the second level, a methodology is developed based on an IPO (Input-Process-Output) model that integrates assessments of resource consumption and environmental impact in terms of a materials balance principle for batch production processes. At the third level, based on the above two levels, a method for determining production processes that focus on low-carbon production is developed based on case-based reasoning, expert systems and feature technology for designing the process flow of a new component. Through the above three levels, a method for determining the production process to identify, quantify, assess, and optimize the production process with the goal of reducing and ultimately minimizing the environmental impact while maximizing the resource efficiency is effectively presented. The feasibility of the method is verified by a case study of a whole production process design at the above three levels.