Carbon Emission Accounting Model of Three-Stage Mechanical Products for Manufacturing Process

Abstract

Carbon accounting is critical to manufacturing and achieving a low-carbon transition and lean carbon management. A comprehensive understanding of carbon emissions in manufacturing is essential to calculate a product’s carbon footprint accurately. Based on the life cycle assessment (LCA) method, this study divides the whole process of mechanical products from parts to finished products into three stages: parts (P), assembly (A), and testing (T). By decomposing each stage’s carbon emission sources and combining each stage’s characteristics, a series of corresponding carbon emission accounting models is established. Finally, the three-stage carbon emission model of the manufacturing process of a three-piece ball valve is established, and the validity and feasibility of the proposed model are verified. The results show that raw material consumption, energy consumption, and transportation are the primary sources of carbon emissions in the manufacturing process of three-piece ball valves, accounting for 35.6%, 38.8%, and 17.6%, respectively. The corresponding carbon emissions were 17.854 kgCO₂e, 19.405 kgCO₂e, and 8.8 kgCO₂e, respectively. Through these results, we can provide some theoretical and data support for the low-carbon transformation of manufacturing enterprises as well as some research ideas for realizing low-carbon production through process planning and shop scheduling.

1. Introduction

In recent years, the issue of climate change caused by global warming has attracted significant attention from all countries and regions worldwide. According to the International Energy Agency [1], in 2023, global energy-related CO₂ emissions increased by 1.1%, an increase of 410 million tons, to reach a record high of 37.4 billion tons. Carbon emissions would have tripled without the growing deployment of five key clean energy technologies since 2019 (solar PV, wind, batteries, electrolyzes, and heat pumps). As more than 30% of the total carbon emissions come from the manufacturing industry, under the background of “carbon peak” and “carbon neutrality” [2,3], manufacturing enterprises are facing enormous economic pressure and environmental challenges. Therefore, the research on manufacturing carbon emissions aiming at energy conservation and emission reduction has become one of the most crucial research hotspots. The research on energy saving and emission reduction in the manufacturing industry mainly focuses on the product, equipment, and production management layers. With the continuous development of manufacturing technology, more and more manufacturing enterprises have begun to focus on process planning and workshop scheduling research. Xiao et al. [4] introduced the concept of the work step to represent the features of the factored parts, established a multi-objective optimization model, and realized the energy saving and low cost of machining. Li et al. [5] set up a scheduling model that minimizes completion time, carbon emission, and machine load, considering the impact of transportation time on scheduling results during workshop processing. In the traditional manufacturing process, process planning and workshop scheduling are independent and serial, which quickly causes target conflict, unreasonable resource utilization, etc. Zhang et al. [6] studied the multi-objective energy-saving integrated process planning and scheduling problem of parallel disassembly, flexible job shop reprocessing, and the parallel reassembly-integrated remanufacturing system to minimize energy consumption cost and completion time.

The manufacturing industry is the core of the national economy and the focus of policies and actions to address climate change. Formulating accurate accounting methods for manufacturing carbon emissions and implementing reasonable control measures is essential [7]. Carbon emissions in manufacturing are characterized by the diversity of carbon emission sources, unclear evaluation boundaries, and difficulty in accurate quantification. Therefore, research on carbon emission accounting is the basis for carbon reduction optimization and low-carbon technology innovation. Currently, relevant research on carbon emission accounting can be roughly divided into two categories [8,9]: one is carbon emission accounting based on feature design or model improvement, and the other type is carbon emission accounting, which is based on the process or system level.

A reasonable and practical feature design or model can reduce carbon emissions from subsequent manufacturing processes. In terms of carbon emission accounting for design or model improvement, Sun et al. [10] innovatively established a quantitative analysis model for carbon footprint assessment from the perspective of the life cycle, which carried out a comprehensive calculation and analysis of carbon footprints at various stages, including production, physical and chemical processes, construction, operation and maintenance, and treatment and recycling. You et al. [11] conducted a comparative analysis of carbon emissions of three typical large-span steel structures. They proposed a layered hybrid life cycle assessment method, which promoted the practice of low-carbon design. Tian et al. [12] constructed a carbon emission accounting model for internet service providers, which considered both direct and indirect influences and discussed the impact of by-product gases on interprocess carbon metabolism in steel production. In addition, an integrated iron-making process based on the headgear recovery and oxygen blast furnace technology is proposed, and its carbon emission reduction potential is analyzed. Li et al. [13] proposed a quantitative analysis method of discrete manufacturing carbon footprints based on energy data space, which supports the real-time quantitative analysis of product carbon footprint. Xiao et al. [14] adopted a double-layer game model to carry out the collaborative optimization of the low-carbon product series and its manufacturing process, analyzed the conflict and coordination between low-carbon product series architecture and manufacturing process configuration, and took microwave oven product series as an example for verification. Kannan et al. [15] introduced a multi-criterion decision model to identify and evaluate the obstacles in carbon emission management. They verified and analyzed the model in combination with the actual production situation of several manufacturing enterprises. Chen et al. [16] proposed a fuzzy evaluation model based on the processing performance to promote various tool industries to improve processing quality, reduce costs, and reduce carbon emissions. Kaur et al. [17] proposed a carbon accounting framework for complex supply chains and applied it to define, calculate, and report carbon emission ranges. Kennelly et al. [18] analyzed the existing carbon accounting methods from two aspects: input–output-based and process-based life cycle assessment, established a practical hybrid model, and analyzed its impact on accuracy. Panagiotopoulou et al. [19] proposed a model-based carbon emission accounting framework for additive manufacturing processes from the level of each process, machine tool, and system based on carbon emission factors and manufacturing hierarchy principles, guiding carbon emission accounting in manufacturing systems. Romain et al. [20] analyzed the overall flow of goods quality according to the factory’s inventory and flow of materials. They proposed a carbon accounting method based on multistage material flow analysis (MFA). Pawanr et al. [21] developed an empirical model for treating carbon emissions of cylindrical parts and verified the practicability of this model by analyzing cylindrical parts with three different process schemes. Zheng et al. [22] proposed a complete carbon emission evaluation model for the feature design of sand castings to guide the reduction in carbon emission in the planning stage of the sand-casting process. Wang et al. [23] proposed an online automatic carbon emission accounting method in the production of aluminum castings. They verified the method’s effectiveness by taking an aluminum casting workshop to produce subframes of electric vehicles as an example.

The process layer and system layer of parts in the machining process are one of the primary sources of carbon emission. In terms of carbon emission accounting at the process or system level, Liu et al. [24] introduced the life cycle assessment of carbon generated in the casting stage in detail. They proposed a carbon emission assessment model of the casting manufacturing process based on life cycle assessment and oriented to the 3D topology optimization structure of parts. Liu et al. [25] proposed a carbon emission model for manufacturing process expansion based on considering energy, material, and environmental emissions and integrated considerations of capital, labor, and other factors. Cai et al. [26] proposed a new benchmark assessment method for sustainable development to quantify the sustainability level of manufacturing systems. Ge et al. [27] made a comprehensive decision on the welding parameters and sequence of multi-feature laser welding units, considering carbon emission and processing time. They proposed a two-layer algorithm combining state compression dynamic programming and a multi-objective marine predator algorithm to solve the problem. Tian et al. [28] established a multi-objective optimization model of cutting parameters, including low-carbon target parameters, taking the cutting parameters during tool wear as the optimization objective, considering the perceptible influence of tool wear on the selection of cutting parameters and carbon emissions in the production process. Agrawal et al. [29] evaluated the carbon emission of Ti-6Al-4V titanium alloy under different turning environments (low temperature/humidity). The results show that the total carbon emission of low-temperature turning at high cutting speed is reduced by 22% compared with wet turning. He et al. [30] built a collaborative, low-carbon, and efficient dual-objective optimization model considering the interaction between cutting parameters and production scheduling. They adopted an improved genetic algorithm based on Pareto optimization. Fang et al. [31] studied the multi-step parameter optimization problem of milling, analyzed the carbon emission, processing cost, and processing time of the processing process, established a multi-objective optimization model with cutting parameters as variables, and proposed an improved particle swarm optimization algorithm for solving the problem. Ge et al. [32] proposed the concept of a “meta carbon emission block” composed of static and variable carbon emission blocks. Based on this, they suggested a data-driven carbon emission accounting method for manufacturing systems. Yao et al. [33] proposed a framework for quantifying carbon emissions in four-layer machining based on Internet of Things (IoT) and energy flow analysis (MEFA) technology. They verified the effectiveness of the proposed method through a boss case. Liu et al. [34] analyzed the carbon emission characteristics of each system used in the directed energy deposition process and built an optimization model of the directed energy deposition manufacturing process. Chi et al. [35] established the objective function of carbon emission and surface roughness in turning processing, solved the optimization model by genetic algorithm, and analyzed the influence of cutting parameters on optimization objectives.

In summary, scholars have conducted some relevant studies on carbon emissions in the manufacturing process of products. However, there are two fundamental research gaps. On the one hand, the source analysis of carbon emissions in the specific manufacturing process of mechanical products needs to be more comprehensive, and the cited literature mainly focuses on the optimization effect of carbon emissions. It needs to be translated into intuitive carbon emissions accounting. On the other hand, the models established in the above literature tend to be for specific products, and manufacturing systems still need a standard carbon emissions accounting method.

Therefore, this paper proposes a three-stage carbon accounting model for mechanical products based on life cycle assessment (LCA). By analyzing the carbon emission source distribution of mechanical products in the three stages of part–assembly–test (P-A-T), the corresponding carbon accounting model is established to evaluate and quantify the carbon emission of mechanical products. In this paper, the parts stage is further divided into the production stage of purchased parts (PPs) and homemade parts (HPs), and the corresponding mathematical models are established for various carbon emission sources in the production and transportation of purchased parts and the processing process of homemade parts. Meanwhile, the product assembly process is analyzed and modeled. It is worth noting that most mechanical products need to be tested before being put on the market, so this paper also establishes the corresponding carbon emission quantitative model according to the characteristics of the product test stage. Through the detailed stage division described above, the carbon footprint of the entire manufacturing process of the product can be more accurately captured and quantified. Finally, the proposed model is verified by taking the processing of a specific type of ball valve as an example. The primary sources of carbon emission in the manufacturing process of the ball valve are analyzed, and some suggestions for reducing carbon emission are put forward.

This paper is organized as follows. Section 2 introduces the accounting boundary of product carbon emission. Section 3 proposes the P-A-T three-stage product carbon emission quantitative model. Section 4 conducts a case study on a model of a three-piece ball valve. Section 5 presents the conclusions (

Table 1. Abbreviations and variable names table.

Abbreviations and Variable	Meaning
$C{E}_{A\text{-}E}$	The carbon emissions from work consumption
$C{E}_{A\text{-}ele}$	The carbon emissions from electricity consumption
$C{E}_{P\text{-}HP\text{-}e}$	The carbon emissions caused by the consumption of electricity during the processing of homemade parts
$C{E}_{P\text{-}HP\text{-}eq}$	The carbon emissions caused by equipment loss during the production of homemade parts
$C{E}_{P\text{-}HP\text{-}material}$	The carbon emissions caused by the consumption of raw materials in homemade parts
$C{E}_{P\text{-}PP\text{-}T}$	The carbon emissions from the transportation of purchased parts
$C{E}_{P\text{-}PP\text{-}M}$	The carbon emissions from the production of purchased parts
$C{E}_{T\text{-}\mathrm{I}}$	The carbon emissions during the T-I stage
$C{E}_{T\text{-}\mathrm{II}-e}$	The carbon emissions caused by electricity consumption in the T-II stage
$C{E}_{T\text{-}\mathrm{II}-eq}$	The carbon emissions caused by the loss of testing equipment in the T-II stage
HP	Homemade parts
KJ	Key joint
LCA	Life cycle assessment
P-A-T	Part–assembly–test
PJ	Pinned joint
PP	Purchased parts
SJ	Screw joint
T-I	The first stage of product testing
T-II	The second stage of product testing

).

2. Product Carbon Emission Accounting Boundary

When conducting LCA, it is essential to first establish the boundaries of the life cycle, which determines the extent of the scope involved in the LCA analysis. The accurate definition of the scientific scope and boundaries is crucial to ensuring the accuracy of the analysis and the final results of the LCA [36]. Mechanical products are typically composed of several parts, and thus the carbon emissions of mechanical products can be viewed as the aggregation of carbon consumption from various resources throughout their entire life cycle [37]. The carbon emissions associated with the production of mechanical products are primarily distributed within their manufacturing processes. Therefore, quantifying the carbon emissions in the manufacturing process of mechanical products requires an analysis of the carbon consumption associated with various resources in the manufacturing processes.

While there may be variations in the machining processes of different parts, the types of resources consumed can be categorized into materials, energy, equipment, e.g., [38]. In the case of discrete manufacturing industries, some parts of mechanical products are obtained through procurement, so it is necessary to consider the carbon emissions associated with purchased parts. This includes both the carbon emissions from the production of purchased parts and the carbon emissions from their transportation [39,40]. Additionally, the assembly of products and the installation of testing equipment during product testing can also contribute to carbon emissions, which further affects the overall carbon footprint of the product. Therefore, the carbon emissions of a product exhibit characteristics such as diversity, interactivity, and complexity.

This paper divides the carbon emissions of the product into three stages, P-A-T, and defines the carbon emission boundaries of the product from the perspectives of direct and indirect carbon emissions. Direct carbon emissions include the carbon emissions directly generated from the consumption of carbon sources such as materials in the part manufacturing processes. Indirect carbon emissions encompass carbon emissions resulting from energy consumption, part transportation, equipment depreciation, and testing. The carbon emission boundaries of the product are illustrated in Figure 1.

3. Product Carbon Emission Quantitative Model

3.1. Product Carbon Emission Decomposition

The product carbon emissions are decomposed into three stages following the P-A-T approach: part carbon emissions, assembly carbon emissions, and testing carbon emissions. Carbon accounting models are established, and the influencing factors of each part of product carbon emissions are analyzed.

(1) Part carbon emissions can be categorized into two distinct types: purchased part carbon emissions and self-made part carbon emissions. Purchased part carbon emissions encompass the carbon emissions from the production and transportation of purchased parts, with production emissions primarily arising from material and energy losses during processing stages, and transportation emissions mainly linked to distance traveled and fuel consumption. On the other hand, self-made part carbon emissions are directly related to the carbon emissions caused by the consumption of various carbon sources in their respective manufacturing processes, as illustrated in Figure 2.

(2) Assembly carbon emissions primarily arise from the combination of various parts through connecting elements. To determine the carbon emissions in this stage, an accounting model is established by considering different connection methods. This model helps quantify the carbon emissions associated with the assembly process.

(3) The carbon emissions calculation for the testing stage should encompass three parts. Firstly, it includes the energy consumption during the installation of the product on testing equipment. Secondly, it considers the electricity consumption during the testing stage. Lastly, it takes into account the carbon emissions resulting from the depreciation of the testing equipment.

3.2. P-Stage Carbon Emission Accounting

3.2.1. PP Carbon Emission Accounting Model

(1) Purchased parts primarily include raw materials and fasteners, among others. As product manufacturers do not have control over the production processes of purchased parts, the carbon emission accounting for purchased parts cannot be based on a detailed assessment of the carbon sources consumed in their production processes from the product manufacturer’s perspective. Therefore, the carbon emissions from the production of purchased parts should consider the direct material consumption and significant energy consumption during their production processes. The carbon emission model for purchased parts production is as follows:

$$C{E}_{P\text{-}PP\text{-}M}=C{E}_m+C{E}_e$$

(1)

where $C{E}_{P\text{-}PP\text{-}M}$ represents the carbon emissions from the production of purchased parts, $C{E}_m$ represents the carbon emissions caused by direct material consumption, and $C{E}_e$ represents the carbon emissions caused by major energy consumption.

(2) According to reference [41], transportation costs can be divided into variable costs and carbon emission costs. Variable costs can be represented as the one-way distance multiplied by fuel consumption per ton of payload, product weight, order quantity, and fuel price. Carbon emission costs are calculated by multiplying the travel distance (round trip) by the unit carbon cost and vehicle carbon emission cost. Based on this analogy, it can be inferred that the carbon emissions from the transportation of purchased parts should also be related to fuel consumption and transportation distance. Therefore, the transportation carbon emission model for purchased parts can be represented as follows:

$$C{E}_{P\text{-}PP\text{-}T}=\eta (2d_s{C}_o{\beta }_o+{\displaystyle \frac{d_s{C}_l{N}_{P\text{-}PP}{m}_{P\text{-}PP}{\beta }_o}{\eta }})$$

(2)

where $\eta$ represents the number of transportation trips, $d_s$ represents the vehicle travel distance, $C_o$ represents the fuel consumption per unit transportation distance, ${\beta }_o$ represents the diesel carbon emission factor, $C_l$ represents the fuel consumption per ton of effective purchased parts payload, $N_{P\text{-}PP}$ represents the quantity of purchased parts, and $m_{P\text{-}PP}$ represents the unit mass of purchased parts.

3.2.2. HP Carbon Emission Accounting Model

Since the manufacturing process of homemade parts is determined by the product manufacturer, when calculating the carbon emissions of homemade parts, it is necessary to analyze various carbon sources based on their production processes and consider the characteristics of different stages. The carbon sources in the production process of homemade parts can be roughly classified into three categories: materials, energy, and equipment. Materials include raw materials used for homemade parts and various consumables such as cutting tools, cutting fluids, and lubricants consumed during processing. Equipment refers to the machinery used in different stages, such as lathes, milling machines, and grinders.

(1)

Material consumption carbon emission accounting model

The material consumption carbon emission accounting model for part processing can be calculated using the input–output method [42]. It is typically represented as a reduction in material quantity or the number of uses. In theory, the carbon emissions from material consumption can be expressed as the ratio of material consumption to the material carbon emission factor. However, different types of materials have distinct calculation methods for material consumption, and each material has a certain utilization rate. Therefore, it is necessary to establish specific carbon emission accounting models for different types of materials.

(a) Raw material consumption carbon emission model

The carbon emission model for the consumption of raw materials in homemade parts can be represented as the product of the mass of raw material consumed, the carbon emission factor of the raw material, and its utilization rate. Therefore, the carbon emission model for raw material consumption in the manufacturing process of homemade parts is as follows:

$$C{E}_{P\text{-}HP\text{-}material}=\Delta m_{material}{\alpha }_{material}{\delta }_{material}$$

(3)

where $C{E}_{P\text{-}HP\text{-}material}$ represents the carbon emissions caused by the consumption of raw materials in homemade parts, $\Delta m_{material}$ represents the consumption of raw materials, ${\alpha }_{material}$ represents the carbon emission coefficient of raw materials, ${\delta }_{material}$ represents the utilization rate of raw materials.

(b) Cutting fluid consumption carbon emission model

Water-based cutting fluids, being the most commonly used type, primarily exhibit carbon emissions during the preparation process of mineral oils [43]. Due to the periodic replacement of cutting fluids, the carbon emissions caused by cutting fluid consumption can be calculated using a time-based distribution method. The carbon emission accounting model for cutting fluid consumption is as follows:

$$C{E}_{P\text{-}HP\text{-}fluid}={\displaystyle \frac{t_{use\text{-}fluid}}{T_{rep\text{-}fluid}}}{\displaystyle \frac{V_{fluid}}{\phi }}{\alpha }_{oil}{\delta }_{fluid}$$

(4)

where $C{E}_{P\text{-}HP\text{-}fluid}$ represents the carbon emissions caused by the consumption of cutting fluids during the production of homemade parts. $t_{use\text{-}fluid}$ represents the usage time of cutting fluids, $T_{rep\text{-}fluid}$ represents the replacement period of cutting fluids, $V_{fluid}$ represents the volume of cutting fluids, $\phi$ represents the concentration of cutting fluids, ${\alpha }_{oil}$ represents the carbon emission factor of mineral oils, and ${\delta }_{fluid}$ represents the utilization rate of cutting fluids.

(c) Carbon emission model of lubricating oil consumption

Similar to the carbon emission model of cutting fluid consumption, the time transformation–distribution method is also used to calculate carbon emissions caused by lubricating oil consumption; then, its carbon emission accounting model is as follows:

$$C{E}_{P\text{-}HP\text{-}\mathrm{lub}e}={\displaystyle \frac{t_{use\text{-}\mathrm{lub}e}}{T_{rep\text{-}\mathrm{lub}e}}}{V}_{\mathrm{lub}e}{\alpha }_{\mathrm{lub}e}{\delta }_{\mathrm{lub}e}$$

(5)

where $C{E}_{P\text{-}HP\text{-}\mathrm{lub}e}$ represents the carbon emissions caused by the consumption of lubricating oil during the production of homemade parts. $t_{use\text{-}\mathrm{lub}e}$ represents the usage time of lubricating oil, $T_{rep\text{-}\mathrm{lub}e}$ represents the replacement period of lubricating oil, $V_{\mathrm{lub}e}$ represents the usage volume of lubricating oil, ${\alpha }_{\mathrm{lub}e}$ represents the carbon emission factor of lubricating oil, and ${\delta }_{\mathrm{lub}e}$ represents the utilization rate of lubricating oil.

(d) Tool consumption carbon emission model

Analyzing from the perspective of cutting time, the quantity of tools can be determined based on the cutting time and the tool’s lifespan. By applying the time-based distribution method, the carbon emission accounting model for tool consumption can be represented as follows:

$$C{E}_{P\text{-}HP\text{-}tool}={\displaystyle \frac{t_{use\text{-}tool}}{T_{rep\text{-}tool}}}{m}_{tool}{\alpha }_{tool}{\delta }_{tool}$$

(6)

where $C{E}_{P\text{-}HP\text{-}tool}$ represents the carbon emissions caused by the consumption of tools during the processing of homemade parts. $t_{use\text{-}tool}$ represents the cutting time, which is the total time the tools are used. $T_{rep\text{-}tool}$ represents the replacement period of the tools. $m_{tool}$ represents the quantity or mass of the tools. ${\alpha }_{tool}$ represents the carbon emission factor of the tools, and ${\delta }_{tool}$ represents the utilization rate of the tools.

(2)

Electricity consumption carbon emission model

The main energy consumed in the production of homemade parts is electricity, which is utilized in the operation of different equipment during various stages. The carbon emission model for electricity consumption is typically represented as the product of total electricity consumption and the carbon emission factor of electricity. The total electricity consumption can be obtained by multiplying the power of the equipment by the duration of equipment usage. However, for the usage time of manufacturing equipment, it is important to consider the time spent on idling, processing, and tool replacement. Therefore, the electricity consumption carbon emission model for a specific process can be expressed as follows:

$$C{E}_{P\text{-}HP\text{-}e}=E_e{\beta }_e=P_{eq}(t_{no\text{-}load}+t_{run}+t_{tool}){\beta }_e$$

(7)

where $C{E}_{P\text{-}HP\text{-}e}$ represents the carbon emissions caused by the consumption of electricity during the processing of homemade parts. ${\beta }_e$ represents the carbon emission factor per unit of electricity. $P_{eq}$ represents the power of the equipment used in the corresponding process. $t_{no\text{-}load}$ represents the idle time, $t_{run}$ represents the processing time, and $t_{tool}$ represents the time for tool replacement.

(3)

Equipment loss carbon emission model

Modern mechanical product manufacturing heavily relies on the operation of equipment, which is composed of many parts. Therefore, the equipment itself stores a certain amount of carbon emissions, which is defined as the implicit carbon emissions of the equipment. From the time the equipment is manufactured and put into use, implicit carbon emissions are continuously released throughout its life cycle as its operating time increases. Assuming the initial carbon emissions of the equipment are zero, each time the equipment is used (represented by a decrease in lifespan or number of uses), a certain amount of carbon dioxide equivalent (CO₂e) is released until the equipment is completely out of use, reaching 100% of its implicit carbon emissions.

Although different equipment is used in different processes of a product or part, the carbon emissions associated with the equipment are related to the utilization rate, operating time, lifespan, and implicit carbon emissions of the equipment. Hence, the carbon emission accounting model for equipment loss in a specific process can be expressed as follows:

$$C{E}_{P\text{-}HP\text{-}eq}=n_{eq}{\displaystyle \frac{t_{use\text{-}eq}}{T_{life\text{-}eq}}}C{E}_{eq}{\gamma }_{eq}$$

(8)

where $C{E}_{P\text{-}HP\text{-}eq}$ represents the carbon emissions caused by equipment loss during the production of homemade parts. $n_{eq}$ represents the number of equipment simultaneously running in the process. $t_{use\text{-}eq}$ represents the usage time of the equipment. $T_{life\text{-}eq}$ represents the lifespan of the equipment in the specific process. $C{E}_{eq}$ represents the implicit carbon emissions of the equipment used in the process. ${\gamma }_{eq}$ represents the utilization rate of the equipment.

3.2.3. Analysis of Typical Process Characteristics in P-HP Production

The typical machining processes for parts in P-HP production include turning, milling, drilling, and grinding. The carbon emission composition for these processes is shown in

Table 2. Carbon emission parts of typical machining processes.

Carbon Source	Mechanical Machining
	Turning	Milling	Drilling	Grinding
Raw material	√	√	√	√
Cutting fluid	√	√	√	—
Lubricant	√	√	√	—
Cutting tool	√	√	√	—
Electric	√	√	√	√
Equipment	√	√	√	√

.

The carbon emission sources for turning, milling, and drilling processes in the mentioned typical operations include raw materials, cutting fluids, lubricating oil, tools, electricity, and equipment, as shown in Table 2. Therefore, the carbon emission accounting models for these three machining processes can be represented as follows:

$$C{E}_{P\text{-}HP}^M=C{E}_{material}^M+C{E}_{fluid}^M+C{E}_{\mathrm{lub}e}^M+C{E}_{tool}^M+C{E}_e^M+C{E}_{eq}^M$$

(9)

where $C{E}_{P\text{-}HP}^M$ represents the carbon emissions from the machining process of homemade parts. $C{E}_{material}^M$ represents the carbon emissions caused by the consumption of raw materials in the machining process, primarily reflecting the generation of processing waste such as chips. $C{E}_{fluid}^M$ represents the carbon emissions caused by the consumption of cutting fluids in the machining process. $C{E}_{\mathrm{lub}e}^M$ represents the carbon emissions caused by the consumption of lubricating oil in the machining process. $C{E}_{tool}^M$ represents the carbon emissions caused by tool consumption. The type of tool used may vary depending on the machining process, such as turning tools, milling cutters, and twist drills. $C{E}_e^M$ electricity represents the carbon emissions caused by electricity consumption in the machining process. $C{E}_{eq}^M$ represents the carbon emissions caused by equipment loss in the machining process. The type of equipment used can be lathes, milling machines, drilling machines, etc., depending on the process requirements.

Due to the higher economic cost and environmental and health hazards associated with grinding fluids, dry grinding is commonly used. Therefore, the carbon emission accounting for the grinding process differs from the three aforementioned machining processes. The carbon emission accounting model for the grinding process can be represented as follows:

$$C{E}_{P\text{-}HP}^{grinding}=C{E}_{material}^{grinding}+C{E}_e^{grinding}+C{E}_{eq}^{grinding}$$

(10)

where $C{E}_{P\text{-}HP}^{grinding}$ represents the carbon emissions from the grinding process of homemade parts. $C{E}_{material}^{grinding}$ represents the carbon emissions caused by the consumption of raw materials in the grinding process. Since the impact of grinding waste on carbon emissions in this stage is negligible, we consider the carbon emissions caused by the consumption of grinding tools, such as grinding wheels. $C{E}_e^{grinding}$ represents the carbon emissions caused by electricity consumption in the grinding process. $C{E}_{eq}^{grinding}$ represents the carbon emissions caused by the loss of the grinding machines in the grinding process.

3.3. Carbon Emission Accounting for Stage A

The parts are interconnected in different ways to form the product. Therefore, the carbon emissions in Stage A can be analyzed by establishing carbon emission accounting models for each interconnection method. Common interconnection methods include threaded connections, key connections, and pin connections. The carbon sources for these interconnection methods include energy consumption during the connection process, electricity, and equipment.

3.3.1. Carbon Emission Accounting Model for Stage A

Similar to the carbon emission accounting model for P-HP, the carbon emission accounting model for Stage A can also be divided into three parts: energy consumption carbon emission model, electricity consumption carbon emission model, and equipment loss carbon emission model, which are represented as follows:

$$C{E}_{A\text{-}E}=E_{A\text{-}E}{\alpha }_{A\text{-}material}$$

(11)

$$C{E}_{A\text{-}ele}=E_{A\text{-}ele}{\beta }_e$$

(12)

$$C{E}_{A\text{-}eq}=n_{eq}{\displaystyle \frac{t_{use\text{-}eq}}{T_{life\text{-}eq}}}C{E}_{eq}{\gamma }_{eq}$$

(13)

where $C{E}_{A\text{-}E}$ represents the carbon emissions from work consumption, $C{E}_{A\text{-}ele}$ represents the carbon emissions from electricity consumption, and $C{E}_{A\text{-}eq}$ represents the carbon emissions from equipment loss. $E_{A\text{-}E}$ represents the energy consumption during the interconnection process, ${\alpha }_{A\text{-}material}$ represents the carbon emission coefficient of the materials used in the interconnection method, $E_{A\text{-}ele}$ represents the electricity consumption, $n_{eq}$ represents the number of equipment simultaneously running in the process, $t_{use\text{-}eq}$ represents the usage time of the equipment, $T_{life\text{-}eq}$ represents the lifespan of the equipment, $C{E}_{eq}$ represents the implicit carbon emissions of the equipment used in the interconnection method, and ${\gamma }_{eq}$ represents the utilization rate of the equipment.

3.3.2. Analysis of Common Interconnection Method Characteristics

(1)

Screw Joint (SJ)

Using the torque-angle method, screw joints are connected using an electric wrench, and their energy consumption is represented as follows [43]:

$$E_A^{SJ}={\displaystyle {\int }_0^{t_0}{M}_r(t)\cdot \omega }dt+{\displaystyle {\int }_0^{{\theta }_0}{M}_r(t)}d\theta$$

(14)

where $E_A^{SJ}$ represents the energy consumption from work during the screw joint process in Stage A, $t_0$ represents the initial torque time in seconds (s), ${\theta }_0$ represents the set rotation angle in radians (rad), $M_r$ represents the torque displayed on the electric wrench in Newton-meters (N·m), and $\omega$ represents the angular velocity in radians per second (rad/s).

The energy consumption carbon emission accounting model for SJ can be represented as follows:

$$C{E}_{A\text{-}E}^{SJ}=E_A^{SJ}{\alpha }_{A\text{-}screw}$$

(15)

where $C{E}_{A\text{-}E}^{SJ}$ represents the carbon emissions from energy consumption during the screw joint process, and ${\alpha }_{A\text{-}screw}$ represents the carbon emission coefficient of the screws.

(2)

Key Joint (KJ)

Key joints are typically divided into two types: loose key joint and tight key joint. The energy consumption can be determined by analyzing the forces acting on the key. Therefore, the energy consumption model for the KJ stage is as follows:

$$E_A^{KJ}={\displaystyle \sum _{i=1}^{n_{key}}{F}_{A\text{-}i}^{KJ}{s}_i}$$

(16)

where $E_A^{KJ}$ represents the energy consumption generated by the key joint process, $n_{key}$ represents the number of keys used in the joint, $F_{A\text{-}i}^{KJ}$ represents the force acting on the i-th key, and $s_i$ represents the assembly length of the i-th key.

The energy consumption carbon emission accounting model for the KJ can be represented as follows:

$$C{E}_{A\text{-}E}^{KJ}=E_A^{KJ}{\alpha }_{A\text{-}key}$$

(17)

where $C{E}_{A\text{-}E}^{KJ}$ represents the carbon emissions from energy consumption during the key joint process, and ${\alpha }_{A\text{-}key}$ represents the carbon emission coefficient of the keys.

(3)

Pinned Joint (PJ)

Similar to the key joint, the energy consumption carbon emission model for the PJ should be analyzed based on the forces involved. Therefore, the energy consumption carbon emission accounting model for the pinned joint can be represented as follows:

$$C{E}_{A\text{-}E}^{PJ}=E_F^{PJ}{\alpha }_{F\text{-}pinned}=({\displaystyle \sum _{i=1}^{n_{pinned}}{F}_{F\text{-}i}^{PJ}\cdot l_i}){\alpha }_{F\text{-}pinned}$$

(18)

where $C{E}_{A\text{-}E}^{PJ}$ represents the carbon emissions from energy consumption during the pinned joint process, $E_A^{PJ}$ represents the energy consumption of the PJ, ${\alpha }_{A\text{-}pinned}$ represents the carbon emission coefficient of the pins used in the joint, $n_{pinned}$ represents the number of pins used in the joint, $F_{A\text{-}i}^{PJ}$ represents the force acting on the i-th pin during assembly, and $l_i$ represents the assembly length of the i-th pin.

3.4. T Stage Carbon Emission Accounting

After the assembly of mechanical products, it is necessary to conduct testing to verify their compliance before they can be delivered to the market. Therefore, establishing a carbon emission accounting model for the T stage is essential.

(1)

T-I carbon emission model

In the T stage, Step I involves placing and installing the product on the testing equipment before conducting the actual testing. This is particularly relevant for larger-sized products that require lifting during installation. Thus, the T-I carbon emission accounting model can be represented as follows:

$$C{E}_{T\text{-}\mathrm{I}}={\lambda }_P{\displaystyle \sum _{n=1}^N{f}_n(E_{T\text{-}\mathrm{I}-n}^l+E_{T\text{-}\mathrm{I}-n}^c)}$$

(19)

where, $C{E}_{T\text{-}\mathrm{I}}$ represents the carbon emissions during the T-I stage, $f_n$ represents the number of times the product is installed during testing, $E_{T\text{-}\mathrm{I}-n}^l$ represents the energy consumption for lifting the product during each installation (per instance), $E_{T\text{-}\mathrm{I}-n}^c$ represents the energy consumption for clamping the product during testing, and ${\lambda }_P$ represents the carbon emission factor of the product.

(2)

T-II carbon emission model

In the T stage, Step II involves the actual testing of the product. The main sources of carbon emissions in this stage are electricity consumption and the testing equipment.

During product testing, there are two stages that contribute to electricity consumption: the testing stage and the pressure-holding stage. Therefore, the carbon emission accounting model for electricity consumption in the T-II stage can be represented as follows:

$$C{E}_{T\text{-}\mathrm{II}-e}={\displaystyle \sum _{n=1}^N(E_{T\text{-}\mathrm{II}-n}^t+E_{T\text{-}\mathrm{II}-n}^p){\beta }_e}$$

(20)

where $C{E}_{T\text{-}\mathrm{II}-e}$ represents the carbon emissions caused by electricity consumption in the T-II stage, $E_{T\text{-}\mathrm{II}-n}^t$ represents the electricity consumption for testing the product during each instance (per test), $E_{T\text{-}\mathrm{II}-n}^p$ represents the electricity consumption for pressure holding the product during each instance (per pressure holding), and ${\beta }_e$ represents the carbon emission factor of electricity.

The carbon emissions caused by the loss of testing equipment in the T-II stage can be expressed in a similar way to the P and A stages, as follows:

$$C{E}_{T\text{-}\mathrm{II}-eq}=C{E}_{eq}{\displaystyle \frac{t_{use\text{-}eq}}{T_{life\text{-}eq}}}{\gamma }_{eq}$$

(21)

where $C{E}_{T\text{-}\mathrm{II}-eq}$ represents the carbon emissions caused by the loss of testing equipment in the T-II stage, $C{E}_{eq}$ represents the hidden carbon emissions of the testing equipment during the detection of product n, $t_{use\text{-}eq}$ represents the usage time of the testing equipment, $T_{life\text{-}eq}$ represents the lifespan of the testing equipment, and ${\gamma }_{eq}$ represents the utilization rate of the testing equipment.

3.5. Product Carbon Emission Accounting Process

By dividing the carbon emissions of the product into the P-A-T stages, carbon emission accounting models have been established for each stage. Therefore, when calculating the carbon emissions of the product, the accounting process can refer to Figure 3.

4. Example Application of a Certain Type of Ball Valve

Ball valves are widely used in various fields such as petrochemical, power generation, metallurgy, pharmaceuticals, water treatment, natural gas pipelines, heating, and ventilation. They play an important role in these industries. Therefore, this section takes the specific model of a three-piece fixed ball valve as the research object, uses the production data, process flow, assembly process, and other information provided by a ball valve company, and combines it with the quantitative carbon emission model proposed in this paper to quantitatively calculate the carbon emission in the production process of a ball valve. The structure of the ball valve is shown in Figure 4.

4.1. Carbon Emission at P Stage of Ball Valve

4.1.1. Ball Valve P-PP Carbon Emission

The purchased parts of the ball valve mainly include blanks, pins, keys, and threaded fasteners for various parts of the ball valve. The production information for the purchased parts is shown in

Table 3. Information table of P-PP.

P-PP Type	Unit	Quantity	Weight
Blank of ①	piece	2	6 kg
Blank of ②	piece	2	4 kg
Blank of ③	piece	1	3 kg
④	piece	1	1 kg
⑤	piece	1	1 kg
⑥	piece	2	1 kg
Blank of ⑦	piece	1	3 kg
⑧	piece	2	2 kg
Pin	group	1	0.3 kg
Key	group	1	0.2 kg
Threaded fastener	group	1	0.5 kg

.

When calculating the carbon emissions for the production of P-PP, it should include the carbon emissions from material consumption and electricity consumption related to all types of parts mentioned in Table 3. By combining these factors with Formula (1), the production carbon emission model for P-PP can be obtained as follows:

$$C{E}_{P\text{-}PP\text{-}M}={\displaystyle \sum C{E}_m}+{\displaystyle \sum C{E}_e}$$

(22)

For each part of the ball valve, they are all forgings, and the carbon emission factor for the raw material is 6.356 kgCO₂e/kg [44], while the carbon emission factor for electricity is 0.381 kgCO₂e/kWh. During the P-PP forging process, a total of 1.67 kg of raw material is consumed, and the electricity consumption during production is approximately 1.306 kWh.

Table 4. Material and electric carbon emissions of P-PP (Unit: kgCO₂e).

P-PP Type	Material Carbon Emissions	Electric Carbon Emissions
Blank of ①	3.178	0.149
Blank of ②	1.272	0.1
Blank of ③	1.271	0.074
④	0.636	0.025
⑤	0.508	0.025
⑥	0.636	0.025
Blank of ⑦	1.907	0.074
⑧	0.636	0.05
Pin	0.127	0.007
Key	0.127	0.005
Threaded fastener	0.318	0.012

shows the material consumption carbon emissions and electricity consumption carbon emissions for each purchased part. Therefore, the production carbon emissions amount to 11.163 kgCO₂e.

According to Formula (2), for the sake of simplification, this paper assume that the purchased parts are transported from the same location to the manufacturer using the same type of transportation. Therefore, we can treat the purchased parts as a whole and calculate the carbon emissions from transportation. Taking the transportation of one unit of purchased part as an example, the calculation parameters are shown in

Table 5. Calculation parameters of carbon emission in P-PP transportation.

Parameter	Value
$\eta$	1
$d_s$	10 km
$N_{P\text{-}PP}$	1
$m_{P\text{-}PP}$	20 kg
${\beta }_{truck}$	0.04 kgCO2e/km

. Finally, the calculated transportation carbon emissions for P-PP amount to 8.8 kgCO₂e.

Therefore, the total carbon emissions for P-PP are as follows:

$$\begin{array}{ll}C{E}_{P\text{-}PP}& =C{E}_{P\text{-}PP\text{-}M}+C{E}_{P\text{-}PP\text{-}T}\\ & =19.277kgC{O}_{2}e\end{array}$$

(23)

4.1.2. Carbon Emissions for Ball Valve P-HP

The self-made parts of the ball valve include the valve body, valve bonnet, valve stem, and ball. The processing operations for P-HP are controlled by the manufacturing company itself. Therefore, when conducting a quantitative analysis of carbon emissions for P-HP, carbon emissions should be analyzed separately for different processing operations. Figure 5 provides an overview of the processing operations for P-HP.

Assume that the same type of CNC machine tool is used in each process of the enterprise, its equipment power is 22 kW, and its invisible carbon emission is estimated to be 3000 kgCO₂e. The carbon emission factors of various consumables in the P-HP processing process are shown in

Table 6. Carbon emission factors for various consumption items.

Material	Carbon Emission Factor
Turning tool	0.0126 kgCO2e/kg
Milling cutter	0.009 kgCO2e/kg
Cutting fluid	0.469 kgCO2e/L
Lubricant oil	0.469 kgCO2e/L
Metal chips	0.195 kgCO2e/kg

.

(1)

Valve body machining

Valve body machining consists of four operations: (1) precision turning of the A-end face, outer diameter, and inner bore; (2) precision turning of the B-end face and inner bore; (3) milling of flat surfaces; and (4) drilling of threaded holes. The carbon emission model for valve body machining is as follows:

$$C{E}_{P\text{-}HP}^{\mathrm{valve}\mathrm{body}}=C{E}_{process1}^{\mathrm{valve}\mathrm{body}}+C{E}_{process2}^{\mathrm{valve}\mathrm{body}}+C{E}_{process3}^{\mathrm{valve}\mathrm{body}}+C{E}_{process4}^{\mathrm{valve}\mathrm{body}}$$

(24)

The relevant calculation parameters are shown in

Table 7. Computational parameters for valve body machining.

Computational Parameter	Parameter Value
Raw material consumption	0.25 kg
Cutting fluid consumption	48 L
Cutting tool usage time	15 min
Milling cutter usage time	8 min
Drill bit usage time	5 min
Electric consumption	11 kWh

. Therefore, the calculated carbon emissions for valve body machining amount to 5.495 kgCO₂e. According to the ball valve structure diagram in Figure 4, a ball valve consists of two valve bodies (left and right). Hence, the total carbon emissions for valve body machining are 10.99 kgCO₂e. The carbon emissions for each operation in the valve body manufacturing process are shown in

Table 8. Carbon emissions from each process in valve body machining.

Manufacturing Process	Carbon Emissions (kgCO2e)
Process 1	1.939
Process 2	1.507
Process 3	1.075
Process 4	0.974

.

(2)

Valve bonnet machining

Valve bonnet machining consists of five operations: (1) precision turning of the A-end; (2) precision turning of the inner bore and boss; (3) precision turning of the B-end; (4) drilling of threaded holes and flange holes; and (5) turning of waterlines. The carbon emission model for valve bonnet machining is as follows:

$$\begin{array}{ll}C{E}_{P\text{-}HP}^{\mathrm{valve}\mathrm{bonnet}}& =C{E}_{process1}^{\mathrm{valve}\mathrm{bonnet}}+C{E}_{process2}^{\mathrm{valve}\mathrm{bonnet}}+C{E}_{process3}^{\mathrm{valve}\mathrm{bonnet}}\\ & +C{E}_{process4}^{\mathrm{valve}\mathrm{bonnet}}+C{E}_{process5}^{\mathrm{valve}\mathrm{bonnet}}\end{array}$$

(25)

The relevant calculation parameters are shown in

Table 9. Computational parameters for valve bonnet machining.

Computational Parameter	Parameter Value
Raw material consumption	0.5 kg
Cutting fluid consumption	30 L
Cutting tool usage time	30 min
Drill bit usage time	7 min
Electric consumption	14.7 kWh

. As there are two valve bonnets (upper and lower), the calculated carbon emissions for valve bonnet machining amount to 8.268 kgCO₂e. The carbon emissions for each operation in the valve bonnet manufacturing process of the ball valve are shown in

Table 10. Carbon emissions from each process in valve bonnet machining.

Manufacturing Process	Carbon Emissions (kgCO2e)
Process 1	1.791
Process 2	2.322
Process 3	1.791
Process 4	1.41
Process 5	0.954

.

(3)

Valve stem machining

Valve stem machining consists of five main operations: (1) precision turning of the large end; (2) precision turning of the small end; (3) milling of the large end’s opposite side; (4) milling of key grooves; and (5) drilling of threaded holes on the small end. The carbon emission model for valve stem machining is as follows:

$$C{E}_{P\text{-}HP}^{\mathrm{valve}\mathrm{stem}}=C{E}_{process1}^{\mathrm{valve}\mathrm{stem}}+C{E}_{process2}^{\mathrm{valve}\mathrm{stem}}+C{E}_{process3}^{\mathrm{valve}\mathrm{stem}}+C{E}_{process4}^{\mathrm{valve}\mathrm{stem}}+C{E}_{process5}^{\mathrm{valve}\mathrm{stem}}$$

(26)

The relevant calculation parameters are shown in

Table 11. Computational parameters for valve stem machining.

Computational Parameter	Parameter Value
Raw material consumption	0.2 kg
Cutting fluid consumption	25 L
Cutting tool usage time	15 min
Milling cutter usage time	10 min
Drill bit usage time	2 min
Electric consumption	7.3 kWh

. Therefore, the calculated carbon emissions for valve stem machining amount to 5.084 kgCO₂e. The carbon emissions for each operation in the valve stem manufacturing process of the ball valve are shown in

Table 12. Carbon emissions from each process in valve stem machining.

Manufacturing Process	Carbon Emissions (kgCO2e)
Process 1	1.796
Process 2	1.261
Process 3	1.434
Process 4	0.296
Process 5	0.297

.

(4)

Ball machining

Ball machining consists of five main operations: (1) rough turning of the end face, outer diameter, and inner bore; (2) precision turning of the end face, outer diameter, and inner bore; (3) milling of grooves; (4) grinding of the outer diameter; and (5) drilling of threaded holes. The carbon emission model for ball machining is as follows:

$$C{E}_{P\text{-}HP}^{\mathrm{valve}\mathrm{ball}}=C{E}_{process1}^{\mathrm{valve}\mathrm{ball}}+C{E}_{process2}^{\mathrm{valve}\mathrm{ball}}+C{E}_{process3}^{\mathrm{valve}\mathrm{ball}}+C{E}_{process4}^{\mathrm{valve}\mathrm{ball}}+C{E}_{process5}^{\mathrm{valve}\mathrm{ball}}$$

(27)

The relevant calculation parameters are shown in

Table 13. Computational parameters for valve ball machining.

Computational Parameter	Parameter Value
Raw material consumption	0.4 kg
Cutting fluid consumption	40 L
Cutting tool usage time	20 min
Milling cutter usage time	4 min
Grinding time	8 min
Drill bit usage time	3 min
Electric consumption	13.5 kWh

. Therefore, the calculated carbon emissions for ball machining amount to 7.298 kgCO₂e. The carbon emissions for each operation in the ball manufacturing process of the ball valve are shown in

Table 14. Carbon emissions from each process in valve ball machining.

Manufacturing Process	Carbon Emissions (kgCO2e)
Process 1	2.065
Process 2	2.292
Process 3	1.023
Process 4	1.268
Process 5	0.65

.

4.2. Carbon Emissions of Ball Valve Stage A

The assembly process of the ball valve involves the assembly of purchased and self-made parts. The main source of carbon emissions in this stage is the joining method between the various parts, which includes pin, key, and threaded connections. The assembly process of the ball valve is illustrated in Figure 6.

Figure 6 shows that the key connection is primarily used for radial fixation between the valve stem and bonnet. The combination of the parts that utilize the pin connection includes the valve body and valve bonnet, fixing block and valve bonnet, valve body and locating sleeve, and connecting plate and locating sleeve. As for the threaded connection, it also involves several parts combinations: valve body and valve seat, sleeve and valve body, and connecting plate and sleeve. The quantities of keys, pins, and threaded fasteners used for these three types of connections are shown in

Table 15. The quantity of each jointing part and their carbon emission factor of the raw materials.

Jointing Part	Quantity	Carbon Emission Factor (kgCO2e/kg)
Key	1	3.220
Pinned	16	0.043
Threaded fasteners	12	2.050

.

The carbon emission accounting model for Stage A is as follows:

$$\begin{array}{ll}C{E}_A& =C{E}_{A\text{-}E}^{KJ}+C{E}_{A\text{-}ele}^{KJ}+C{E}_{A\text{-}eq}^{KJ}+C{E}_{A\text{-}E}^{PJ}\\ & +C{E}_{A\text{-}ele}^{PJ}+C{E}_{A\text{-}eq}^{PJ}+C{E}_{A\text{-}E}^{SJ}+C{E}_{A\text{-}ele}^{SJ}+C{E}_{A\text{-}eq}^{SJ}\end{array}$$

(28)

Since only one flat key is used in the mentioned ball valve and no auxiliary equipment is required for assembly, its carbon emissions can be neglected. Therefore, by using Formulas (11)–(18), the carbon emissions from pin connections are calculated to be 0.02 kgCO₂e, and the carbon emissions from threaded connections are calculated to be 0.145 kgCO₂e. Thus, the total carbon emissions for Stage A amount to 0.165 kgCO₂e.

4.3. Carbon Emission at T Stage of Ball Valve

The ball valve needs to undergo three testing methods: strength testing, high-pressure water sealing testing, and low-pressure gas sealing testing. Strength testing involves closing both valve body ends on the test bench with the ball semi-open. The exhaust port is opened, and pressure is gradually increased to 10.4 MPa by applying pressure from one end. Once the test medium overflows from the exhaust port, the exhaust port is closed with a screw plug. The pressure is then held for 5 min. High-pressure water sealing testing requires closing both ends of the valve on the test bench with the valve in a semi-open position. Pressure is applied from both ends, and the exhaust port is opened. The valve is closed when the test medium overflows from the exhaust port. The pressure gradually increases to the specified pressure of 6.3 MPa and is held for 5 min. The test is considered qualified if no leakage is observed at the exhaust port. During the low-pressure gas sealing testing, both ends of the valve are closed on the test bench with the valve closed. The exhaust port is opened, and pressure is applied from both ends, gradually increasing from zero to the specified pressure of 0.6 MPa. The ball is closed at this pressure, and it is held for 5 min. If no leakage is observed, the test is considered qualified.

According to Formula (21), the ball valve requires three installations on the testing equipment during the testing process, resulting in a calculated carbon emission of 0.383 kgCO₂e for Stage T-I.

According to Formulas (22) and (23), the calculated carbon emission caused by the consumption of electricity in Stage T-II is 3.408 kgCO₂e, and the carbon emission caused by the loss of testing equipment is 0.0038 kgCO₂e. Therefore, the total carbon emission generated in Stage T-II amounts to 3.412 kgCO₂e.

Therefore, the total carbon emission for the T stage is 3.795 kgCO₂e.

4.4. Analysis of Valve Carbon Emission Accounting Results

4.4.1. Ball Valve P-PP Carbon Emission Analysis

Based on the analysis of the 11 self-made parts, Figure 7 is obtained. The total carbon emissions for P-PP are 11.163 kgCO₂e. In the valve body blank manufacturing process, material and electricity consumption contribute the highest carbon emissions, accounting for 29.9% and 27.3%, respectively. This indicates that a significant amount of material and electricity is consumed during the forging process of the valve body blank. Electricity consumption during the forging of the valve bonnet ranks second, accounting for 18.3%, while the forging of the ball blank ranks second in carbon emissions caused by material consumption, accounting for 18%. Due to the low demand and small volume of keys in the ball valve, material and electricity consumption contribute the least carbon emissions, accounting for 1.2% and 0.9%, respectively.

Ball valve manufacturers have difficulty controlling the carbon emissions of purchased parts without intervening in their manufacturing processes. For the parts, the larger the design size, the higher the carbon emissions generated during production. Therefore, when manufacturers design ball valves, they should strive to minimize the dimensions of the designed parts while meeting the usage requirements, thus reducing the carbon emissions of purchased parts.

4.4.2. Carbon Emission Analysis of Ball Valve P-HP

According to Section 4.1.2, the carbon emissions of the four self-made parts, namely valve body, valve bonnet, valve stem, and ball, are 10.99 kgCO₂e, 8.268 kgCO₂e, 5.084 kgCO₂e, and 7.298 kgCO₂e, respectively. Since the processes involved in manufacturing these parts are all types of machining, the analysis of carbon emissions caused by material consumption should consider the characteristics of each process. This includes accounting for factors such as raw material, cutting fluid, turning tools, milling tools, drills, and grinding tools. Additionally, carbon emissions caused by energy consumption during machining and equipment loss should also be taken into account.

Figure 8 presents the carbon emission sources involved in the manufacturing process of P-HP and their respective proportions in each process. Subfigures (a), (b), (c), and (d) depict the carbon emissions in different stages of the valve body, valve bonnet, valve stem, and ball, respectively.

By comparing each graph horizontally, it is evident that each process generates a certain amount of chips or waste, resulting in material consumption. For example, in Figure 8a, the material consumption for the four stages is 0.407 kgCO₂e, 0.356 kgCO₂e, 0.305 kgCO₂e, and 0.203 kgCO₂e, respectively. Regarding the consumption of cutting fluid, under the condition of the same volume of cutting fluid used in each process, longer processing times lead to relatively higher carbon emissions from cutting fluid. For instance, in Figure 8b, compared to Process 2, Process 6 has a shorter turning time, resulting in less carbon emissions from cutting fluid, with a value of 0.0011 kgCO₂e. Each machining process consumes electricity through the utilization of machinery. Thus, carbon emissions caused by energy consumption and equipment loss are reflected in each process. The proportion of carbon emissions caused by energy consumption in machining processes is relatively significant.

Through the vertical comparison of the four graphs, it is evident that although machining processes involve tool consumption, they contribute relatively less to carbon emissions and have a relatively more minor impact on the machined products. Cutting fluid, an essential material in machining processes, leads to carbon emissions during consumption. Under the same processing time and type, the more cutting fluid used, the higher the carbon emissions. For example, in Process 1, the valve bonnet and ball are involved in turning operations. Under similar processing times, increased cutting fluid consumption leads to changes in carbon emissions. The carbon emissions caused by cutting fluid consumption in Process 1 of the valve bonnet amount to 0.0023 kgCO₂e, while in the ball machining, it reaches 0.0038 kgCO₂e.

In summary, optimizing the manufacturing process to reduce energy consumption and controlling the amount of chips and waste generated during machining is of significant importance in controlling the carbon emissions of P-HP.

4.4.3. Analysis of Carbon Emissions in Ball Valve

The carbon sources in the production process of ball valves can be categorized into six types: materials, energy, equipment, transportation, testing, and assembly. Material consumption during the production process of ball valves primarily occurs in the P phase, including raw materials, cutting tools, and fluids. Therefore, material consumption is one of the main factors influencing carbon emissions in ball valve production, accounting for 35.6% of the total carbon emissions, as shown in Figure 9.

Energy, as the primary source for sustaining machinery operation, permeates the entire ball valve production process. The carbon emissions caused by energy consumption significantly impact the carbon emissions of ball valves. The carbon emissions from energy consumption in the ball valve production process amount to 19.405 kgCO₂e, accounting for 38.8% of the total emissions.

Equipment continuously releases its invisible emissions during operation, contributing to carbon emissions collectively. However, due to equipment’s typically longer lifespan, the impact of equipment wear on carbon emissions in ball valve production is minimal, amounting to 0.0483 kgCO₂e, representing 0.1% of the total carbon emissions.

Figure 9 shows that the transportation emissions of purchased parts account for 17.6% of the carbon emissions in ball valve production, becoming a significant part of the overall emissions. This is primarily influenced by transportation vehicles, transportation distance, and fuel consumption during transportation.

5. Conclusions

Low-carbon development in the manufacturing industry is one of the key areas for global sustainable development. With climate change and environmental issues becoming increasingly prominent, the industry must take proactive measures to reduce carbon emissions and achieve sustainability. Therefore, establishing a comprehensive carbon emissions quantification model for mechanical products is significant in controlling and reducing carbon emissions in the manufacturing industry.

This paper proposes a three-stage accounting model for quantifying carbon emissions of mechanical products based on the life cycle assessment (LCA) method. Starting from the carbon emissions in the product manufacturing process, the model divides product carbon emissions into three stages: parts, assembly, and testing. Detailed modeling is conducted for the production and transportation of purchased parts, processing steps of self-made parts, connection methods, and the installation and testing of products on testing equipment. The model has strong generality and can be used for the carbon accounting of everyday mechanical products. Through this model, mechanical manufacturing companies can calculate the carbon emissions at each stage and identify corresponding optimization solutions.

Finally, the effectiveness and feasibility of the model are validated using a specific three-piece ball valve as an example. The validation reveals that carbon emissions from material consumption, energy consumption, and transportation account for a significant proportion in the ball valve production process, namely 35.6%, 38.8%, and 17.6%, respectively. The corresponding carbon emissions are 17.854 kgCO₂e, 19.405 kgCO₂e, and 8.8 kgCO₂e.

Based on the above analysis, the research significance of this paper is as follows:

(1) Based on the LCA method, this paper comprehensively considers the major carbon emissions sources in the product manufacturing process and establishes a corresponding carbon emissions accounting model. The model is strong and general and suitable for general mechanical manufacturing industries with low theoretical requirements for readers.

(2) This paper divides the carbon emissions of mechanical products into stages (P-A-T). Through this model, manufacturing companies can obtain carbon emissions information for each production stage of the product, providing low-carbon optimization directions for enterprises and improving the low-carbon competitiveness of their products.

Future research will aim to build a more comprehensive quantitative model of carbon emissions from product manufacturing workshops. In addition to considering the impact of factors such as the transportation route of the product and its components, the number of mass production, and the manufacturing and assembly sequence of the parts, the subsequent research should also include the impact of dynamic characteristics such as urgent order insertion, equipment aging failure, etc., on the carbon emissions of mechanical products. The research on these factors will further refine and optimize the carbon emissions accounting of each link in the product manufacturing process. In addition, based on the carbon emission model proposed in this paper, the optimization method of product process planning and workshop scheduling optimization technology will be deeply studied, and how to effectively coordinate resource utilization and production scheduling in a dynamic production environment will be explored to minimize the overall carbon emission. The research in these directions will provide new theoretical support and practical guidance for green manufacturing and help promote the manufacturing industry’s sustainable development.