Equipment Manufacturing Industry Research Articles

IoT- enabled crop waste mulching machine for sustainable farming: perspective of circular economy

Abstract A large amount of crop waste is generated after crop harvesting. A substantial quantity of waste on the farm is burnt to clear the field, contributing to environmental harm and global warming. The study aims to develop a technological solution for crop waste management (CWM) by designing and developing an IoT-enabled crop waste mulching machine. This initiative addresses the environmental and health issues caused by burning crop waste on farms. The research involves designing and developing an IoT-enabled mulching machine that can be attached to the back side of a tractor. The machine consists of power-transmitting elements, supports, and mechanisms to distribute mulching material evenly onto the plant bed. It incorporates advanced IoT load cell sensors, soil moisture sensors, and proximity sensors to optimize the mulching process based on soil moisture content and to prevent machinery blockages. The IoT-enabled mulching machine effectively manages crop waste by utilizing it in mulch, thus preventing the harmful practice of burning waste. This machine ensures a more efficient, safer, and environmentally friendly approach to mulching, offering significant improvements over traditional manual mulching methods.
The novelty of this research lies in integrating IoT technologies within mulching machine. The mulching machine uses sensors to automate and optimize the mulching process, representing a significant technological advancement over conventional methods. The study offers practical benefits by reducing labour requirements, minimizing the risk of injuries, and ensuring a more uniform mulch application. This technology facilitates more sustainable farming practices, aligning with global sustainability goals. The study can potentially revolutionize the agricultural equipment manufacturing industry (AEMI) by shifting the focus toward environmental sustainability. It promotes replacing plastic film mulching machines with more eco-friendly crop waste mulching solutions. This technology has the potential to reduce air pollution, carbon emissions, and mitigate climate. It also enhances soil health through better mulching practices.

How Does Innovation-Collaboration Network Structure Influence Regional Economic Resilience?

This paper examines whether different structures of co-patenting networks affect regional economic adaptation and adaptability in divergent ways. Adaptation differentiates from adaptability by recovering in a pre-shock growth path, while adaptability entails forging a new growth path. Focusing on computer, electronic, and electrical equipment manufacturing industries in U.S. metropolitan and micropolitan areas from 1990 to 2012, the study reveals that complete networks, characterized by closely connected nodes, promote adaptation but weaken adaptability. In contrast, coalitional networks, featuring loosely connected subgroups, enhance adaptability but hurt adaptation. The study contributes to regional economic resilience literature by empirically demonstrating the trade-off relationship between adaptation and adaptability from network structures’ perspective. Practically, the study helps policy makers to effectively allocate stimuli, such as grants and tax incentives, to develop targeted co-patenting networks to improve adaptation or adaptability.

Measurement of stress optical coefficients for GFRP based on terahertz time-domain spectroscopy

Glass Fiber-Reinforced Polymer (GFRP) finds extensive applications in the high-end equipment manufacturing industry owing to its advantages of light weight, high strength, and corrosion resistance. Since the residual stress in GFRP builds up during the curing process and affect its mechanical properties and service life, the characterization of the residual stress in GFRP is crucial. In this study, we establish a theoretical model based on the anisotropic stress-optics law for the orthorhombic crystalline system to describe the terahertz-elasticity of GFRP and calibrate the stress optical coefficients of GFRP. First, the residual stress in GFRP at different curing temperatures are measured by fiber Bragg grating sensors. Then, the refractive index of GFRP with different residual stress are obtained based on transmission-type THz-TDS. Finally, based on the proposed photoelastic model of GFRP, the stress optical coefficients of GFRP are measured by combining the measurement results of residual stress and refractive index. The experimental results show that the refractive index of GFRP decreases with the increase of residual stress; the stress optical coefficients of GFRP are determined as q11 = −5.612 × 10−9 Pa−1, q12 = −2.548 × 10−9 Pa−1, q21 = −1.305 × 10−8 Pa−1, q22 = −1.408 × 10−9 Pa−1. The modeling of terahertz photoelasticity in GFRP and the determination of stress optical coefficients provide a basis for characterizing residual stress in GFRP by THz-TDS.

Strategies for Green Supply Chain for Agriculture Equipment Manufacturing Industries: Perspective of Blockchain- IoT Integrated Architecture

In order to protect the environment, manufacturing sectors have begun implementing a green supply chain (GSC) strategy. Governments are enacting increasingly stringent environmental regulations; consequently, industries must reduce the environmental impact of their supply chains. Our research investigates the barriers to implementing a GSC in the agriculture equipment manufacturing industries (AEMI). This research aims to discover and prioritize the barriers that impede the implementation of sustainable supply chain strategies in the AEMI. Through an in-depth literature review, contributions from experts, and empirical analysis, seventy-one barriers are identified across ten categories. The top barrier in each category is determined using the Delphi approach. The Fuzzy Technique for Order of Preference by Similarity to the Ideal Solution (F-TOPSIS) method creates an exhaustive framework that evaluates and ranks these barriers. The top five barriers are the lack of an environmental partnership with buyers and suppliers, the design complexity when reusing or recycling old goods or products, carbon emissions, paint shop emissions, lack of environmental education and training professionals that lack the necessary skills and less manpower available for the greening supply chain. This framework facilitates decision-makers to organize resources and create effective strategies for overcoming identified barriers. In addition, we proposed a blockchain IoT integrated architecture and strategies. This integrated architecture and strategies will help to mitigate all GSC barriers. It also increases the supply chain's transparency, traceability and effectiveness, fostering sustainability practices and reducing environmental impacts. Blockchain and IoT facilitate real-time data collaboration, computerized transactions and the implementation of smart contracts, thereby enhancing cooperation, trust and collaboration among stakeholders. Implementing GSC practices enables manufacturers to reduce waste and increase productivity, thereby saving funds. In addition, adopting sustainable practices improves these industries' reputation and brand image among environmentally conscious customers, investors and other stakeholders.

Improving the Performance of the Machining Process by Using Ultra‐Advanced Tools in a Clean Turning of Inconel 686 Using the Minimum Quantity Lubrication Method

ABSTRACTThe high tensile strength and high resistance of nickel‐based superalloy 686 against high temperatures and corrosion rates have made it a widely used in important applications such as the aerospace industry, high pollution‐ and corrosion‐resistance equipment manufacturing and petrochemical industry. Therefore, the machining of this advanced alloy with its unique properties is extremely important and can be challenging. Significant increase in input parameters levels, reduction of machining costs, improvement of surface and subsurface properties and clean production are among the issues that should be considered in dealing with Inconel 686 turning operations. Simultaneous application of advanced tools such as polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) and optimised minimum quantity lubrication (MQL) method and evaluating the results obtained with a wide range of output parameters related to machining process performance and tribological properties can be proposed as an innovation and a solution to this problem in this article. This study analyses several output parameters with different speeds and feeds to evaluate the effect of cutting insert type on machining process performance and tribological properties. The output parameters include tool wear, residual stress, cutting zone temperature, surface smoothness, machining forces and workpiece surface defects. The results indicated that using the optimised MQL method reduces the size of lubricant droplets and increases the surface covered by cooling. With these changes, the performance of the machining process and the parameters related to the surface integrity increase significantly. Among the parameters associated with the performance of the machining process, the PCD tool reduces the cutting zone temperature by 23%, the tool wear by 19% and the machining forces by 18% compared to the PCBN tool. In the parameters related to surface integrity, this method reduces the residual stress by 19% and the surface roughness by 9% compared to the PCBN tool. From the production index perspective, the PCD tool can significantly increase the cutting speed and feed rate, reducing production time and costs.

The Digital Transformation Path of Agricultural Machinery and Equipment Manufacturing Industry from the Perspective of Smart Agriculture

The Digital Transformation Path of Agricultural Machinery and Equipment Manufacturing Industry from the Perspective of Smart Agriculture

The Economic Evolution of the Romanian Defense Market in the Context of the World Crisis (Post-pandemic) and the Imbalance of International Security (Military Conflict in Ukraine)

Abstract The analysis of crisis management shows that any crisis will generate risks and opportunities for certain industrial sectors. The current security crisis overlaps today with other crises (climatic, economic, energy, and medical crises generated by COVID-19). The medical crisis generated by the COVID-19 pandemic has recorded considerable profits for the pharmaceutical industry and companies in the medical equipment manufacturing industry. (John A. Parnel). The defense market and armaments production industry has been steadily growing at national and international levels due to the imbalance in international security caused by Russia's military conflict. An economical inside perspective is provided due to an internal study case based on the evolution of this industry's key sector. As per the analyzed data, the market demand is currently higher than the production capacity, both at European and national levels. The industry cannot meet the requirements of the defense market. Nonetheless, the turnover of the profile companies experienced significant increases with positive effects on the recorded profit rates. After conducting a thorough evaluation of the domestic defense industry, the solution might be to privatize state-owned companies in the security industry, which may involve merging companies with similar activity profiles. Also, financial incentives, such as tax measures like those granted to personnel working in the IT industry, can help overcome the human resources issue that the Romanian defense industry is currently facing.

What drives equipment manufacturing enterprises green technology innovation in the Yangtze River Economic Belt? A configuration analysis based on DEA-fsQCA model

Under the dual backdrop of the “dual-carbon” goal and the strategic goal of "Made in China 2025", the equipment manufacturing industry, as the "industrial mother machine", has to undergo a green, low-carbon transformation. Green technology innovation is an essential component of achieving green transformation. Therefore, their green technology innovation efficiency (GTIE) deserves in-depth examination to achieve the "double carbon" goal. The aim of this study is to reveal the possible paths and models for equipment manufacturing enterprises to obtain high GTIE from a configuration perspective. Based on 94 listed equipment manufacturing companies' green technology innovation data in the Yangtze River Economic Belt (YREB) from 2018 to 2021, this paper explores the GTIE and its combination improvement path with a DEA-fsQCA model. The results indicate that: (1) The average efficiency score of the sample was 0.506, only 16 enterprises reached the production frontier, and the overall GTIE in equipment manufacturing industries as a whole showed a "first drop and then a steady upward" trend from 2018 to 2021; (2) The results of heterogeneity analysis revealed that the level of GTIE showed a characteristic of the upstream region > downstream region > midstream region, foreign-invested enterprises > private-owned enterprises> state-owned enterprises, and there is significant industrial heterogeneity, with a GTIE difference of up to 0.478 between the industries with the strongest green technologys innovation ability and those with the weakest. (3) A single conditional variable cannot constitute the necessary condition for high GTIE. There are four combination paths that can produce high GTIE: PCW+ MP-dual driven, PCW+ Fin-dual driven, COCEN-oriented, and COCEN+MP-dual driven. Further analysis shows that there is a substitution effect between the absence of the financing constraint and the existence of market power. This study provides a scientific basis for facilitating the improvement of YREB's equipment manufacturing industry's green technology innovation capabilities.

Statistical Measurement of Zhuhai's Digital Economy Development Level Based on Entropy Method

Against the backdrop of the increasing popularity of mobile internet and the expanding commercialization of fifth-generation mobile communications (5G), the digital economy is booming with continuous innovations and integrations of internet technologies such as artificial intelligence, blockchain, cloud computing, and big data. As one of the special economic zones, Zhuhai has emphasized in its work report the need to "vigorously develop the digital economy." Based on panel data from Zhuhai and its surrounding cities from 2018 to 2022, this paper empirically measures the level of digital economic development in Zhuhai and conducts a deep analysis of its development from the perspective of temporal characteristics. The research results indicate that: (1) Among various evaluation indicators of the digital economy, the output value of the communication and other electronic equipment manufacturing industries (in tens of thousands of yuan) has the greatest impact on the development of the digital economy, followed by the total volume of telecommunications business (in tens of thousands of yuan). The number of internet broadband users (in tens of thousands of households) and FTTH/O fiber-optic access users (in tens of thousands of households) have relatively smaller impacts. (2) In terms of temporal characteristics, the annual growth rate of Zhuhai's digital economy exhibits a steady decline, which differs from that of surrounding cities. (3) Regarding spatial characteristics, the development of the digital economy is highly unbalanced among different cities in Guangdong, and there is still a significant gap between Zhuhai and its surrounding cities. Based on the measurement results, countermeasures and suggestions are proposed to enhance the digital economic development in Zhuhai.

Influence Factors of Digital Economy on the Willingness of Equipment Manufacturing Industry to Green Production in the Era of Artificial Intelligence

In the age of artificial intelligence, the digital economy significantly promotes green production in manufacturing. It optimizes processes, recycles resources, drives green tech innovation, and boosts product sustainability. While there's ampleresearch on green manufacturing, studies linking it to the digital economy are limited. Given the machinery manufacturing sector's strategic importance and China's focus on green, sustainable manufacturing, this study bridges that gap. Using the Theory of Planned Behavior (TPB) and Normative Activation Model (NAM), it examines how the digital economy influences green production intentions in equipment manufacturing. The study surveys Middle Eastern equipment manufacturers, analyzes the data with SmartPLS, and finds that the digital economy positively impacts green production via personal norms, responsibility, consequence awareness, attitudes, and cost savings. These factors mediate the relationship between the digital economy and green production intentions. The paper concludes with practical recommendations based on these findings. In the era of artificial intelligence, how the digital economy provides a new path to the green production of the manufacturing industry, and provides a theoretical reference for the sustainable development of the equipment manufacturing industry.

Remanufacturing Operations in Different Financial Ownership Structures with Consideration of the Upwards Supplier

Under the increasing environmental pressure, remanufacturing has increasingly become a new mode of recycling economy and upgrading and transforming the equipment manufacturing industry. Some enterprises include remanufacturing businesses in the original production system by holding or controlling shares in other remanufacturing enterprises. This paper builds a two-echelon supply chain model composed of a supplier, a manufacturer, and a remanufacturer, considering the different ownership structures (i.e., shareholding and share-controlling) between them, in which the supplier sells non-remanufacturable parts to the manufacturer and the remanufacturer. At the same time, the optimal decisions of each firm are considered. The results show that for the manufacturer, a higher shareholding ratio means that it can obtain more profits. For the supplier, the impact of the shareholding ratio depends on the manufacturing cost. When the manufacturing cost is relatively low, the stock sharing relationship between the manufacturer and the remanufacturer will decrease the supplier’s profit. When the manufacturing cost is relatively high, it will depend on the shareholding ratio. In the case of shareholding between the manufacturer and the remanufacturer, a higher shareholding ratio will decrease the supplier’s profit. From the perspective of the supply chain, when the production cost is high enough, the supply chain’s profit decreases first and then increases with the shareholding ratio. Furthermore, the increase in the manufacturer’s shareholding in remanufacturing does not always improve the remanufacturing proportion of products.

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta.

The Yangtze River Delta (YRD) bears the vital task of driving the growth of China's equipment manufacturing industry (EMI) intelligence as an advanced region. Fostering the transformation and upgrading of the EMI in the YRD and constructing a modern production mode is vital to developing and reforming China's manufacturing industry. This paper uses industrial robot data to assess the level of intelligence (LoI) in the EMI from 2016 to 2019. The OLS (ordinary least squares) model is used for the measurements, and the MQ (the modified contribution index) is used to estimate the degree of contribution from a host of variables. It is identified that the LoI is on the rise. However, excluding railways, aerospace, shipbuilding, and other transportation equipment manufacturing, the LoI is significantly higher than in other subsectors. It is also identified that technological innovation ability, human capital density, and enterprise cost pressure govern the industry's LoI. Moreover, while there is a difference in the main influencing factors in LoI within different industries, R&D investment, technological innovation ability, and enterprise cost pressure have the most significant impact across most equipment manufacturing sub-industries.

Method of inclined hole axis adjustment based on geometric optimization and minimum zone theory

The machining accuracy of the axis position and spatial angle of the array microholes with high aspect ratio on the components of the high-end equipment manufacturing industry will directly affect the performance of the whole machine. A method of tilt hole axis adjustment is proposed in this paper. It utilizes geometric optimization and minimum zone theory to measure the position and spatial angle of the hole axis. This addresses the slight angle error that occurs after correcting the inclined hole axis using visual techniques. Based on the minimum zone criterion for the cylindricity error, the evaluation model is re-established through the inner and the outer loop and spatial projection, which includes roundness evaluation of the projection curve by an improved particle swarm optimization (PSO) algorithm and elliptic fitting by a geometric parameter method, so as to obtain the optimal solution of the axis vector and spatial angle. Experimental comparison with the theory above shows that the precision of the method proposed is better than that of the least squares method and the traditional PSO algorithm based on the minimum zone criterion. The research results indicate that the precision of the tilt angle is better than 0.03°, and simultaneously the rotation angle is better than 0.1° in the range of 1°. This experiment verifies the effectiveness and accuracy of the proposed method.

Optimization of benzene exposure risk assessment: An integrated approach utilizing internal and external concentrations with a focus on biomarkers S-PMA & t, t-MA

In the majority of occupational settings within China, the concentrations of benzene are observed to fall markedly below the demarcated detection thresholds. Employing traditional risk assessment models, the presence of exceptionally low airborne benzene exposure concentrations may infuse heightened degrees of uncertainty. Consequently, the necessity arises to investigate risk assessment methodologies more apt for the prevalent exposure environment among employees. In the present study, a pharmacokinetic model premised on urinary benzene metabolites (S-PMA and t, t-MA) was employed to ascertain a more precise daily airborne benzene exposure concentration per individual. This value was integrated into the linear multistage model as the ‘internal exposure concentration’. In conjunction with the U.S National Environmental Protection Agency's (EPA) inhalation risk assessment model predicated on the external exposure concentration, the Singapore Ministry of Manpower's (MOM) model, and the linear multistage (LMS) model, the carcinogenic and non-carcinogenic effects of benzene were evaluated for 1781 benzene-exposed employees across 76 enterprises in Jiangsu Province. Findings suggest that in the linear multilevel model assessment, the cancer risk levels based on t, t-MA and S-PMA were higher in the printing and recording media reproduction industry, automobile manufacturing industry, general equipment manufacturing industry and the furniture manufacturing industry (median 2.842 × 10−4, 2.819 × 10−4, 2.809 × 10−4, and 2.678 × 10−4), which align more consistently with the actual benzene exposure circumstances of each industry's study participants, with overall risk levels calculated by the linear multistage model exceeding those of the EPA inhalation risk assessment model and the MOM model. This implies that the linear multistage model of internal exposure, based on the reciprocal of benzene biomarkers S-PMA and t, t-MA for airborne benzene exposure, presents enhanced sensitivity and suitability for the current occupational health risk assessment of workers. Without doubt, biomarker-based benzene exposure risk assessment emerges as the optimal choice.

Surveillance of noise exposure level in industrial enterprises-Jiangsu Province, China, 2022.

Occupational noise exposure is the most prominent problem in industrial enterprises in Jiangsu Province. Since 2019, China has established the National Surveillance System for Occupational Hazards in the workplace to grasp the current occupational hazards in critical industries, including occupational noise. According to the Work Plan for Surveillance of Occupational Hazards in the Workplace (2022) issued by the National Health Commission of the People's Republic of China, the noise exposure level of 3,142 enterprises in our province was monitored, the median and interquartile range (IQR) were calculated, and the distribution of noise exposure level was described by industry classification, enterprise-scale and ownership type of the enterprise. The railway, shipping, aerospace, and other transportation equipment manufacturing industries exhibited the highest proportion (42.9%) of individual noise exposure levels exceeding 85 dB(A), followed by the motor vehicles manufacturing industry (36.4%). The proportion of individual noise exposure levels exceeding 85 dB(A) was higher in medium and small enterprises, with rates of 28.1 and 28.6%, respectively. The highest proportion of personal noise exposure levels exceeding 85 dB(A) was observed in Hong Kong, Macao and Taiwan investment enterprises (37.5%), followed by incorporated companies (34.6%) and limited liability companies (28.1%), the lowest was state-owned enterprises(15.5%). The areas with excessive noise are primarily concentrated in grinding, welding, machining, cutting, and other related operations, accounting for 61.2% of the total. Among these operations, grinding accounts for 29.8%. The highest environmental noise and individual noise intensity were found in sandblasting and grinding positions, with individual noise intensities of 115.5 dB(A) and 108.4 dB(A), respectively. The noise exposure risk is so high that cannot be ignored in the manufacturing industry, especially in Hong Kong, Macao, and Taiwan investment enterprises, incorporated companies and medium and small enterprises.

A cascaded flowshop joint scheduling problem with makespan minimization: A mathematical model and shifting iterated greedy algorithm

This paper studies a cascaded flowshop joint scheduling problem that has critical applications in the electronic information equipment manufacturing industry but has received limited attention in the scheduling field. The cascaded flowshop joint scheduling problem encompasses both a distributed permutation flowshop scheduling problem and a hybrid flowshop scheduling problem. This paper investigates the efficient scheduling of a set of jobs in two heterogeneous flowshops to minimize the makespan. We present a mixed integer linear programming mathematical model and a shifting iterated greedy algorithm, which constantly changes its search space to explore different solution spaces. Based on the specific characteristics of the problem, a hybrid scheduling approach that combines forward and backward scheduling, a step-by-step destruction and reconstruction operator, and three adaptive reconstructive methods that combine coarse-tuning and fine-tuning are proposed to explore the near-optimal solution. Through comprehensive computational comparison and statistical analysis, the results demonstrate that the proposed shifting iterated greedy algorithm performs significantly better in relative deviation index values at the same CPU running time.

Influence of martensitic transformation on the surface integrity aspects during sustainable turning of NiTi-SMA

With the development of the equipment manufacturing industry towards the direction of intelligence, the demand for the use of intelligent materials is increasing, and high-performance shape memory alloy (SMA) products are getting more and more attention. However, the current machining quality of shape memory alloy products can not meet the existing quality requirements. The mechanism of surface integrity of NiTi SMA needs to be revealed. The influence of martensitic transformation on microstructure, roughness, hardness, and superelasticity was explored. The occurrence of martensitic transformation is determined by controlling the cutting speed (lower and higher cutting speeds) and machining conditions (dry and liquid nitrogen conditions). The superelasticity was expressed quantitatively by the remnant depth ratio. The occurrence of martensitic transformation promoted the formation of the affected layer and work hardening. Meanwhile, it is an important reason for the increase in roughness and the decrease in superelasticity.

Pricing of Convertible Bonds Based on the NIG Model—A Case Study of Electrical, Electronic, and Communication Equipment Manufacturing Industry

Pricing of Convertible Bonds Based on the NIG Model—A Case Study of Electrical, Electronic, and Communication Equipment Manufacturing Industry

Leveraging graph theory approach for managing design principles for sustainable manufacturing of industry 4.0: A case study of electrical equipment manufacturing industry

Analyzing design principles and supply chain sustainability are critical for organizational success in today's competitive marketplace. The process of evaluating an organization's supply chain design principles and manufacturing sustainability entails incorporating various sources of information, which are typically uncertain, incomplete, and subjective in nature. Particularly when various organizations are confronted with significant principles such as a lack of interoperability, decentralization, virtualization, real-time and capabilities, service orientation, and so on. Using graph theory and a matrix approach (GTMA), this article attempts to analyze the interaction between design principles-related factors with a focus on operational excellence, growth and sustainability in supply chains by considering the business of Industry 4.0. We have considered electrical equipment manufacturing Industry 4.0 as test ground. Based on a literature review and expert opinions, we identified several key principles, and then explored the most significant one using graph theory and a matrix approach. The findings indicate that autonomy has been evaluated as the most significant challenge to manage design principles most effectively for sustainable manufacturing in the Industry 4.0 context. Therefore, organizations must enhance autonomous systems capable of operating and making decisions alone, without relying on external instructions or support, in order to achieve sustainability. This and the other identified principles to achieving corporate supply chain sustainability are ranked in this paper. These findings will be useful for managers and policymakers managing the interaction between people and processes, as well as corporate sustainability management in Industry 4.0-based supply chain organizations. The unique contributions of this paper can aid in the improvement of design principles and the sustainability of emerging economies' Industry 4.0 perspectives.

Does the agglomeration of high-tech industries improve the efficiency of China’s green economy? Analysis based on the marketization

High-tech industries represent a country’s advanced productivity, technological level and innovation ability, they carry the characteristics of green industries in terms of resource-saving and being environmentally friendly, and their agglomeration has a significant impact on the development of green economy. The marketization process, as an important macroenvironment for the development of high-tech industries, not only relates to the motivation of high-tech industry agglomeration but also affects the effectiveness of the agglomeration effect. It is unclear whether marketization plays a role in the relationship between high-tech industry agglomeration and green economy efficiency and whether this role has heterogeneity. Taking China’s provincial panel data from 2001 to 2020, this paper constructs a panel threshold econometric model, and examines the threshold effect of the high-tech industry agglomeration impact on green economic efficiency under different marketization levels. 1) The high-tech industry agglomeration impact on green economic efficiency has a double-threshold effect due to the marketization level, with threshold values of 5.862 and 8.938, and the promotion effect is the highest in the second threshold range. 2) Under the influence of the government-market relationship, non-state economic development, market intermediary organization development and legal environment, the impact of high-tech industry agglomeration on green economic efficiency has a single-threshold effect, with threshold values of 7.4950, 12.1960 and 11.6100. After crossing the threshold values, the impact changes from negative to positive. Factor market development has a double-threshold effect, with threshold values 10.3100 and 14.9210, and the impact changes from negative to positive and gradually increases. 3) Among the major industries, the pharmaceutical manufacturing industry (3.978 and 9.639) and the computer and office equipment manufacturing industry (3.359 and 9.639) have a double-threshold effect due to the marketization level, and the medical equipment and instrumentation manufacturing industry (9.494) has a single-threshold effect. This study is of great significance for China as it would help optimize the market environment and stimulate the green economy effect of high-tech industry agglomeration; moreover, it would provide a reference for other developing countries and transition economies.