Hasil untuk "Industrial productivity"

F. Blomsma, Geraldine Brennan

In this article, we use Hirsch and Levin's notion of umbrella concepts as an analytical lens, in order to articulate the valuable catalytic function the circular economy (CE) concept could perform in the waste and resource management debate. We realize this goal by anchoring the CE concept in this broader debate through a narrative approach. This leads to the insight that whereas the various resource strategies grouped under the CE's banner are not new individually, the concept offers a new framing of these strategies by drawing attention to their capacity of prolonging resource use as well as to the relationship between these strategies. As such, the CE offers a new perspective on waste and resource management and provides a new cognitive unit and discursive space for debate. We conclude by discussing research opportunities for the industrial ecology (IE) community relating to the concept's theoretical development and its implementation. Specifically, we pose that reinvigorating and growing the social science aspects of IE is required for both. After all, it is in understanding and facilitating the collective implementation of any idea, also the CE concept, that the potential lies for shaping our material future.

Chad Syverson

Ronghui Xie, Yi-jun Yuan, Jing-jing Huang

Tie Qiu, J. Chi, Xiaobo Zhou et al.

The Industrial Internet of Things (IIoT) is a crucial research field spawned by the Internet of Things (IoT). IIoT links all types of industrial equipment through the network; establishes data acquisition, exchange, and analysis systems; and optimizes processes and services, so as to reduce cost and enhance productivity. The introduction of edge computing in IIoT can significantly reduce the decision-making latency, save bandwidth resources, and to some extent, protect privacy. This paper outlines the research progress concerning edge computing in IIoT. First, the concepts of IIoT and edge computing are discussed, and subsequently, the research progress of edge computing is discussed and summarized in detail. Next, the future architecture from the perspective of edge computing in IIoT is proposed, and its technical progress in routing, task scheduling, data storage and analytics, security, and standardization is analyzed. Furthermore, we discuss the opportunities and challenges of edge computing in IIoT in terms of 5G-based edge communication, load balancing and data offloading, edge intelligence, as well as data sharing security. Finally, we introduce some typical application scenarios of edge computing in IIoT, such as prognostics and health management (PHM), smart grids, manufacturing coordination, intelligent connected vehicles (ICV), and smart logistics.

Ana Vafadar, F. Guzzomi, A. Rassau et al.

In recent years, Additive Manufacturing (AM), also called 3D printing, has been expanding into several industrial sectors due to the technology providing opportunities in terms of improved functionality, productivity, and competitiveness. While metal AM technologies have almost unlimited potential, and the range of applications has increased in recent years, industries have faced challenges in the adoption of these technologies and coping with a turbulent market. Despite the extensive work that has been completed on the properties of metal AM materials, there is still a need of a robust understanding of processes, challenges, application-specific needs, and considerations associated with these technologies. Therefore, the goal of this study is to present a comprehensive review of the most common metal AM technologies, an exploration of metal AM advancements, and industrial applications for the different AM technologies across various industry sectors. This study also outlines current limitations and challenges, which prevent industries to fully benefit from the metal AM opportunities, including production volume, standards compliance, post processing, product quality, maintenance, and materials range. Overall, this paper provides a survey as the benchmark for future industrial applications and research and development projects, in order to assist industries in selecting a suitable AM technology for their application.

M. C. Jensen

G. Fragapane, D. Ivanov, M. Peron et al.

Manufacturing flexibility improves a firm’s ability to react in timely manner to customer demands and to increase production system productivity without incurring excessive costs and expending an excessive amount of resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems. We develop and test an analytical model for a throughput analysis and use it to reveal the conditions under which the autonomous mobile robots (AMR)-based flexible production networks are more advantageous as compared to the traditional production lines. Using a circular loop among workstations and inter-operational buffers, our model allows congestion to be avoided by utilizing multiple crosses and analyzing both the flow and the load/unload phases. The sensitivity analysis shows that the cost of the AMRs and the number of shifts are the key factors in improving flexibility and productivity. The outcomes of this research promote a deeper understanding of the role of AMRs in Industry 4.0-based production networks and can be utilized by production planners to determine optimal configurations and the associated performance impact of the AMR-based production networks in as compared to the traditionally balanced lines. This study supports the decision-makers in how the AMR in production systems in process industry can improve manufacturing performance in terms of productivity, flexibility, and costs.

Shiyi Chen, Jane Golley

Jiaying Peng, R. Xie, Chunbo Ma et al.

Abstract Taking China’s recent SO2 Emissions Trading Pilot as a quasi-natural experiment on changing regulatory stringency and using large panel data of Chinese industrial enterprises for 1998–2007, this study identifies the productivity effects of this market-based environmental regulation by employing a difference-in-difference-in-differences design. Our results suggest that the market-based environmental regulation has exerted significant productivity-enhancing effects across all types of industrial enterprises, with stronger effects associated with privately owned, more productive, and less pollution-intensive enterprises. We also identify a dynamic productivity-enhancing effect that tends to decay slowly over time. The SO2 Emissions Trading Pilot, as a market-based environmental regulation, allows more flexible mechanisms for production adjustment and innovation than do conventional command-and-control regulations. Thus, our results provide evidence supporting the narrow but strong version of the Porter Hypothesis that strict but flexible environmental regulations are more likely to trigger positive productivity effects.

Hong-li Tang, Jianmin Liu, Jin-guang Wu

Abstract Command-and-control environmental regulation is a traditional environmental policy that is still widely used in developing countries. This study examined a rarely discussed but significant issue for environmental sustainability and economic development—the impact of command-and-control environmental regulation on enterprise total factor productivity growth—based on a large enterprise-level sample. Employing China’s “Two Control Zone” policy as a quasi-natural experiment, we used a Chinese industrial enterprise panel dataset from 1998 to 2007 to estimate the effects of command-and-control environmental regulation in a difference-in-difference framework. It is found that command-and-control environmental regulation hassignificantly hindered the growth of enterprise total factor productivity, and this negative effect was lagging and continuous. In addition, we leaned that this negative effect mainly came from the increase in costs of enterprises and the negative impact on the enterprise resource allocation efficiency. When considering enterprise heterogeneity in terms of pollution intensity, size, and ownership, the study further found that the negative effects are exacerbated for enterprises in more heavily polluting industries, those of smaller size, and those owned by foreign companies, respectively. Our research is a reexamination of the Porter hypothesis in China, and fills the gap in the literature on the micro effects of command-and-control policy on enterprise total factor productivity for developing countries. Based on a rigorous empirical analysis, we conclude that it is difficult to achieve a win–win scenario with sustainable environmental development and enterprise total factor productivity growth under command-and-control environmental regulation. Environmental regulations should have clear objectives and take a flexible approach, and it is necessary to adopt diversified environmental regulation policies based on market instruments.

Sudhi R. Sinha, Y. M. Lee

Marc Djahangard, Maximiliano Costa, Harald Bugmann et al.

Climate change is impacting forests in Central Europe, causing increased mortality and degradation of forest ecosystem services (FES). As global warming intensifies, these effects are likely to worsen, particularly through more severe droughts and increased biotic disturbances. Understanding how forests respond to different levels of warming is essential for adaptation planning. Therefore, this study analyzed changes in forest structure and FES, including timber production, climate change mitigation, recreation, and structural diversity, under three global warming scenarios. Using the LandClim model, we compared warming levels of 1.5, 2, and 3 ​°C above pre-industrial temperatures, based on 30-year periods from RCP data, to historical climate. Our research focused on Freiburg's forests in southwestern Germany, characterized by diverse tree species and an elevation range of 200–1,250 ​m a.s.l. A warming of 1.5 ​°C could temporarily increase productivity, but at 2 ​°C, biomass losses of up to 10% would occur below elevations of 450 ​m due to drought mortality. Under 3 ​°C, losses would intensify below 650 ​m up to 40%, with even drought-resistant species like pedunculate oak experiencing mortality. At higher elevations, bark beetle outbreaks caused mortality of Norway spruce, while European beech capitalized on the changing ecological conditions. Higher warming levels significantly deteriorated FES, particularly timber production, climate change mitigation, and structural diversity, while recreation was less affected. These findings emphasize the urgency of meeting Paris Agreement targets, as limiting warming below 2 ​°C can reduce severe impacts. If warming exceeds this critical threshold, even species presently considered drought-resistant, such as native sessile and pedunculate oaks and non-native red oak, could face serious threats at lower elevations. This would undermine the effectiveness of current management strategies, as these tree species are key to providing multiple FES.

Naoko Adachi, Kumiko Sugimoto, Hitomi Suzuki et al.

Background/Purpose: Work productivity reduction due to oral health problems has not been well investigated. This study aimed to examine the impact of oral health status, including periodontitis, dental caries, and oral health-related quality of life (QOL), on absenteeism and presenteeism. Materials and methods: This cross-sectional study included 559 workers of a Japanese industrial company. Data on dental health and general health checkups were obtained from workers’ health records, and the workers responded to questionnaires on work productivity loss due to oral health problems, job stress, and oral health-related QOL. The odds ratio (OR) and 95% confidence interval (CI) for presenteeism and absenteeism were calculated using multiple logistic regression analyses of oral health status and oral health-related QOL adjusting with sex, age, educational background, occupation, job stress, current smoking, and hypertension. Results: Of the 559 participants, 6.6% and 8.9% reported absenteeism and presenteeism, respectively, due to oral health problems. Multiple logistic regression analyses identified the number of decayed teeth (OR = 1.12, 95%CI = 1.02–1.24) as a significantly associated factor with presenteeism, and additionally low oral health-related QOL with both absenteeism (OR = 2.48, 95%CI = 1.20–5.11) and presenteeism (OR = 5.00, 95%CI = 2.46–10.19). Conclusion: The number of decayed teeth and low oral health-related QOL were significantly associated with presenteeism and/or absenteeism. This highlights oral health problem as a potential factor for productivity loss.

Ye Chen, Bin Zhong, Bingnan Guo

IntroductionThe implementation of energy-consuming right trading (ECRT) policy in 2017 is a major measure to promote the construction of ecological civilization and green development, which also aligns with the global trend towards sustainable energy management and carbon emission reduction.MethodsBased on energy consumption data in China from 2010 to 2021, this paper utilizes the Difference-in-Differences (DID) method to assess the extent and process of the impact of energy consuming right trading policy on the low-carbon transition of the energy structure. The transmission mechanism of industrial structure upgrading and the new-quality productive forces in the impact process was discussed, and the regulatory role of environmental regulations was tested.ResultsThe findings indicate: 1) ECRT has a strong driving effect on the low-carbon transition of the energy structure. 2) ECRT can promote low-carbon transition of the energy structure through the dual channel of promoting industrial structure upgrading and new quality productive forces. 3) The influence of ECRT on the low-carbon transition of the energy structure is different in different regions, and the higher degree of industrial agglomeration and renewable energy-rich regions are more significantly promoted by new quality productivity. 4) Environmental regulation has a significant positive moderating effect on the relationship between ECRT and low-carbon transition of the energy structure. 5) Furthermore, the exploratory analysis reveals that the positive impacts of ECRT policies on the low-carbon Transition of the energy structure translates into higher green total factor productivity and lower environmental pollution, which promotes the sustainable development of the low-carbon Transition of the energy structure.DiscussionThis paper responds to the basic question of whether energy use rights policies can promote the low-carbon Transition of the energy structure, and provides empirical evidence and policy reference not only for the development of China’s environmental policy and the direction of energy consumption but also for the international community’s efforts in sustainable energy and environmental governance.

Jingting Jin, Wenzhi Li, Liqun Wang et al.

Abstract Direct and efficient methane oxidation to methanol is an appealing route for upgrading abundant methane resources while acquiring building blocks of clean fuels and chemicals. However, owing to its highly symmetrical nature imparted chemical stability and steric hindrance, the design of multi‐ångstrom (<3.0 Å) spaced active species capable of activating its first C−H bond remains a fundamental challenge. Herein, Cu−Ni dual‐atom Pair is constructed using defect engineering and a stepwise deposition method over indium oxide to precisely modulate the C−H polarization with the Cu atom showing affinity to H end and Ni anchoring the C side. The optimal CuNi/InNT achieves an oxygenates (CH3OH and CH3OOH) productivity of 106 mmol gcat h−1, surpassing reported systems. Theoretical calculations validate the dominating role of interatomic distance for methane activation. Specifically, the dual‐atom orbital coupling effect in the minimally spaced Cu−Ni pair up‐shifts the overall d‐band center, significantly enhancing its hybridization with C/O 2p. Further modification through macroscopic reactor design boosts CH3OH yield to 36818.84 µmol gcat h−1 with 79.37% selectivity in a 1000 mL semi‐industrial prototype. This work provides a comprehensive explanation of the Cu−Ni synergy, bridging atomic‐scale catalysis with reactor design, and establishes a common design principle for binary catalysts at the electron and orbital level.

Katharina Ledebur. Ladislav Bartuska, Klaus Friesenbichler, Peter Klimek

The automotive industry is undergoing transformation, driven by the electrification of powertrains, the rise of software-defined vehicles, and the adoption of circular economy concepts. These trends blur the boundaries between the automotive sector and other industries. Unlike internal combustion engine (ICE) production, where mechanical capabilities dominated, competitiveness in electric vehicle (EV) production increasingly depends on expertise in electronics, batteries, and software. This study investigates whether and how firms' ability to leverage cross-industry diversification contributes to competitive advantage. We develop a country-level product space covering all industries and an industry-specific product space covering over 900 automotive components. This allows us to identify clusters of parts that are exported together, revealing shared manufacturing capabilities. Closeness centrality in the country-level product space, rather than simple proximity, is a strong predictor of where new comparative advantages are likely to emerge. We examine this relationship across industrial sectors to establish patterns of path dependency, diversification and capability formation, and then focus on the EV transition. New strengths in vehicles and aluminium products in the EU are expected to generate 5 and 4.6 times more EV-specific strengths, respectively, than other EV-relevant sectors over the next decade, compared to only 1.6 and 4.5 new strengths in already diversified China. Countries such as South Korea, China, the US and Canada show strong potential for diversification into EV-related products, while established producers in the EU are likely to come under pressure. These findings suggest that the success of the automotive transformation depends on regions' ability to mobilize existing industrial capabilities, particularly in sectors such as machinery and electronic equipment.

Vincenzo Petrone, Enrico Ferrentino, Pasquale Chiacchio

This paper presents the full dynamic model of the UR10 industrial robot. A triple-stage identification approach is adopted to estimate the manipulator's dynamic coefficients. First, linear parameters are computed using a standard linear regression algorithm. Subsequently, nonlinear friction parameters are estimated according to a sigmoidal model. Lastly, motor drive gains are devised to map estimated joint currents to torques. The overall identified model can be used for both control and planning purposes, as the accompanied ROS2 software can be easily reconfigured to account for a generic payload. The estimated robot model is experimentally validated against a set of exciting trajectories and compared to the state-of-the-art model for the same manipulator, achieving higher current prediction accuracy (up to a factor of 4.43) and more precise motor gains. The related software is available at https://codeocean.com/capsule/8515919/tree/v2.

Rongfei Li, Francis Assadian

Image-based visual servoing (IBVS) methods have been well developed and used in many applications, especially in pose (position and orientation) alignment. However, most research papers focused on developing control solutions when 3D point features can be detected inside the field of view. This work proposes an innovative feedforward-feedback adaptive control algorithm structure with the Youla Parameterization method. A designed feature estimation loop ensures stable and fast motion control when point features are outside the field of view. As 3D point features move inside the field of view, the IBVS feedback loop preserves the precision of the pose at the end of the control period. Also, an adaptive controller is developed in the feedback loop to stabilize the system in the entire range of operations. The nonlinear camera and robot manipulator model is linearized and decoupled online by an adaptive algorithm. The adaptive controller is then computed based on the linearized model evaluated at current linearized point. The proposed solution is robust and easy to implement in different industrial robotic systems. Various scenarios are used in simulations to validate the effectiveness and robust performance of the proposed controller.

Jiang Xu, Haoxiang Qu

Iconic products, as innovative carriers supporting the development of future industries, are key breakthrough points for driving the transformation of new quality productive forces. This article is grounded in the philosophy of technology and examines the evolution of human civilization to accurately identify the patterns of product innovation. By integrating theories from systems science, it analyzes the intrinsic logical differences between traditional products and iconic products. The study finds that iconic products are based on a comprehensive knowledge system that integrates explicit and tacit knowledge, enabling them to adapt to complex dynamic environments. Therefore, based on the method of phenomenological essence reduction and the process of specialized knowledge acquisition, this study establishes the first principle of knowledge phenomenology: "knowledge generation-moving from the tacit to the explicit-moving from the explicit to the tacit-fusion of the explicit and tacit." Grounded in knowledge phenomenology, it reconstructs the product design evolution process and establishes a forward innovative design framework for iconic products, consisting of "design problem space-explicit knowledge space-tacit knowledge space-innovative solution space." Furthermore, based on FBS design theory, it develops a disruptive technology innovation forecasting framework of "technology problem space-knowledge base prediction-application scenario prediction-coupled technology prediction," which collectively advances the innovation systems engineering of iconic products. In light of the analysis of the global future industrial competitive landscape, it proposes a strategy for enhancing embodied intelligence in iconic products.