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The purpose of this paper is to explore the possibility of an enhanced continuous liquid interface production (CLIP) with a porous track-etched membrane as the oxygen-permeable window, which is prepared by irradiating polyethylene terephthalate membranes with accelerated heavy ions.

Experimental approaches are carried out to characterize printing parameters of resins with different photo-initiator concentrations by a photo-polymerization matrix, to experimentally observe and theoretically fit the oxygen inhibition layer thickness during printing under conditions of pure oxygen and air, respectively, and to demonstrate the enhanced CLIP processes by using pure oxygen and air, respectively.

Owing to the high permeability of track-etched membrane, CLIP process is demonstrated with printing speed up to 800 mm/h in the condition of pure oxygen, which matches well with the theoretically predicted maximum printing speed at difference light expose. Making a trade-off between printing speed and surface quality, maximum printing speed of 470 mm/h is also obtained even using air. As the oxygen inhibition layer created by air is thinner than that by pure oxygen, maximum speed cannot be simply increased by intensifying the light exposure as the case with pure oxygen.

CLIP process is capable of building objects continuously instead of the traditional layer-by-layer manner, which enables tens of times improvement in printing speed. This work presents an enhanced CLIP process by first using a porous track-etched membrane to serve as the oxygen permeable window, in which a record printing speed up to 800 mm/h using pure oxygen is demonstrated. Owing to the high permeability of track-etched membrane, continuous process at a speed of 470 mm/h is also achieved even using air instead of pure oxygen, which is of significance for a compact robust high-speed 3D printer.

With the development of economy and the progress of science and technology, the function of Luoyang city is constantly enriched and expanded. The city is no longer a simple area for people to live in. The function structure of the city is affected by the external factors and is constantly expanding. Urban logistics is one of the important influencing factors. To more comprehensively and accurately understand the status and role of logistics network space in urban planning, the characteristics and development law of urban logistics structure from the theoretical point of view are analyzed in this paper with Luoyang City as the research background. The city logistics function is determined as one of the main factors affecting the economic growth of the city is determined through the literature search method, consulting professionals and other research methods. Urban road planning and design are the focus of the study; the planning and development of urban logistics road network in Luoyang City are compared and analyzed. In full consideration of the necessity of the optimization of the urban logistics network space, the preliminary optimization scheme design and suggestion of Luoyang logistics is introduced. At the end of this paper, the sustainable development and the status of the future urban logistics function are analyzed and prospected. Continuous research and analysis of multiple subjects and angles are still needed.

With the rapid increase in the consumption of electrical and electronic innovations, responsible management and recycling of electronic waste (e-waste) or waste electrical and electronic equipment (WEEE) has been a significant concern for the governments, stakeholders, researchers and industry practitioners around the world. Consumer awareness, disposal behaviour and perception are chief facets of designing sustainable management strategies. Although researchers have widely studied e-waste over many years, the research focusing on consumer awareness about e-waste recycling has gained momentum recently. This paper aims to systematise the existing literature and explore future research prospects on household e-waste sorting behaviour.

Web of science (WoS) core collection was searched using selected keywords to identify relevant articles published from 2001 to 2021. The search resulted in 1,156 research articles published from 2001 to 2021. After a detailed study, 85 articles were shortlisted for in-depth review. The review was conducted based on global trends, top journals, most prolific authors, most active e-waste research countries, and institutions centring on consumer participation in e-waste disposal and recycling behaviour. The present research has also identified around eleven factors that seem to have a bearing on consumer behaviour towards storage, disposal and recycling of e-waste.

E-waste research has gained increased attention in the last five years. The majority of the studies has focused on motivational factors and ignore the risks associated with handling e-waste. The present study reports the pertinent issue of lack of awareness among the masses about e-waste handling and disposal. Thus, bringing to the fore the lack of awareness programmes and initiatives. The analysis presents the gaps in the literature and future research agendas.

The review article will help in providing an in-depth understanding of consumer behaviour towards storage, disposal and recycling of e-waste and delineates the future direction of research that may be undertaken in this field of study.

The purpose of this study is to detect the bolt loosening under conditions of impact loading with a low-cost self-powered triboelectric nanogenerator sensor.

In this work, an Al/PTFE-based triboelectric nanogenerator (AP-TENG) is used as a sensor. A pendulum impact device and a force hammer were used to apply the impact loads. The bolt status and the applied torque can be monitored under impact loading conditions by using the output voltage results of the AP-TENGs.

The output voltage results of the current AP-TENG sensor under five different bolt torques, i.e. from 0.5 to 2.5 N m, were measured. The measurements revealed that a thicker buffer layer significantly contributed to the generation of higher voltages. Besides, the AP-TENG was also used to light ten commercial green LEDs in series, and the brightness of the LEDs was high enough even for the daytime, which showed that it can be used as the alarm device. In addition, a sudden loose test was also carried out, and the obvious voltage spikes can be seen without the external impact. The force hammer impact tests have expanded the application scope of the AP-TENG in the bolt loosening detection.

The bolt loosening monitoring is important and useful for the safe operation. The application of TENG technology for detecting bolt loosening remains relatively unexplored. In addition, ten commercial green LEDs can be driven by the AP-TENG sensor, which can be used for the early warning of the bolted loosening status.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0216/

The purpose of this study is to solve the Reynolds equation for finite journal bearings by using the physics-informed neural networks (PINNs) method. As a meshless method, it is unnecessary to use big data to train the neural networks, but to satisfy the Reynolds equation and the corresponding boundary conditions by using the known physics information.

Here, the boundary conditions are enforced through the loss function firstly, i.e. the soft constrain method. After this, an equation was constructed to build a surrogate model for satisfying the corresponding boundary conditions naturally, i.e. the hard constrain method.

For the soft one, in brief, the pressure results agree well with existing results, apart from the ones on the boundaries. While for the hard one, it can be noted that the discrepancies on the boundaries are reduced significantly.

The PINNs method is used to solve the Reynolds equation for finite journal bearings, and the error values on the boundaries for the results of the soft constrain method are improved by using the hard constrain method. Therefore, the hard constraint maybe also a good option when the pressure results on the boundaries are emphasized.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0045/

This paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory in complex strata. This method could be applied to solve the problems caused by linear and nonlinear model uncertainties.

First, an integral-type sliding surface is defined to reduce the static tracking error. Second, a projection type adaptation law is designed to approximate the linear and nonlinear redefined parameters of the electrohydraulic system. Third, a nonlinear robust term with a continuous approximation function is presented for handling load force uncertainty and reducing sliding mode chattering. Moreover, Lyapunov theory is applied to guarantee the stability of the closed-loop system. Finally, the effectiveness of the proposed controller is proved by comparative experiments on a scaled test rig.

The linear and nonlinear model uncertainties lead to large variations in the dynamics of the mechanism and the tracking error. To achieve precise position tracking, an adaptation law was integrated into the sliding mode control which compensated for model uncertainties. Besides, the inherent sliding mode chattering was reduced by a continuous approximation function, while load force uncertainty was solved by a nonlinear robust feedback. Therefore, a novel ASMC for tunnel boring machine cutterhead telescopic system with uncertainties can improve its tracking precision and reduce the sliding mode chattering.

To the best of the authors’ knowledge, the ASMC is proposed for the first time to control the tunnel boring machine cutterhead telescopic system with uncertainties. The presented control is effective not only in control accuracy but also in parameter uncertainty.

The purpose of this paper is to analyze the measurement error of a three-dimensional coordinate measurement system based on dual-position-sensitive detector (PSD) under different background light.

The mind evolutionary algorithm (MEA)-back propagation (BP) neural network is used to predict the three-dimensional coordinates of the points, and the influence of the background light on the measurement accuracy of the three-dimensional coordinates based on PSD is obtained.

The influence of the background light on the measurement accuracy of the system is quantitatively calculated. The background light has a significant influence on the prediction accuracy of the three-dimensional coordinate measurement system. The optical method, electrical method and photoelectric compensation method are proposed to improve the measurement accuracy.

BP neural network based on MEA is applied to the coordinate prediction of the three-dimensional coordinate measurement system based on dual-PSD, and the influence of background light on the measurement accuracy is quantitatively analyzed.

Quality management (QM) practices have long been suggested as a package to improve the quality performance of a company. Yet, empirical studies offered little support of this perspective as only a small set of QM practices were found to be conductive to quality improvement. By taking a new approach, the purpose of this paper is simultaneously evaluate the individual and synergistic effects of several key quality practices on operations performance.

Survey data were collected and used to test the proposed hypotheses. Hierarchical regression analyses were performed to assess the magnitude of synergistic effects and individual effects.

It is found in this study that the synergistic effects across QM practices are substantial in enhancing all operations performance dimensions whereas individual effect varies for different performance goals.

This study makes theoretical contributes to the field of QM by providing empirical support of the interdependence assumption of QM practices and resolving the inconsistent findings. Practically, the results suggest that in-depth implementation of various QM practices simultaneously can be highly effective to achieve performance improvement on all accounts. In addition, the positive additional individual effects also open up a firm’s strategic choices of where to focus the resource investment in the adoption process as long as the strategic focus can justify its contribution toward the desired performance goals.

While the significance of organizational resources and capabilities is widely discussed, little is known about their interrelationships as well as benefits for firms that are involved in coopetitive relationships. Against this backdrop, the purpose of this paper is to investigate the performance effects of entrepreneurial orientation, strategic intent and potential absorptive capacity as well as their complementarity effects on operational and innovation performance for firms involved in horizontal coopetitive relationships.

Drawing upon the resource-based-view, dynamic capabilities and the relational view theories, this study forwards numerous hypotheses between the constructs of interest. The proposed hypotheses are tested utilizing survey data collected from 313 horizontal coopetitive relationships.

The results clearly suggest that entrepreneurial orientation, strategic intent and potential absorptive capacity could positively impact innovation and operational performance outcomes independently. In addition, the authors also find strategic intent and potential absorptive capacity to have differential moderating effects on the relationships between entrepreneurial orientation and the performance outcomes.

The findings suggest that although strategic intent and potential absorptive capacity could lead to performance benefits independently, when it comes to coopetitive relationships, the use of both these capabilities may not substantially increase the positive impact of entrepreneurial orientation on performance outcomes. Specifically, given that these capabilities could intensify competitiveness as well as hostility between partners, they seem to affect the firm's performance differently.

Operational practices and operational capabilities are critical yet distinct elements in operations strategy. The purpose of this paper is to examine their conceptual differences and explore how they are developed in a portfolio, considering the potential for practices and capabilities to be either compensatory or additive in nature.

The compensatory model argues that the lack of investments in certain practices or capabilities can be offset by higher level of investments in other practices or capabilities. In contrast, the additive model argues that the firm must invest in certain practices or capabilities and that trade‐offs are impossible. The authors examine evidence for these two competing models using an approach borrowed from studies of multi‐attribute consumer preference models and statistical comparisons of non‐nested models.

Data for the study were collected from operations managers who were members of a large professional organization. The findings indicate that the effects of operational practices are additive for some operational outcomes and compensatory for others. However, the combinatorial nature of operational capabilities is purely compensatory.

The results imply that adequate investment in a wide range of operational practices is necessary to enhance operations performance. However, operations units appear to have more flexibility in choosing to develop a distinctive operational capability set.

The study clarifies the different orientation of operational practices and operational capabilities as they contribute to operations strategy. The findings provide guidelines regarding the combinatorial natures of operational practices and operational capabilities. These guidelines have critical strategic implications for resource allocation schemes and how these schemes affect operational performance.