A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Synthesis and Biological Activity of Organothiophosphoryl Polyoxotungstates

Organothiophosphoryl polyoxotungstates R∋XW∞∞O∋∃/- , R∋ P∋W∞,O∞/-, R∋PW∃O∋ Δ-(X = P, Si, Ge, B or Ga; R = PhP(S), C6H11P(S)) have been prepared from lacunary polyoxoanions and PhP(S). The products were characterized by elemental analysis, IR, and NMR spectroscopy. According to spectroscopic observations, the hybrid anions consist of a lacunary anion framework on which are grafted two equivalent or groups through P-O-W bridges. Some of the title compounds showed the antigerm activity

Reinforcement learning based optimal decision making towards product lifecycle sustainability

Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact.Vinnova [2017-01649]

Effects of Methotrexate on Plasma Cytokines and Cardiac Remodeling and Function in Postmyocarditis Rats

Excessive immune activation and inflammatory mediators may play a critical role in the pathogenesis of chronic heart failure. Methotrexate is a commonly used anti-inflammatory and immunosuppressive drug. In this study, we used a rat model of cardiac myosin-induced experimental autoimmune myocarditis to investigate the effects of low-dose methotrexate (0.1 mg/kg/d for 30 d) on the plasma level of cytokines and cardiac remodeling and function. Our study showed that levels of tumor necrosis factor-(TNF-)alpha and interleukin-6 (IL-6) are significantly increased in postmyocarditis rats, compared with the control rats. Methotrexate treatment reduced the plasma levels of TNF-alpha and IL-6 and increased IL-10 level, compared to saline treatment. In addition, postmyocarditis rats showed significant cardiac fibrosis characterized by increased myocardial collagen volume fraction, perivascular collagen area, and the ratio of collagen type I to type III, compared with the control rats. However, MTX treatment not only markedly attenuated cardiac fibrosis, diminished the left ventricular end-diastolic dimension, but also increased the left ventricular ejection fraction and fractional shortening. Collectively, these results suggest that low-dose methotrexate has ability to regulate inflammatory responses and improves cardiac function and hence contributes to prevent the development of postmyocarditis dilated cardiomyopathy

Transparent Perfect Microwave Absorber Employing Asymmetric Resonance Cavity

The demand for high‐performance absorbers in the microwave frequencies, which can reduce undesirable radiation that interferes with electronic system operation, has attracted increasing interest in recent years. However, most devices implemented so far are opaque, limiting their use in optical applications that require high visible transparency. Here, a scheme is demonstrated for microwave absorbers featuring high transparency in the visible range, near‐unity absorption (≈99.5% absorption at 13.75 GHz with 3.6 GHz effective bandwidth) in the Ku‐band, and hence excellent electromagnetic interference shielding performance (≈26 dB). The device is based on an asymmetric Fabry–Pérot cavity, which incorporates a monolayer graphene and a transparent ultrathin (8 nm) doped silver layer as absorber and reflector, and fused silica as the middle dielectric layer. Guided by derived formulism, this asymmetric cavity is demonstrated with microwaves near‐perfectly and exclusively absorbs in the ultrathin graphene film. The peak absorption frequency of the cavity can be readily tuned by simply changing the thickness of the dielectric spacer. The approach provides a viable solution for a new type of microwave absorber with high visible transmittance, paving the way towards applications in the area of optics.A general strategy is presented to design a new type of microwave absorber based on an asymmetric Fabry–Pérot resonant cavity by employing monolayer graphene, transparent spacer, and ultrathin doped Ag film. This asymmetric cavity is demonstrated with microwaves near‐perfectly and exclusively absorbs in the ultrathin graphene layer at resonances and maintains high visible transmittance.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151816/1/advs1299-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151816/2/advs1299.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151816/3/advs1299_am.pd

The Technology of Mould Steel for Online Pre-hardening

AbstractThis article describes a production method of mould steel pre-hardening, and focus on the advantage of this method, The technical core of method is the variable frequency and variable amplitude pulse uniform high-precision temperature control, which achieved by using strong-medium-weak water cooling, gas-water cooling and gas mist cooling composite cooling control technology. Optimizing the cooling rate path is a good method of optimizing quenched organization and structure