Manufacturing Service Innovation and Foreign Trade Upgrade Model Based on Internet of Things and Industry 4.0

Liu, Ling; Zhao, Ping

doi:10.1155/2022/4148713

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…Smart manufacturing is the primary trajectory for global industrial development, wherein the manufacturing sector serves as the main battlefield for innovation-driven transformation and upgrades in the digital economy [10]. Shoe design is stepping into the era of intelligence, necessitating the harnessing of novel technologies in the conception of superior footwear designs [11].…”

Section: Introductionmentioning

confidence: 99%

A Study on Perception of Visual–Tactile and Color–Texture Features of Footwear Leather for Symmetric Shoes

Wang

2023

Symmetry

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The study applies Kansei engineering in analyzing the color and texture of leather footwear, utilizing neural network verification to mirror consumers’ visual and tactile imageries onto varieties of leather. This aids in the development of an advanced system for selecting leather footwear based on such impressions. Initially, representative word pairs denoting consumers’ visual and tactile perceptions of leather footwear were delineated. Post-evaluation of these perceptions through a sensibility assessment questionnaire was administered, using 54 samples of leather footwear provided by manufacturers, with each leather type codified in terms of visual and tactile sensibilities. Subsequently, a customized software algorithm was crafted to isolate the primary color and adhesiveness as color features from the leather sample images. Analyzing grayscale values of the images and using pixel neighborhood as a base, the associated calculation methods, such as LBP, SCOV, VAR, SAC, etc., were proposed to extract texture features from the images. The derived color and texture feature values were used as the input layer and the sensory vocabulary quantified values as the output layer. Backpropagation neural network training was conducted on 49 leather samples, with five leather samples used for testing, culminating in the verification of neural network training for three types and 17 combinations. The outcome was an optimal method for leather footwear Kansei engineering and neural network training, establishing a design process for leather footwear characteristics assisted by sensory vocabulary and a backpropagation neural network. Additionally, a computer-aided system for selecting leather footwear, based on these impressions, was designed and validated through footwear design. This study utilized symmetry in footwear design. By using the design of a single shoe to represent the imagery of a pair of symmetrical shoes, we verified whether the leather samples recommended by the leather imagery selection query system met the expected system input settings.

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Section: Introductionmentioning

confidence: 99%

A Study on Perception of Visual–Tactile and Color–Texture Features of Footwear Leather for Symmetric Shoes

Wang

2023

Symmetry

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Application of Industrial Robot in Injection Molding of Thin-Walled Porous Plastic Parts

Huang¹,

Wang²,

Yang³

et al. 2023

Lecture Notes in Mechanical Engineering

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Does industry 4.0 and environmental quality asymmetrically affect South Africa’s manufacturing sector? A fresh insight from nonlinear autoregressive distributed lag (NARDL) model

Ngepah,

Saba,

Kajewole

2024

Discov Sustain

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Owing to recent developments and implications inspired by fourth industrial revolution (4IR) technologies in the global manufacturing sector through the Industry 4.0 (I4.0) concept, this study was conducted to discover the impacts of I4.0 and environmental quality on the South African manufacturing sector, considering governance quality. To the best of our knowledge, no study has analysed the long-run and short impacts of I4.0, environmental quality and governance quality on the South African manufacturing sector integrating the bound test cointegration, Fully-Modified Ordinary Least Squares (FMOLS) & Dynamic Ordinary Least Squares (DOLS) and nonlinear autoregressive distributed lag (NARDL) estimations techniques. Therefore, this study attempts to bridge this gap using different econometric approaches. The data used spans from 2000Q1 to 2020Q4. The principal component analysis was used to create Industry 4.0 (I4.0) and governance quality components. In this study, utilising the dynamic NARDL, it is seen that the LCO2, representing environmental quality, possesses positive and significant relationship with the LMVA, but when in interaction with the governance quality variables (GOV, INS, POL & ECO), there exists a positive and insignificant relationship with the LMVA showing there exists a dearth of green innovative technologies in the South Africa manufacturing sector respective of its significance. Utilising the FMOLS and DOLS, the GOV, INS, POL & ECO which represents governance quality, mostly possesses negative but significant relationships with the LMVA, even when in interaction with the I4.0 variable proving the I4.0 technologies have not yet started to be impactful to the South African manufacturing industry at large.

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Manufacturing Service Innovation and Foreign Trade Upgrade Model Based on Internet of Things and Industry 4.0

Cited by 3 publications

References 20 publications

A Study on Perception of Visual–Tactile and Color–Texture Features of Footwear Leather for Symmetric Shoes

A Study on Perception of Visual–Tactile and Color–Texture Features of Footwear Leather for Symmetric Shoes

Application of Industrial Robot in Injection Molding of Thin-Walled Porous Plastic Parts

Does industry 4.0 and environmental quality asymmetrically affect South Africa’s manufacturing sector? A fresh insight from nonlinear autoregressive distributed lag (NARDL) model

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