• Journal of Information Technology Services
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• v.20 no.3
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• pp.13-25
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• 2021

The article presents the results of how employee's hierarchical job roles differently recognize a SM(smart manufacturing) and evaluate comprehensively on the SM employees training. The research was focus on small and medium size manufacturing corporation in Banwol·Siwha industrial complex, where is carried out Smart Complex National Policy. The Results from 205 participants working for a manufacturing firms in the Banwol·Siwha industrial complex. The results of study show that managers (vs workers) group is higher recognition of smart manufacturing and more intention to participate a SM employee training and utilize a SM equipments for test a manufacturing process. and these variables were mediated by SM cognition. These results will help SM manpower training center strategically design their training programs to maximize the training effectiveness.

• Journal of Distribution Science
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• v.22 no.1
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• pp.37-46
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• 2024

Purpose: This study aims to address the overlooked micro-level aspects within Smart Manufacturing (SM) research, rectifying the misalignment in manufacturing firms' estimation of their technological adoption capabilities. Drawing upon the Social-Technical Systems (STS) theory, this paper utilises innovation capability as a mediating variable, constructing a human-centric organizational model to bridge this research gap. Research design, data and methodology: This study collected data from 233 Chinese manufacturing firms via online questionnaires. Introducing innovation capability as a mediating variable, it investigates the impact of social-technical system dimensions (work design, social subsystems, and technical subsystems) on SM adoption willingness. Smart PLS 4.0 was employed for data analysis, and Structural Equation Modelling (SEM) validated the theoretical model's assumptions. Results: In direct relationships, social subsystems, technical subsystems, and work design positively influence firms' innovation capabilities, which, in turn, positively impact SM adoption. However, innovation capability does not mediate the relationship between technical subsystems and SM adoption. Conclusions: This study focuses on the internal micro-level of organisational employees, constructing a human-centric framework that emphasises the interaction between organisations and technology. The study fills empirical gaps in Smart Manufacturing adoption, providing organisations with a means to examine the integration of employees and the organisational social-technical system.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.287-295
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• 2014

Smart manufacturing (SM) considered as a new trend of modern manufacturing helps to meet objectives associated with the productivity, quality, cost and competiveness. It is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of SM is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee's foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To prove this concept, a cloud machining system is considered as research object in which internet of things and cloud computing are used to integrate, organize and allocate the machining resources. Artificial life tools are used for cooperation among autonomous elements in the cloud machining system.

• Advances in Computational Design
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• v.4 no.1
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• pp.43-52
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• 2019

Variation Analysis (VA) is used to simulate final product variation, taking into consideration part manufacturing and assembly variations. In VA, all the manufacturing and assembly processes are defined at the product design stage. Process Capability Data Bases (PCDB) provide information about measured variation from previous products and processes and allow the designer to apply this to the new product. A new challenge to this traditional approach is posed by the Industry 4.0 (I4.0) revolution, where Smart Manufacturing (SM) is applied. The manufacturing intelligence and adaptability characteristics of SM make present PCDBs obsolete. Current tolerance analysis methods, which are made for discrete assembly products, are also challenged. This paper discusses the differences expected in future factories relevant to VA, and the approaches required to meet this challenge. Current processes are mapped using I4.0 philosophy and gaps are analysed for potential approaches for tolerance analysis tools. Matching points of simulation capability and I4.0 intents are identified as opportunities. Applying conditional variations, incorporating levels of adjustability, and the un-suitability of present Monte Carlo simulation due to changed mass production characteristics, are considered as major challenges. Opportunities including predicting residual stresses in the final product and linking them to product deterioration, calculating non-dimensional performances and extending simulations for process manufactured products, such as drugs, food products etc. are additional winning aspects for next generation VA tools.

• Journal of Platform Technology
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• v.11 no.3
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• pp.76-82
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• 2023

Starting from the 4th industrial revolution, core technologies were applied to industries to build various smart environments. Smart factories in the manufacturing industry produce high-quality products by applying IIoT as a core technology that can collect and control a wide range of data for customized production. However, the network environment of the smart factory converted to open through IIoT was exposed to various security risks. In accordance with security breaches, IIoT has shown degradation in the quality of manufactured products and production processes due to network disturbance, use and maintenance of forged IIoT, and can cause reliability problems in business. Accordingly, in this study, a method for safe connection and utilization of IIoT was studied during the initial establishment of a smart factory. Specifically, a study was conducted to check the IIoT connection situation so that the practicality of the IIoT connected to the smart factory could be confirmed and the harmless environment established.