Digital Transformation Path for Manufacturing Enterprises Using Internet of Things and Data Encryption Technology

被引:2
|
作者
Lin, Yu [1 ]
机构
[1] China Tobacco Fujian Ind Co Ltd, Xiamen 361002, Fujian, Peoples R China
关键词
Customisation - Data encryption - Digital transformation - Encryption technologies - Industrial manufacturing - Manufacturing business - Manufacturing enterprise - Recommendation methods - Service systems - Transformation paths;
D O I
10.1155/2022/6862999
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Innovation in products or services is crucial for industrial manufacturing businesses in countries that prioritize exports. A plethora of advancements based on the internet of things (IoT) applications has been made possible by the falling prices of processing power, communication, and electrical components. Only a small number of industrial manufacturing enterprisespecific IoT applications have been effective yet. The present literature does not fully explain this scenario, which is very necessary for taking the advantage of IoT in manufacturing enterprises. In order to adapt to the change in digital market demand and enhance the market competitiveness of manufacturing enterprises, this paper aims to study the digital transformation path of manufacturing enterprises based on the internet of things (IoT) and data encryption technology. A digital transformation service system is built for manufacturing enterprises based on the IoT and data encryption technology to help manufacturing enterprises fully understand their own digital degree, provide e'ective suggestions for the digital transformation, and introduce the overall architecture and functional structure of the service system in detail. A distributed intelligent recommendation method is proposed that is based on personalized customization and recommends transformation schemes for businesses in order to better direct users' product customization and decision-making and allow the users to accurately describe their own needs, improve customization efficiency, introduce intelligent recommendation methods, and strengthen the basis of collaborative filtering methods based on items. The simulation result demonstrates that the service system proposed in this study performed really well in terms of both accuracy and time consumption. It is anticipated that the suggested approach will successfully raise the digital maturity of manufacturing companies and will help them in increasing their ability to compete in the current market.
引用
收藏
页数:9
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