Intelligent manufacturing: bridging the gap between the Internet of Things and machinery to achieve optimized operations

Author:

Yuanfang Wei ,Li Song

Abstract

The access gateway layer in the IoT interior design bridging the gap between several destinations. The capabilities include message routing, message identification, and a service. IoT intelligence can help machinery industries optimize their operations with perspectives on factory processes, energy use, and help efficiency. Automation can bring in improved operations, lower destruction, and greater manufacture. IoT barriers are exactly developed for bridging the gap between field devices and focused revenues and industrial applications, maximizing intelligent system performance and receiving and processing real-time operational control data that the network edge. The creation of powerful, flexible, and adjustable Human Machine Interfaces (HMI) can enable associates with information and tailored solutions to increase productivity while remaining safe. An innovative strategy for data-enabled engineering advances based on the Internet of Manufacturing Things (IoMT) is essential for effectively utilizing physical mechanisms. The proposed method HMI-IoMT has been gap analysis to other business processes turns into a reporting process that can be utilized for improvement. Implementing a gap analysis in production or manufacturing can bring the existing level of manpower allocation closer to an ideal level due to balancing and integrating the resources. Societal growth and connection are both aided in the built environment. Manufacturing operations are made much more productive with the help of automation and advanced machinery. Increasing the output of products and services is possible as a result of this efficiency, which allows for the fulfillment of an expanding population's necessities.

Publisher

European Alliance for Innovation n.o.

Reference30 articles.

1. Author AA, Author BB, Author CC, Author DD. Title of article. Abbreviated title of journal. Year of publication; volume number(issue number):page numbers.

2. Author AA. Title of book. Edition [if not first]. Place of publication: Publisher; Year of publication. Pagination.

3. Author AA, Author BB. Title of book. Edition. Place of publication: Publisher; Year of publication. Chapter number, Chapter title; p. [page numbers of chapter].

4. Author AA. Title of paper. In: Editor AA, editor. Title of book. Proceedings of the Title of the Conference; Date of conference; Location of conference. Place of publication: Publisher's name; Year of publication. p. page numbers.

5. Wang, J., Xu, C., Zhang, J., & Zhong, R. (2022). Big data analytics for intelligent manufacturing systems: A review. Journal of Manufacturing Systems, 62, 738-752.

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