Revolutionizing Trust Manufacturing Integrating Real-Time Data and AI Innovations for Enhanced Efficiency

Revolutionizing Trust Manufacturing Integrating Real-Time Data and AI Innovations for Enhanced Efficiency

K. Sudha, C. Balakrishnan, T. P. Anish, T. Nithya, B. Gracelin Sheena, B. Maheswari, R. Siva Subramanian
Copyright: © 2024 |Pages: 24
DOI: 10.4018/979-8-3693-4276-3.ch003
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Abstract

The revolutionary synergy of AI and real-time data in transforming trust manufacturing processes is explored in this research study. The use of AI technology has unparalleled prospects for augmenting productivity in the ever-changing realm of contemporary production. The study looks at a number of significant issues, such as the automation of document processing, the use of AI to optimise shipping and buying, and the development of strong lines of communication between manufacturers and suppliers. With a focus on the future, the report explores how AI and machine learning are changing the trust manufacturing environment and provides insights into possible advancements and obstacles. Besides this, the chapter provides instances demonstrating effective use of AI powered technologies and describes the complex influence of AI on day to day operations. In summary, this study adds to a more complex knowledge of how manufacturing processes may be streamlined and opportunities for innovation and optimisation in the industrial environment can be generated by integrating real-time data with AI.
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1. Introduction

1.1 Background

The combination of artificial intelligence (AI) with real-time data is causing a paradigm change in the industrial sector (Zhang, C & Lu, Y 2021). Static workflows and infrequent evaluations were common features of industrial processes in the past, which allowed for inefficiencies and restricted responsiveness. But the emergence of cutting-edge technology has brought about a new era in which data is instantly used to inform decisions and streamline processes, rather than merely being gathered. The industrial sector is undergoing a significant transition as businesses adopt automation and smart technology. The incorporation of sensors, Internet of Things devices, and more data generating sources has produced a setting in which all production related activities are constantly tracked and evaluated. With this real-time monitoring feature, manufacturers have a never before seen chance to improve accuracy, cut down on downtime, and proactively handle issues.

1.2 Real-Time Data and AI's Significance in Trust Manufacturing

Manufacturing is built on trust, particularly in sectors where accuracy and dependability are essential. AI and real-time data are essential for establishing and preserving this confidence (Arinez, J. F et al 2020). Manufacturers can make sure that every stage of the manufacturing process is optimised for quality and efficiency by using the power of real-time information. This transition is intelligently supported by AI, which provides automated processes, adaptive learning, and predictive analytics. This simplifies processes and gives businesses the ability to make data driven choices that guarantee their goods live up to client expectations and strict requirements. The integration of real-time data and artificial intelligence (AI) is revolutionary in the trust manufacturing industry, where accuracy and high stakes are critical. Enhancing process efficiency is only one benefit; it also gives stakeholders, including suppliers and end users, confidence that the goods they get are of the greatest quality. The future of production is being shaped by this synergy, which makes it more responsive, nimble, and reliable as we dig deeper into the complex interactions between these technologies and trust manufacturing.

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2. Ai And Real-Time Data

2.1 Manufacturing's Use of Real-Time Data

The dynamic beating heart of contemporary manufacturing is real-time data, which offers immediate insights into every aspect of the production process (Cui Y et al 2020). Realtime data is continually created by sensors, IoT devices, and monitoring systems in production, in contrast to older approaches that depended on periodic data gathering. Manufacturers may have a current grasp of their operations because to this immediacy. In the industrial sector, where accuracy and productivity are critical, real-time data is essential for process optimisation. It makes it possible to maximise output, reduce downtime, and respond proactively to changing circumstances. Realtime data from manufacturing lines, for example, might show possible bottlenecks and enable quick modifications to maintain a smooth process. Additionally, it helps with predictive maintenance by seeing problems with the equipment before they result in expensive failures (Kumar et al 2023). Realtime data has applications outside of the work floor. Because it incorporates data throughout the supply chain, producers are able to make well-informed judgements on the state of raw materials, inventory levels, and market needs. This all encompassing strategy guarantees that production procedures are not only effective but also in line with more general corporate goals.

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