Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0

Chong, Agnes Wen Lin (2023) Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0. Final Year Project, UTAR.

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Abstract

This project is to propose Malaysian industrial companies' excellent application of machine learning assists with Green 4.0. It will provide businessanalytic methodologies, industry 4.0 concept and sustainability 4.0. This will beillustrated through the problem statements of lacking research and technologiesofeffective use in AI for Malaysia manufacturers, the accuracy of resources supplyinsustainability 4.0 and the issue of faults detection in the high speed of changingmachine operating environments. The research aims to investigate the relationshipbetween effective use of adopting business analytics in the manufacturing industry. Thus, the secondary objective is to learn about the model including innovation, enterprise, and Ecological. Framework can facilitate the performanceofManufacturing Firms. The purpose is to interpret the implementation of businessanalytic ultimately affects the overall performance of the organization. and creatingafeasible framework. Model interpreted according to an effective use theoryandbusiness analytic to form theoretical framework in advancing accuracy and reliabilityof manufacturing process using PLS-SEM solutions after collecting data throughdevelop a Google survey form to reduce iterations of complicated data, predict andenhance complexity of performance, and differentiate the day-to-dayhumanbehaviour. In this project, Fornell-Larker parameters are used to test the measurement algorithm for the research's discriminant validity. 380 valid questionnaires returnedback and conducted the calculation of the algorithm's assessment to constructs' validity and realibility assessment, discriminant validity using HTMTand Fornell-Larker approaches. Variance inflation factor analysis and hypothesis testing analysisevaluated for determine variables affecting business analytics adoption for furtherresearch study about suggestions and direction of industrial sector.

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