Resumen de Sustainable manufacturing in the fourth industrial revolution: A big dataapplication proposal in the textile industry
Gustavo Araque González, Albeiro Suárez Hernández, Mauricio Gómez, Juan Vélez, Alexis Bernal Avellaneda
Purpose: Design an industrial production model with a focus on industry 4.0 (Big Data) anddecision-making analysis for small and medium-sized enterprises (SMEs) in the clothing sector that allowsimproving procedures, jobs and related costs within the study organizationDevelop a sustainable manufacturing proposal for the industrial textile sector with a focus on Big data(entry, transformation, data loading and analysis) in organizational decision making, in search of time andcost optimization and environmental impact mitigation related.
Design/methodology/approach: The present research, of an applied nature, raises a value propositionfocused on the planning, design and structuring of an industrial model focused on Big Data, specifically inthe apparel manufacturing sector for decision-making in a structured and automated way. with themethodological approach to follow: 1) Approach of production strategies oriented in Big Data for thetextile sector; 2) Definition of the production model and configuration of the operational system; 3) Datascience and industrial analysis, 4) Production model approach (Power BI) and 5) model validation.Methodological design of the investigation. 1) Presentation of the case study, where the current situationalanalysis of the company is carried out, formulation of the problem and proposal of solution for the set ofdata analyzed; 2) Presentation of a solution proposal focused on Big Data, on the identification of theindustrial ecosystem and integration with the company’s information systems, as well as the solutionapproach in the study and science of data in real time; 3) Presentation of the Model proposal for SQLstructured databases in the loading, transformation and loading of important information for this study; 4)Information processing, in the edition of data in the M language of Power BI software, construction andelaboration of the model; 5) Presentation of the related databases, in the integration with the foreign keyof the Master table and the transactional Tables; 6) Data analysis and presentation of the Dashboard, inthe design, construction and analysis of the related study variables, as well as the approach of solutionscenarios in the correct organizational decision making Findings: The results obtained show an improvement in operational efficiency from the value-addedproposal Research limitations/implications:Currently, the number of studies applying Big Data technology fororganizations in the textile and manufacturing sector in organizational decision making are limited. Ifanalyzed from the local scene, there are few cases of Big Data implementation in the textile sector, as aconsequence of the lack of projects and financing of value propositions. Another limiting factor in thisresearch is the absence of digital information of high relevance for study and analysis, which leads tolonger times in data entry and placement in information systems in real time. Finally, there is no data-614- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.3922organizational culture, where there are processes and/or procedures for data registration and itstransformation into clean data.
Originality/value: This research integrates, as well as the correct organizational decision makingFor the verification of originality, the project search and systematic review of literature in the main onlinesearch engines are carried out for this research; In addition, the percentages of coincidence with onlinereviewers such as turnitin and plag.es are reviewed in the transparency of this study project.
