## 7 Conclusions and Future Works  
In this study, we developed a \"cloud and collaboration-based MES system\" to support the connection and integration of the value chain of \"order-design-production-delivery\" for the production of sportswear products in the Korean fashion industry and applied the system to manufacturing companies. The following research results were obtained. Figure 21: I/F with MES and enterprise resource planning (ERP). Figure 22: Analysis of process automation through application of MES system. First, the mapping results for the development stage of the management system including ERP and MES were presented, supported by the annual analysis of the industrial revolution stage and the manufacturing company innovation methodology. Through this process, it was identified that cooperation between companies is becoming important in recent years and that the MES system is continually being developed. Second, through the analysis of the concept, the necessity and importance of introduction, and the current development status of MES, which is an important system for implementing smart manufacturing and smart factory in the Industry 4.0 era, nine future MES deployment directions and frameworks were identified. Third, the analysis of the collaboration model between participating companies at each stage of the sportswear production value chain targeted in this study, the characteristics of that collaboration, and the form of collaboration were presented. Fourth, AS-IS analysis was carried out on collaborative companies in the sportswear manufacturing value chain, which is the subject of this study, and through this, the analysis of the requirements of six future MES construction directions was conducted. Through this process, we performed the MES system design process. Through the UML modeling process, the conceptual framework of the cloud-based collaborative MES system was derived. Fifth and finally, we presented a functional framework for collaborative MES development, and based on this, the system was applied to 11 companies included in the target value chain. In particular, examples of system applications that have been actually introduced and operated based on the six MES construction directions were presented. Next, we present the following research content to be conducted in the future. * Development and application of the \"artificial intelligence and data analysis module\" using facility data and environmental sensor data collected in this study, alongside additional collectible manufacturing data, such as power and vibration. * Development of a \"collaborative enterprise recommendation system\" to recommend appropriate enterprises when the number of collaborative enterprises increases to the extent that it is difficult to select fabric, printing, or sewing companies from the perspective of a design company. * Development of a \"product design recommendation system\" that allows design companies to recommend design candidates in consideration of the requirements of customers who want personalized products. * Full integration of MES systems and ERP systems. Consequently, the final operation form of the \"cloud-based collaborative MES\" presented in this paper should be serviced to the manufacturing company in the form of DT (Digital Twin). Currently, there are many difficulties in applying DT technology, which is the core technology of Industry 4.0, to SMEs [72]. In the future, if information related to products, processes, and resources is continuously accumulated through cloud-based collaborative MES, and a bidirectional, standardized, and automated information flow is achieved [72], then the application of DT will be possible. Conceptualization, Y.C. and C.L. ; methodology, Y.C. and C.L. ; software, M.K. ; validation, Y.C. and C.L. ; formal analysis, Y.C. ; investigation, M.K. ; data curation, M.K. ; writing--original draft preparation, Y.C. and M.K. ; writing--review and editing, Y.C. and M.K. ; visualization, Y.C. ; supervision, Y.C. ; project administration, Y.C. ; funding acquisition, Y.C.