Data analytics and application challenges in the childrenswear market - a case study in GreeceData analytics and application challenges in the childrenswear market - a case study in Greece Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2022-05-272020enThis research has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-03464).Integrating technology solutions like PLM, 3D Prototyping, digital printing, automatic cutting, AR & VR into the fashion product development process can deliver continuous improvement in everyday business and empower fashion companies navigate the challenges and opportunities of Industry 4.0. Leveraging powerful artificial intelligence capabilities that guide the discovery of next-generation - in popularity- fashion product designs, can improve innovation and conceptual design exploration to the clothing companies. This study focuses in the market of childrenswear which is the fastest-growing and one of the most lucrative markets in the garment industry; a growth that had overtaken both menswear and womenswear. At the same time, childrenswear product consumers are fashion conscious, demanding more fashionable designer clothing. Predicting the best appealing and selling product maybe the recent demand of applying AI tools in the design generation phase or decision making process, however comfort, fit for play, rest and safety most of all, are requirements that childrenswear must comply with. This paper aims to identify the challenges that AI technology applications face regarding childrenswear, due to safety restriction and standards by taking into consideration a Greek childrenswear manufacturer and retailer.http://creativecommons.org/licenses/by/4.0/647–65817th IFIP International Conference on Product Lifecycle ManagementProduct Lifecycle Management Enabling Smart X Papachristou Evrydiki Παπαχρηστου Ευρυδικη Bilalis Nikolaos Μπιλαλης Νικολαος Springer Nature Childrenswear Data analytics Machine learning Safety standards