SEOUL, Korea, Feb. 24, 2021 /PRNewswire/ -- Digital transformation regarding supply chain has become a rather familiar issue for many global manufacturers over the years. Naturally, demand for supply chain solutions is exploding worldwide, with various forms of solutions making their way. One end-to-end solution provider, eMoldino, comes into this fast growing market with a fresh take and a big ambition. People there believe they can redefine supply chain management and digital transformation with their IoT-based solution and upcoming AI system.

They provide manufacturers with a two-part solution: wireless IoT devices and analytic software. The wireless IoT sensors are installed on manufacturers' various tooling, automatically transmitting crucial data of shot count, cycle time, temperature, pressure, and location to the server with encryption. Then, the stored data is processed through the company's original software, providing client managers with tailored reports.

eMoldino's solution stands out with high emphasis on data visibility and easy-to-use analytics software. Data precision and advanced analytics are sourced through the company's software — customized for each client — and allows the manufacturers to improve their strategic sourcing, part quality assurance, asset management, and risk management.

"Ultimately, we aim to provide a comprehensive supply chain solution for global manufacturers, where they can achieve operational excellence through a tightly knit collaborative system with their suppliers.", says eMoldino CEO Mardi Park.

eMoldino's comprehensive solution led world-renowned industry giants to partner up with the company. Samsung Electronics was the very first to see the value in digitizing tooling, and was rewarded with a 50% decrease in mold CAPEX. Dyson followed suit, seeing progress regarding preventing loss of tooling data and reducing part defect. Schaeffler, a tier-1 automotive part supplier, is also undergoing a pilot project.

A quote from Dr. Jason Kim, Head of R&D, sheds light on eMoldino's vision. "The ability to get real-time data of different process parameters for part quality is now possible. By building AI machine learning models with this data, we'll be able to make predictive analysis on part quality and enable accurate risk management."

You can see a more detailed description of their solution and case studies on their website.

Photo - https://mma.prnewswire.com/media/1439720/image1.jpg
Photo - https://mma.prnewswire.com/media/1439719/image2.jpg