ARES ciMes Partners with DALabx to Optimize Manufacturing Processes and Predict Quality Risks with AI

ARES International Corp. has recently partnered with DALab Solutions x Associates Co., Ltd. (DALabx) to integrate its ciMes Manufacturing Execution System (MES)with DALabx's AI Manufacturing Process Recommendation Module and AI Quality Risk Prediction Module.This collaboration helps manufacturers transform large volumes of manufacturing data into actionable optimization strategies, addressing two critical challenges: production process optimization and quality inspection. By leveraging AI-driven insights, manufacturers can improve production efficiency, ensure consistent product quality, reduce operational costs, and accelerate their transition to AI-powered smart manufacturing.

C.L. Lin, General Manager of ARES International Corp., noted, "Although manufacturers can accumulate vast amounts of production and quality data after implementing an MES system, the real challenge lies in turning that data into valuable insights that support faster and more accurate decisions on the shop floor. Through our collaboration with DALabx, we are combining ciMes's manufacturing operations management capabilities with AI analytics. This enables manufacturers not only to monitor production activities but also to receive actionable process improvement recommendations and identify potential quality risks in advance, gradually transforming data management into intelligent decision-making."

Mao-Yang Yeh, Chairman of DALabx, stated, "The value of AI in manufacturing should go beyond data analysis and anomaly detection. AI must be integrated into actual production workflows to help manufacturers optimize processes and reduce quality risks. Through our collaboration with ARES, ciMes connects AI analytics with manufacturing execution and management processes, making AI-driven insights more relevant to real-world production needs. This helps manufacturers gradually establish data-driven decision-making models, improve production stability, and strengthen their overall competitiveness."

From Collecting More Data to Collecting More Valuable Data

Ying-Jen Chen, General Manager of DALabx, explained, "During digital transformation, manufacturers often invest significant resources in collecting production process data without knowing which data can genuinely contribute to production improvements. Collecting more data does not necessarily lead to better results. The key is to begin with the end in mind: first identify the manufacturing challenges to be addressed, the desired improvement goals, and the expected business benefits. AI analytics can then help identify the key factors affecting process performance and product quality."

AI-driven process optimization provides manufacturers with clear, data-backed criteria for decision-making. By identifying which data should be collected and which key parameters should be retained, businesses can make better use of their data resources and avoid unnecessary data collection and waste.

Integrating ciMes with AI Analytics to Accelerate Smart Manufacturing

ARES ciMes is a self-developed Manufacturing Execution System (MES) that provides comprehensive manufacturing management capabilities, including work-in-process (WIP) management, material management, quality management, equipment management, process control, parameter collection, real-time production monitoring, and production traceability.

Through its collaboration with DALabx, ciMes integrates AI analytics with manufacturing process parameter recommendations and quality risk prediction. This enables manufacturers to move beyond basic data recording and traceability, using data-driven insights to support process optimization and risk management on the shop floor.

Looking ahead, both companies will continue to deepen the integration of MES and AI technologies based on the evolving needs of the manufacturing industry. Together, they aim to help manufacturers improve process management efficiency, strengthen quality risk control, and gradually establish data-driven smart manufacturing operations, unlocking greater value through digital transformation.