Digital Transformation in Production Management
Okabe, a company specializing in metal component manufacturing, has revealed tangible results from using the aIDEM artificial intelligence system to improve production scheduling operations. This announcement came during the ITmedia Virtual EXPO 2026, where the company showcased how AI technologies helped address manufacturing complexities that previously took a long time.
Traditional Scheduling Challenges
The company handles about 5,000 production orders per month, with approximately 1,800 different product types. Previously, the scheduling process relied on complex manual skills, where planners had to balance available resources with delivery deadlines, posing a significant risk in the event of any human error or supply delay. This process required continuous coordination between departments, consuming massive human and time resources.
What Changed Practically?
By integrating the aIDEM system, the company managed to fully automate the scheduling process, leading to:
- Reduced scheduling time: The time required to prepare production schedules dropped from 23 days to just a few minutes.
- Digital connectivity: Converting data that relied on faxes and phone calls into centralized digital data, making it easier to track order statuses and worker locations in real time.
- Operational flexibility: The ability to make immediate adjustments to schedules based on sudden variables, such as raw material delays or changing order priorities.
Why Does This News Matter?
This development represents a practical model for how artificial intelligence is applied in the manufacturing sector (Physical AI), where the role of technology is not limited to automation alone, but extends to "digitizing human expertise." This transformation confirms that the success of digital transformation (DX) in factories does not depend solely on introducing AI tools, but on building an integrated data platform that allows manufacturers to make accurate decisions based on real-time data, reducing reliance on planners' personal estimates and ensuring higher operational efficiency.