TGA Tags:#IndustrialAutomation#AIOptimization#LogisticsEfficiency
Yokogawa Automates Truck Loading Planning with AI
Tokyo-based Musashino City-based Yokogawa Electric Corporation successfully conducted a proof-of-concept (PoC) via its subsidiary Yokogawa Digital Corporation for Hokuetsu Logistics, a Niigata Prefecture-based subsidiary of Hokuetsu Corporation. Using its proprietary loading planning AI, Yokogawa replicated the mental process of veteran artisans, automating an activity traditionally reliant on human know-how.
Challenges in Traditional Loading Planning
Hokuetsu is a paper and pulp products firm whose shipping plans are under numerous constraints. Product shape, vehicle, destination demands, and driver workload must be considered by planners. Conventional optimisation technologies are strained by complex scenarios, making training successors difficult and loading planning laborious. All these factors underscored the need for a wiser, AI-based solution.
How the AI Imitates Artisanal Expertise
Before the AI was developed, Yokogawa experts surveyed veteran artisans in depth to gain insight into how they made decisions and the in-shop environment. This information was used to craft a unique AI capable of mimicking the way human minds think, known as the "Takumi thought process," in order to ensure complex considerations such as item category, vehicle limitations, and delivery route are smartly optimized.
Key Results of the PoC
The AI reduced planning time by leaps and bounds: a single loading plan now takes under 10 seconds, even with difficult constraints. The system effectively clusters delivery destinations to minimize driver fatigue and intelligently orders multiple stops. This demonstrates that human-like "consideration" can indeed be incorporated into AI-based logistics planning successfully.
Scaling up the AI Mechanism
Yokogawa's AI goes beyond optimization as it simulates human intuition and experience. By adding artisan strategies to the algorithm, the system optimizes practicality with efficiency to yield plans that respect operational constraints while also being mindful of human concerns. This is an industrial logistics automation benchmark.
Future Prospects and Impact
With this AI deployment, Yokogawa aims to foster operational effectiveness and facilitate sustainable logistics systems. Companies can tailor the AI to their specific contexts, significantly boosting productivity while reducing human labor in logistics centers. This technology is a step towards intelligent, human-centric automation in factory operations.