This month Deep Insights signed a WMS partnership with Jiangsu FAMSUN Intelligent Technology Co., Ltd. It covers the full warehouse process, from FAMSUN's production bases in China to its overseas spare-parts warehouses, and brings AI assistance into daily warehouse management.
FAMSUN is a world-leading provider of agri-food and feed equipment and systems, with business in more than 100 countries and regions. Nine of the world's top ten feed companies are long-term FAMSUN customers.
The warehouse must answer one question: who does this part belong to?
For turnkey equipment, delivery is never the end. A production line runs at the customer's plant for many years. Spare parts, repairs and quality tracing all have to keep up during that time.
That depends on the warehouse being able to answer one question: which project does this part belong to?
FAMSUN's business makes this complex. Engineer-to-order and make-to-order projects run at a different pace from make-to-stock standard models. On the same site, stock ranges from steel and castings to complete machines. In project manufacturing, inventory records must show more than how much is left. They must also show which project and which machine it belongs to.
So the project began with a shared view: seeing inventory is not the same as being able to use it.
Ownership first, then quantity
On top of item, location and status, the system adds business identities such as project number, WBS element and serial number. The same item is kept logically separate under different project numbers. Project stock can be reserved or frozen. Before any issue, the system checks reservations, so stock already allocated cannot be taken by another work order. When every part is matched to its owner, tracing later on has a solid basis.
Connected to manufacturing
On the shop floor, workers pick a work order and operation on a handheld device. The system pulls the standard hours for that operation from the ERP. After confirmation, the hours flow back into cost accounting. Outsourced and in-house processing issue materials according to BOM quotas. Anything above the quota needs approval, and returned surplus material can be traced. Warehouse data becomes part of the manufacturing cost picture.
Accurate records every day
Items with movements on a given day are counted that same day. Blind counts show only the location, not the expected quantity. Differences are reviewed, then approved and posted. Stock is graded by age, and slow-moving and obsolete stock is pushed to the right people automatically.
The data feeds two levels of dashboards. Management sees inventory health, asset turnover and risk signals. Supervisors see receiving and shipping progress, exception closure and productivity.
AI helps here too. It turns knowledge scattered across policies and procedures into answers people can get by simply asking, and it suggests likely causes of stock differences. Approvals and stock adjustments still follow the existing process, and people make the decisions.
One standard, copied to every new warehouse overseas
A four-level structure (group, company, plant, warehouse) forms the base. Multiple languages, currencies and time zones are supported natively, and overseas warehouses join as nodes in the structure. Transfers between organizations are raised and approved in one view. When one site is overstocked while another runs short, the system raises an alert. A new warehouse simply starts work on the same standard.
What it means in practice
When a machine on an overseas site needs a part replaced, the spare-parts warehouse can see which project and order that part belongs to and whether it can be used right now. If a replaced part points to a supplier quality problem, a single serial number traces it back to the supplier, purchase order and receiving batch.
Spare parts serve the second half of a machine's life, and this inventory record has to last as long as the equipment does.
