# Supply Chain

## <mark style="color:purple;">Navigation:</mark>

{% hint style="info" %}

* Manufacturing & Production
* Warehousing & Logistics
  {% endhint %}

***

## <mark style="color:purple;">生産 & 在庫管理</mark>

### Nvidia NIM

{% embed url="<https://youtu.be/a9O0JipIrb4?si=t_ADR1QJx0yNspl7>" %}

## <mark style="color:purple;">販売と需要予測：</mark>

AIによって強化された予測分析は、過去の販売データ、市場動向、外部要因を活用して、将来の需要を正確に予測します。これにより、企業は在庫管理を最適化し、無駄を削減し、顧客のニーズに応えるために適切な商品を在庫に確保することができます。

## <mark style="color:purple;">物流 & 輸送 & 配送</mark>

UPSは、配達ルートの最適化を継続的に行うORIONを強化

{% embed url="<https://about.ups.com/us/en/newsroom/press-releases/innovation-driven/ups-to-enhance-orion-with-continuous-delivery-route-optimization.html>" %}

{% embed url="<https://about.ups.com/content/dam/upsstories/images/newsroom/press-releases/1440x752_DIADwithNavScreen_A.jpg>" %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aiandbusiness.com/ja/to/supply-chain.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.