> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Manufacturing Template

> Four-agent pipeline for order parsing, inventory checking, production scheduling, and quality inspection — ready in three lines.

Turn an unstructured order (email, PDF, API payload) into a quality-checked production schedule with a single function call.

Turn an unstructured order (email, PDF, API payload) into a quality-checked production schedule with a single function call.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.manufacturing_template import manufacturing_workflow

result = manufacturing_workflow(
    "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
)
print(result)
```

The user submits unstructured order text; four agents parse inventory, schedule production, and return a quality report.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    subgraph "Manufacturing Workflow"
        IN["📋 Order Text"] --> PO["🤖 ParseOrder"]
        PO --> CI["🤖 CheckInventory"]
        CI --> OS["🤖 OptimizeSchedule"]
        OS --> DD["🤖 DefectDetect"]
        DD --> OUT["✅ Quality Report"]
    end

    classDef input fill:#6366F1,stroke:#7C90A0,color:#fff
    classDef agent fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef output fill:#10B981,stroke:#7C90A0,color:#fff

    class IN input
    class PO,CI,OS,DD agent
    class OUT output

    classDef agent fill:#8B0000,color:#fff
    classDef tool fill:#189AB4,color:#fff
```

## Quick Start

<Steps>
  <Step title="Run the prebuilt workflow">
    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    from praisonaiagents import Agent, tool
    from examples.cookbooks.Industry_Templates.manufacturing_template import manufacturing_workflow

    result = manufacturing_workflow(
        "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
    )
    print(result)
    ```

    `result` is a dict with keys `order`, `inventory`, `schedule`, and `quality`.
  </Step>

  <Step title="Build a custom agent with IndustryAgentPattern">
    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    from examples.cookbooks.Industry_Templates.manufacturing_template import IndustryAgentPattern

    custom_parser = IndustryAgentPattern.create_data_parser(
        name="XMLOrderParser",
        domain="XML purchase orders",
        sla_seconds=15
    )

    order_data = custom_parser.start("Parse <order><id>999</id><qty>50</qty></order>")
    print(order_data)
    ```
  </Step>
</Steps>

***

## How It Works

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant Operator
    participant ParseOrder
    participant CheckInventory
    participant OptimizeSchedule
    participant DefectDetect
    participant Report

    Operator->>ParseOrder: Raw order text
    ParseOrder-->>Operator: OrderDetails schema
    Operator->>CheckInventory: product_id + quantity
    CheckInventory-->>Operator: InventoryStatus schema
    Operator->>OptimizeSchedule: order + inventory
    OptimizeSchedule-->>Operator: ProductionSchedule schema
    Operator->>DefectDetect: batch_id
    DefectDetect-->>Operator: QualityReport schema
    Operator->>Report: Complete result
```

| Agent              | Responsibility                                    | SLA     |
| ------------------ | ------------------------------------------------- | ------- |
| `ParseOrder`       | Extract structured order info from any format     | ≤ 30 s  |
| `CheckInventory`   | Validate material availability and reorder levels | ≤ 5 s   |
| `OptimizeSchedule` | Generate optimal production schedule              | ≤ 2 min |
| `DefectDetect`     | Automated quality inspection per batch            | ≤ 1 min |

***

## Configuration Options

Pydantic I/O schemas used by this template:

| Schema               | Fields                                                                                                                        |
| -------------------- | ----------------------------------------------------------------------------------------------------------------------------- |
| `OrderDetails`       | `order_id`, `customer_id`, `product_id`, `quantity`, `priority`, `due_date`, `requirements`                                   |
| `InventoryStatus`    | `material_id`, `available_quantity`, `reorder_level`, `supplier_lead_time`, `location`                                        |
| `ProductionSchedule` | `schedule_id`, `production_line`, `start_time`, `end_time`, `assigned_workers`, `estimated_completion`, `bottleneck_analysis` |
| `QualityReport`      | `batch_id`, `inspection_time`, `defect_rate`, `defect_types`, `passed`, `recommendations`                                     |

***

## Common Patterns

**Plug a custom ERP tool into ParseOrder**

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import tool
from examples.cookbooks.Industry_Templates.manufacturing_template import order_parser

@tool
def erp_order_lookup(order_ref: str) -> dict:
    """Fetch order details from ERP system"""
    return {"erp_confirmed": True, "order_ref": order_ref, "priority": "high"}

order_parser.tools.append(erp_order_lookup)
result = order_parser.start("Look up order ORD-2024-555 in ERP")
print(result)
```

**Swap the fallback strategy for inventory**

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.manufacturing_template import (
    manufacturing_workflow, inventory_checker
)

def conservative_inventory(order_text: str) -> dict:
    try:
        return manufacturing_workflow(order_text)
    except Exception:
        return {
            "status": "manual_review_required",
            "reason": "inventory_system_unavailable"
        }

result = conservative_inventory("Rush order: 200 units PART-999")
```

**Scale with IndustryAgentPattern**

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from examples.cookbooks.Industry_Templates.manufacturing_template import IndustryAgentPattern

optimizer = IndustryAgentPattern.create_optimizer(
    name="ShiftOptimizer",
    optimization_target="shift scheduling across 3 production lines",
    sla_minutes=5
)
schedule = optimizer.start("Optimize night shift for lines A, B, C with 80% capacity")
```

***

## Best Practices

<AccordionGroup>
  <Accordion title="Always validate priority before scheduling">
    The `OptimizeSchedule` agent sorts by priority (`urgent > high > normal`). Ensure `ParseOrder` correctly extracts the priority field — incorrect priorities cascade into suboptimal schedules.
  </Accordion>

  <Accordion title="Keep SLA budgets per agent">
    `CheckInventory` must respond within 5 seconds to avoid blocking production scheduling. Any custom inventory tool you attach should query a cache or pre-indexed store rather than a slow ERP endpoint.
  </Accordion>

  <Accordion title="Use fallback_strategies for supply chain disruptions">
    When `CheckInventory` cannot find stock, the built-in fallback returns an alternative-supplier flag. Extend this by attaching a `@tool` that queries a supplier API before escalating to manual review.
  </Accordion>

  <Accordion title="Run quality inspection on every batch, not just failures">
    `DefectDetect` returns a `defect_rate` even when `passed=True`. Log these rates over time to catch drift in machine calibration before it causes real rejections.
  </Accordion>
</AccordionGroup>

***

## Related

<CardGroup cols={2}>
  <Card title="Industry Templates Overview" icon="building-2" href="/docs/features/industry-templates/overview">
    Hub page — choose the right template and understand cross-industry reuse.
  </Card>

  <Card title="Energy Template" icon="bolt" href="/docs/features/industry-templates/energy">
    Wind-farm monitoring, vibration fault detection, and predictive maintenance.
  </Card>
</CardGroup>