How Do ERP-MOM-MES Layers Connect? Data Flow and Integration

ERP, MOM, and MES are separate layers. But apart from each other, they’re useless.

Over the first three days, we learned: ERP is finance, sales, and procurement; MES records real-time work order data; MOM orchestrates decisions. But what if each worked in isolation?

Monday morning, the sales manager enters a customer Ahmet Bey’s order in ERP. Product A, 100 units, delivery by Monday evening. But what if that order never reaches the shop floor? The production manager still waits for a WhatsApp message and discovers it Tuesday morning. Or worse, someone prints the order and tapes it on the wall. Then the data from MES won’t match what ERP promised the customer. If scrap comes out, MES knows it but ERP told the customer delivery is safe.

Another scenario: the recipe changes. Tomorrow morning Deniz Bey needs to produce with a new recipe. Does he write it down by hand, or does the system automatically show it? If handwritten, misunderstood by another shift supervisor, who’s responsible for scrap?

That’s where data flow comes in.

The Anatomy of Data Flow

In a correct setup, this happens:

Phase 1: Order Coming Down from ERP to MOM

Right after the sales manager enters the order in ERP (say Netsis, Odoo, Logo, or Paraşüt), it automatically flows to MOM. MOM sees the order date, product, recipe, delivery time, and current stock. MOM immediately prepares: “Deniz must produce 100 units of product A by Tuesday 8 AM.”

Phase 2: MOM Shapes the Work Order to MES

MOM sends the recipe and time constraint to MES. But it’s not just “make A.” MOM says:

MES watches this real-time. The operator sees the queue, picks the most urgent job, starts. When the machine runs, MES starts timing.

Phase 3: MES Data Flows Back to MOM

Deniz starts the machine. MES records every minute: How many parts done, machine running or idle. After 1 hour 50 minutes, if the recipe said 2 hours, MES says “on schedule.” If halfway done at 2.5 hours, MES alerts MOM that “delay risk exists.”

If the machine jams and stops for 30 minutes, MES logs it. MOM opens a maintenance ticket. Maintenance fixes it in 45 minutes, and MES records that too.

Phase 4: MOM Sends Real Cost and Progress Back to ERP

When the work order closes, MES sends “100 units, 4 actual hours, 2 scrap” to MOM. MOM evaluates: Standard recipe was 3.5 hours but actual was 4 (why?), scrap rate above expected (repair downtime), quality issue?

MOM then sends this real data to ERP. ERP’s accounting module records “actual cost of this job, standard cost was this, variance is this.”

The 98 units shipped to the customer (100 minus 2 scrap), ERP sales records and the payment plan bases on those 98 units.

Tools: Netsis, Odoo, Logo, Paraşüt

In Turkey, mid-size manufacturers typically wire these integrations like this:

But in most setups, this integration is missing or weak. Why?

  1. Data Model Mismatch: Netsis recipe format differs from MES template. Netsis says “5 pieces, 2 hours once” but MES expects output every 10 minutes. Manual workaround kills time.

  2. Variable Recipe: Customer says “this batch, use different tempering water for A1.” Recipe changes. Time to enter in ERP: 30 minutes. Operator already started with the old recipe.

  3. Machine Flexibility: Product A can run on machine X or Y. ERP has one fixed route, but MES sees real-time machine status and should pick Y dynamically. Coordinating by hand invites errors.

infab.cloud’s Role

infab.cloud fills this gap as a natural integration layer. How?

infab.cloud connects directly to the ERP API (Netsis, Odoo, Logo, Paraşüt) and pulls orders, recipes, stock. At the same time, it collects MES data real-time from shop sensors, operator mobile apps, and machine APIs. At the MOM layer, it orchestrates that data, enabling variable recipes and dynamic route selection.

As a result:

All of this without manual file swaps and WhatsApp coordination. Not perfect integration, but for Turkey’s conditions, it significantly cuts data duplication and time loss.

Next: Variable recipe and real-cost engine. Because data flow alone isn’t enough; we need systems that speed up decisions.


This post is Day 5 in the “Make-to-Order Manufacturing and Factory Software” series.