Odoo to EDGEBIC: The Data Mapping Reference

Mapping Odoo data into EDGEBIC is a column-mapping exercise rather than a development project: you export products, work centers, operations, open manufacturing orders, and optionally work order time logs to Excel or CSV, then drag each source column heading onto the matching EDGEBIC field once and save it as a reusable import mask. Because Odoo's manufacturing module carries all of this natively, every export has a clean source. This reference lists what maps to what, which columns are mandatory, how unit conversion and blank cells behave, and what every row outcome means.

EDGEBIC by User Solutions integrates with Odoo through those masks rather than a certified app, so nothing is installed inside the ERP. If you have not read the end-to-end version, start with the complete Odoo integration guide. This post is the lookup table you keep open while building masks.

The load order

Import in dependency order. Later files reference records that earlier files created.

Two entity types have no Odoo origin and are built from a spreadsheet you write yourself: Shift (one row per shift with a start and end pair per weekday, a blank pair meaning the day is off) and PlantHoliday (closures by name and date). These define the calendar every date is computed against, so they deserve ten careful minutes. Odoo's work center calendars do not carry across as shifts; you set the calendar once in EDGEBIC.

Auto-create is on by default, so an operations file naming a work center that has not been imported yet creates it on the fly. That is a useful safety net and a poor strategy: an auto-created work center has a name and nothing else. Load the work center file properly first.

Products to Product

Only the identifier is required. Everything else can arrive later through a second, narrower refresh file, because blank cells preserve existing values on an update run. Use the internal reference, not the display name, and use it consistently across every export.

Work centers to Workcenter

This is the file where scheduling accuracy is won or lost, because it carries capacity.

Number_Of_Instances is the highest-value column on the page. Odoo describes a work center partly through its capacity and time efficiency rather than an explicit machine count, so this is a column you often set deliberately rather than export straight. A center of four identical machines imported with one instance produces a plan roughly four times too long, and it fails quietly: nothing errors, the dates are simply wrong. The arithmetic is in how EDGEBIC calculates work center capacity.

If your Odoo export expresses capacity as an available-hours figure that already embeds a machine count, do not carry that number into Capacity unchanged while also setting instances, or you will count the same capacity twice. Instances plus the shift calendar is the representation the engine reasons about best.

Machine pools have no export column

Planners think in pools of interchangeable machines, and EDGEBIC models that as a work center group. A routing step bound to a group re-evaluates every member on each reschedule, picks by strategy (earliest completion, primary first, or earliest start), and applies a per-member efficiency factor so a slower machine is chosen only when it still finishes first. Operations already started keep the machine they started on, because recorded work is never moved. Import the members as ordinary work centers, then create the group inside EDGEBIC and add them: see how to create work center groups.

Operations to BOR

Op_Flag is the field people get wrong first. True means "this row is an operation running on a work center". False means "this row is a component consumed at this point in the routing". Odoo bill of materials lines land as component rows with a flag of false, and the operations land as rows with a flag of true.

Why the import takes two passes

An operation chain cannot be written row by row, because step 10 must point at step 20 and step 20 does not exist yet. So the import runs in two passes. Pass one validates each row, resolves or creates the products and work centers it names, and buffers the row. Pass two groups the buffer by end product, sorts by sequence number, writes the steps, and wires the chain: 10 to 20, 20 to 30, and the terminal step to the finished product. Check that visually after the first import: a routing missing its final link draws as a chain floating free of the product it builds.

All of one product's steps must travel in one file, because a run wipes and recreates that product's steps on first reference. And re-importing is safe for running orders, because every scheduled job carries a frozen snapshot of the routing it was planned with.

Subcontracted operations map cleanly as an operation row on a work center that represents the vendor, with the turnaround expressed as transit days, so the outside time stays visible on the Gantt rather than buried inside one long step.

Manufacturing orders to SalesOrder

Two mask options control the date logic when the export carries only one date: one treats the job date as the due date, the other derives the job date backward from the due date. Choose the one matching how your export is built, once, on the mask.

Time logs to Actuals

Job number, work center id, and actual date are mandatory. Hours and pieces are both optional, and either can be derived from the other using the operation's rate. A Complete column marks the operation finished, and an explicit start column overrides the default of using the earliest imported date. The import always overwrites the days a file carries, so re-running a corrected extract fixes the numbers rather than doubling them.

Conversions, blanks, and zeros

Reading the outcomes

Every row resolves to Created, Updated, Reused, or Failed. Reused is the default for a record that already exists, so a weekly product file of 6,000 rows reporting Created 12, Reused 5,988 is the desired result rather than a failure. When counts look wrong, the per-run log file carries one line per row with the exact reason for every failure.

What import cannot bring, and why it matters

The settings that most differentiate a schedule have no column in an Odoo export: the sequence-dependent setup matrix, operator skills and certifications, work center group strategies, bottleneck anchoring, and lot streaming transfer batches. Those are configured once in EDGEBIC and then apply to every imported order afterwards. The EDGEBIC product overview maps the engine, and the ERP integration architecture explains why one mask design serves every ERP.

For the questions that come up before a project starts, see the Odoo integration FAQ. The Fishbowl and Syteline / CloudSuite Industrial references show how little the method changes from one platform to the next, and the ERP scheduling add-on page frames the category.