How a high-volume metal packaging manufacturer runs multi-order, shared-line production on Odoo, from customer requirement and automated pricing through shared-board manufacturing, QC and delivery.
large orders in 5 months
production orders managed
QC inspections logged (estimated)
inventory records processed
The client is a high-volume manufacturer of tinplate and metal packaging components (tins, cans and related containers) for industrial and consumer goods brands.
Its production model is defined by shared tooling. One design board, the sheet layout used for stamping, printing and coating, often carries several customer orders and product codes through the opening stages before the sheet is cut and each piece follows its own finishing route.
The campus is an estimated 500,000+ square feet of manufacturing and warehouse space, built around twin production lines that share machines, tooling and shifts. At 40+ orders a month, the plant runs dozens of interleaved production threads, each needing its own pricing, spec, QC trail and delivery record.
Facility size is a visual estimate from aerial photography, not an engineering measurement.
Orders, product codes, shared boards, semi-finished goods, stages and QC records relate many-to-many, not the one-to-one flow most out-of-the-box manufacturing setups assume.
The goal at every step was inheritance, not re-entry: data created upstream is never typed again downstream.
Sales configures each product at the quote line: type, dimensions, material and gauge, quantity, print and colour, coating, construction, accessories, packaging and special processing. Required-field and compatibility checks catch problems before a quote goes out.
The engine works out material structure, quantities, routing and shrinkage, then calculates material, machine, labor, outside processing, packaging and overhead cost, split into three price layers.
| Price layer | What it represents | Control rule |
|---|---|---|
| Estimated cost | Calculated from standards and data available at quoting | Data source, formula version and date logged |
| Proposed sell price | Estimated cost plus margin and commercial policy | Alert when margin falls below threshold |
| Approved sell price | Final price after discount or exception | Approver, reason and history mandatory |
Every configuration, pricing input, cost basis, margin, price, preparer, approver and version is kept. The configuration the customer confirms is the one that carries into the order and technical documentation.
Specs, expected bill of materials, routing, shrinkage allowances, QC checkpoints, packaging and tooling live under version control. A Draft / Confirmed gate means production, planning and QC only work from signed-off documentation.
Demand is aggregated by product code and delivery date, then matched onto shared boards: board count, repeat layout, expected yield after cutting, and any shortfall or surplus, each plan linked to the orders it serves.
Coating, printing and cutting run as shared work orders. After the cut, each code follows its own routing with formal predecessor-successor links. Start and finish, good and defect quantities, shift, operator and machine are captured, and bottlenecks are flagged.
One board can produce several semi-finished outputs across product codes. Cutting work orders record each output's code, parent order, expected versus actual yield, defects, shrinkage and next step.
Raw material, board, semi-finished goods, finished goods and packaging map to discrete locations (issued, in process by stage, pending QC, rework, pending shipment), each movement linked to its order, board, stage and product code.
Actual consumption is reconciled against standard usage, and shared-stage costs are allocated back to product codes by area, position count, output, weight or standard usage, surfacing abnormal consumption.
Inspectors log pass/fail, defect categories, quantities and photos at the point of inspection, with board-level and product-level defects kept distinct. Defect rate is calculated automatically and flagged against thresholds while the problem is still contained.
Trace any order forward to board, stage, semi-finished good and finished good, or trace a defect backward to every stage, board, product code and order it may have touched.
Material is issued against the production order or board and finished goods are confirmed before shipment. Delivery PDFs generate automatically and customers see only their own records in the self-service portal.
large orders processed, about 40 per month
production orders generated, about 2.2 per order
estimated QC inspections, about 8 checkpoints per production order
inventory in/out documents, at least 100 per month
The QC inspection count is derived from an average checkpoint rate per production order, not a raw system export, and is an estimate pending full data reconciliation.
Average time per cycle across the core quote-to-plan sequence.
reduction in processing time
faster cycle throughput
more QC checkpoints per order, at 20% less total QC time
The real value isn't the 44 hours saved on QC. It is the shift from one end-of-run summary to about 8 inspection touchpoints per order (5 random plus 3 end-of-line, about 3 minutes each), catching defects before they spread across a shared board.
The number of net-new product configurations in the 200 orders isn't confirmed yet, so savings are shown as a range.
| Scenario | Basis | 5-month estimate |
|---|---|---|
| Conservative | Only the steps that repeat on every order | ~280.9 hours |
| Upper bound | All 200 orders needed a new product setup | ~314.2 hours |
estimated hours saved in 5 months
equivalent work-days saved
estimated hours saved per year at the same scale
Time-on-task savings only, from measured before and after steps. Not included: fewer data-entry errors, fewer wrong-version runs, contained defect spread or faster quote turnaround. Not a full ROI calculation, which would also count software, infrastructure and change-management cost.
"The system doesn't just digitize what happens after an order comes in. It puts the company's own configuration and pricing knowledge into the software, so one chain of data runs from the first customer requirement to the delivery record."
Any manufacturer running several SKUs or customer orders across a shared production step (metal packaging, printed tin, coated sheet and similar batch-and-split work) has the same many-to-many problem that single-SKU-per-order MRP setups were never designed for.
It is solvable with Odoo's standard manufacturing, inventory, sales and quality building blocks configured around the plant's real production logic: shared work orders with predecessor-successor links, cutting orders with multiple tracked outputs, and pricing that reflects the real cost structure.
Yes. With shared work orders, board-matching logic and cutting orders that track multiple outputs, one shared run can split into several independently tracked semi-finished and finished goods without losing traceability to the originating orders.
A pricing engine of this complexity is typically a combination of configuration and targeted development on top of Odoo's standard sales and manufacturing modules, keeping the core upgradable while reflecting the real costing logic.
Technical documentation has a Draft / Confirmed gate. Production orders, material issuance and planning can only reference a confirmed version, and changes after approval need a new version or a formal exception approval.
No. Any manufacturer with several in-process inspection points benefits from structured defect logging, photo capture, automatic defect-rate thresholds and traceability by machine, shift and stage.
If your plant shares tooling or runs across multiple orders and SKUs, standard ERP configuration usually falls short.