AI Solutions for Optimizing Manufacturing

Boost service levels and cut excess inventory across plants and warehouses with Lokad’s end-to-end, multi-echelon supply chain optimization.

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AI Solutions for Optimizing Manufacturing

Manufacturing problems we fix

Line stoppages because a single component is missing.
Excess working capital tied up in slow-moving stock.
Hours lost exploding multi-level BOMs in Excel spreadsheets.
Unreliable supplier lead-times, yields, and price breaks.
Siloed tools for inventory, production, and pricing.

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How we do it

Supply Chain Scientists (SCS)

Each initiative has its own expert (or small team of experts) to partner clients from kickoff to go-live and into the continuous improvement phase. They monitor the automated pipeline, review performance, and adapt the solution as your supply chain evolves (new products, warehouses, or demand patterns).
Probabilistic forecasts

Our SCSs generate full demand and lead-time distributions, replacing single-number guesses and manual safety-stock tables.
Evaluating risk

Millions of future production scenarios are simulated; each decision is scored in dollars/euros to balance stock-out risk versus holding cost.
Differentiable programming

Our SCSs crunch millions of SKUs, BOM levels, MOQs and price breaks in minutes, every night, so that you have the best possible decisions ready each morning.
AI-automation

Optimized purchase and production plans flow straight into your ERP/MRP; planners regain days each week.
Cloud native setup

Working with us does not require new hardware or ERP upheaval. Our Supply Chain Scientists' decisions are piped directly to your pre-existing software on a daily basis.
Rapid deployment

Full go-live in under 6 months (on average).

Project implementation

Multi-echelon manufacturing at Bridgestone

Bridgestone has 8 manufacturing plants and 20 warehouses across Europe, handling 40,000 – 60,000 different SKUs each month.

Lokad replaced dozens of country-level spreadsheets with a single multi-echelon solver that generates daily stock targets and replenishments for every SKU.

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Common questions answered

How fast will we see results?

Most retailers notice meaningful drops in stockouts and inventory within 6–8 weeks of going live.

Can Lokad handle multi-level BOMs and MOQs?

Yes. BOM explosions, resource constraints, MOQs, price breaks and container loads are all encoded into the solver so every recommendation is immediately executable.

Do we need to replace our ERP or APS?

No. Lokad layers on top of your existing stack, exchanging data and orders through flat files, APIs or EDI—no upheaval required.

Will planners still have control?

Absolutely. They can review, lock or override any recommendation while shedding routine spreadsheet work.

How is the solution priced?

A simple monthly subscription aligned to network size—no per-user fees or surprise costs.

The technical details

Probabilistic vs Point Forecasts

Every component, sub-assembly and finished good is forecast as a probability curve rather than a single number. These curves capture erratic, lumpy demand plus variable supplier lead-times, so the optimizer weighs the full risk distribution—measured in dollars—when deciding order sizes or production batch-starts.

BOM & BOR-aware optimization

Lokad natively handles multi-level BOMs, automatically exploding finished-product demand into demand for every component and propagating uncertainty through each level. This aligns component inventory with planned parent production. It also integrates the Bill of Resources—machines, labour, tooling—so schedules respect capacity and skill constraints, avoiding the classic “materials ready but tools missing” dead-end. By embedding both BOM and BOR in one optimization, Lokad keeps production flowing and stock right-sized.

Batching constraints (MOQs, Lot Sizes, Container Loads)

Manufacturing orders face batching limits—MOQs per SKU, per order, fixed production batches, pack multiples and container loads. Lokad models all these simultaneously: it can respect a 50-unit pack size, satisfy both per-item and total-order MOQs, or fill half- and full-containers when that cuts freight cost. The optimizer only rounds up when the financial upside outweighs extra carrying cost, eliminating manual spreadsheet tweaks while ensuring every supplier and shipping constraint is met.

Supplier price breaks

Lokad builds supplier price-break tables straight into its optimiser. It weighs cheaper unit prices at higher quantities against the added carrying cost, buying extra only when the discount justifies it. The engine handles complex tiers and nonlinear cost curves, so orders reflect all cost components, not just stock value. Where volume discounts are steep, this feature alone can trim procurement spend by exploiting economies of scale at exactly the right point.

Differentiable programming for supply chain

All business logic lives in Envision—Lokad’s domain-specific language that compiles to auto-differentiable code. Gradients steer the search, so thousands of SKUs, BOM levels and constraints converge in minutes during each nightly run, with static checks catching unit or join errors before anything hits production. Business logic is written in Envision, Lokad’s domain-specific language that compiles to autodifferentiable code. Gradients steer the optimizer, accelerating convergence on large-scale problems, while static analysis in Envision catches unit mismatches or null joins before anything reaches production.

Cloud-scale compute and secure SaaS

Calculations burst onto hundreds of Azure cores, then spin down to keep costs low. Data stay encrypted end-to-end and the platform inherits ISO 27001 controls, SSO and role-based access. Because Lokad layers on top of your existing ERP/MRP, no new hardware or rip-and-replace project is required.