Choose the right software layer for the constraint; do not confuse a measurement tool with an operating system.
Evidence-led selection framework
Factory efficiency is not a single product category. OEE exposes losses, MES runs shop-floor work, APS plans against capacity, CMMS protects asset uptime, QMS controls quality, and ERP manages resources and cost. A sound selection starts by defining the loss that must be solved first.
First the problem and baseline KPI, then the system category, and only then the vendor.
These layers are not necessarily substitutes. In a mature plant, several usually operate together through integrations.
Makes machine or line effectiveness visible by measuring availability, performance and quality losses.
Runs work orders, labour, machines, material, quality, downtime and traceability in real time.
Builds a feasible production schedule using finite capacity, due dates, sequence dependencies and alternative resources.
Manages assets, failures, maintenance work orders, spare parts and preventive maintenance.
Manages control plans, measurements, nonconformities, SPC and corrective actions.
Manages orders, purchasing, inventory, bills of material, material planning, costing and finance.
Manages location-based warehousing, barcode/RFID, FIFO/FEFO, receiving, picking and dispatch.
Build the buying shortlist from a verifiable operating problem, not from a feature catalogue.
OEE + MES
Measures the loss tree and connects causes to the work order, machine and operator context.
MES + QMS
Unifies material genealogy, process measurements and nonconformities in one production record.
APS + MES
APS builds a feasible schedule; MES feeds actual production data back into it.
CMMS + machine data
Connects maintenance history, condition signals and production loss to the same asset.
WMS + ERP
Validates physical movement by location and barcode, then reconciles it with order and financial stock.
Validate data, integration and implementation risk before focusing on the demo interface.
See exactly what is captured from machines, operators and manual stations, at what latency, and what happens offline.
Request a real product history from work order to lot/serial, operation and quality measurement.
Verify ERP, PLC, scale, laboratory or warehouse connections through a reference architecture and live example.
Ask the vendor to run your routing, quality, recipe, variant and compliance workflow—not a generic feature list.
Pilot scope, ownership, data cleansing, training, acceptance criteria and rollout timing should be explicit.
Calculate hardware, integration, configuration, support, infrastructure and upgrades alongside licences.
Ask for named users in a similar industry and scale, with baseline and outcome KPIs.
argemas combines MES, OEE, manufacturing ERP/MRP, WMS, quality, traceability and IoT data capture with field experience from 200+ factory deployments.
The outcomes below come from statements by the named managers on Arge Bilişim's customer-review page.
Alders
Reported after three years, with live action on production and quality issues.
Melih Ayan, General Coordinator
Gülce Tekstil
Reported after three years, alongside faster data-based delivery decisions.
Cemal Aysel, General Manager
Görkem Giyim
Reported eight months into the project, with loss visibility and line balancing.
Fatih Yurdadön, Manufacturing Manager
These are customer-reported outcomes, not an independent benchmark. Results vary with baseline, scope, implementation discipline and factory structure.
Map the current data flow, the three largest losses and the integration boundary before the product demo; turn them into a measurable evaluation scope.
