Manufacturing Software Development — ERP, MES & IoT
Manufacturing operations generate more data than most businesses can act on. Machine sensor readings, production line throughput, inventory levels, quality inspection results, and maintenance schedules are tracked — often across disconnected systems. Automely builds the software that connects these data sources, automates the manual workflows between them, and makes operational data visible and actionable. Dedicated senior developers, onboarded in 7 days.
Dedicated developers • 7-day onboarding • ERP, MES, IoT & AI • NDA on day oneClients Served
Projects Delivered
Average Onboarding
Clutch / GoodFirms Rating
Why Manufacturing Businesses Need Custom Software
ERP systems like SAP, Oracle, and Dynamics handle the basics. Bills of materials, work orders, inventory, financial reporting. But they don't handle custom logic. They can't adapt to the quality inspection workflow your line needs. They can't build a supplier scoring model around your lead time data. And they won't read directly from your CNC machines and PLCs.
Industry 4.0 is not a single product. It is a set of capabilities built over time. You connect machine data via OPC-UA or MQTT. You build real-time dashboards. You create digital twin models to test changes before making them. And you use AI to shift from reactive maintenance to predictive.
Automely builds the custom software that sits between your machines and your team. It makes operational data visible. It automates manual workflows. And it gives production managers the data they need to make better decisions.
WHAT WE BUILD
Manufacturing Software We Build
Every manufacturing software engagement is scoped to your specific production model, existing systems, and operational data requirements — not a generic Industry 4.0 template.
Manufacturing ERP Development & Integration
Custom ERP modules for manufacturing operations where standard ERP functionality does not match the specific production model. Custom bill of materials management, production scheduling with real-world constraint logic, multi-site inventory visibility, quality management integration, and cost accounting tied to actual production data. Integration with existing SAP, Oracle, or Dynamics deployments.
Build Your ERP Solution →Manufacturing Execution System (MES)
MES software connecting shopfloor operations to production planning: work order release and dispatch, real-time production tracking against schedule, quality inspection data capture at each production stage, operator instruction delivery on shopfloor terminals, machine status monitoring, and OEE (Overall Equipment Effectiveness) calculation.
Build Your MES →IoT & Machine Connectivity
Industrial IoT platforms connecting machine data to operational dashboards: OPC-UA and MQTT protocol integration for CNC machines, PLCs, and SCADA systems, real-time sensor data ingestion pipelines, production KPI dashboards (cycle time, downtime, reject rate, throughput), edge computing for low-latency machine data processing, and predictive maintenance models using vibration, temperature, and current draw data.
Connect Your Machines →AI Inventory & Supply Chain
AI inventory management: demand forecasting using sales velocity, seasonality, and external data signals; automated reorder point calculation adjusted by supplier lead time variability; safety stock optimisation across multi-site inventory; and AI-powered supplier risk scoring. Supply chain visibility platforms tracking purchase order status, inbound shipment ETAs, and supplier on-time delivery performance.
Optimise Your Supply Chain →Digital Twin Development
Digital twin applications for manufacturing: 3D process simulation models that mirror production line behaviour using real machine data, what-if simulation for production scheduling changes and capacity planning, digital models of individual assets for predictive maintenance, and plant layout optimisation tools. Built using Three.js or Unity for visualisation with real-time data feeds from the IoT connectivity layer.
Build Your Digital Twin →Quality Management Software
Custom quality management systems: incoming goods inspection workflows with supplier scorecard integration, in-process quality check capture on shopfloor terminals, non-conformance tracking and root cause analysis workflows, statistical process control (SPC) charting, customer complaint management, and quality reporting for ISO 9001 or IATF 16949 compliance audits.
Build Your QMS →HOW WE WORK
Our Manufacturing Software Development Process
Six stages built around the specific challenges of manufacturing software — from operational discovery through machine integration and AI model deployment.
01
Operational Discovery
We map your manufacturing operations, existing systems (ERP, SCADA, MES), data sources, and the specific workflows that off-the-shelf software cannot handle. The output is a technical architecture document that identifies integration points and data flows. Deliverable: Operational process map, system integration diagram, and phased development roadmap.
02
IoT & Data Architecture
For IoT projects: protocol selection (MQTT or OPC-UA), edge agent design, data ingestion pipeline architecture, and time-series database schema for sensor data. For ERP projects: data model design, integration API specification, and migration planning. Deliverable: Architecture specification approved before any development begins.
03
Core Platform Development
Backend API and database development in parallel with dashboard and interface development. Two-week sprints with working software at the end of each cycle. For IoT projects: edge agent development and initial machine connectivity established in the first sprint. Deliverable: Testable software increments delivered every sprint.
04
Machine Integration & Testing
Integration with physical machines, PLCs, and existing systems — the most unpredictable phase of any manufacturing software project. We build integration with realistic tolerance for the variability of industrial communication protocols. Deliverable: Verified machine connectivity with documented data flow and error handling.
05
AI & Analytics Layer
Machine learning model training using historical production data, model validation against held-out data, and deployment of prediction endpoints into the operational platform. For demand forecasting: backtesting across multiple historical periods. Deliverable: Deployed and validated ML models with accuracy metrics documented.
06
Rollout & Continuous Improvement
Controlled rollout to pilot production line or pilot facility with monitoring in place. Operator training and documentation. Your dedicated developer remains available for model retraining, feature additions, and scaling to additional sites. Deliverable: Live system with monitoring, operator documentation, and a rollout plan for additional sites.
Why Manufacturers Choose Automely Over Generic Software Consultancies
Manufacturing software projects have specific failure modes — integrations that break when the protocol specification does not match reality, IoT platforms that collect data nobody acts on, and ERP customisations that work in demo but not on the shopfloor. Automely's manufacturing developers know these failure modes before the first sprint.
The Problem You Face
What Automely Does Differently
Standard ERP systems handle the standard production model — not the custom scheduling logic, quality workflows, or shopfloor data capture that individual manufacturers actually need
We build custom ERP modules that extend your existing system with the specific workflows your production model requires — without replacing what already works
Machine data lives in the machine — inaccessible to production managers making scheduling decisions from incomplete information
We connect your machines via OPC-UA and MQTT, making real-time production data visible in operational dashboards that production managers actually use
Predictive maintenance is a reactive process — machines fail, production stops, and maintenance is called
We build ML models on vibration, temperature, and current draw data to predict failures before they occur, shifting maintenance from reactive to scheduled
Generic software consultancies quote manufacturing projects without understanding OPC-UA, PLCs, or the integration complexity of industrial communication protocols
Our manufacturing developers have hands-on experience with industrial IoT protocols, ERP integration, and the specific data quality challenges of shopfloor environments
Inventory reorder decisions are made manually using spreadsheets and intuition — leading to both stockouts and excess inventory
AI demand forecasting models predict future demand at the SKU level with seasonality and external signal adjustments, automating replenishment recommendations
Digital twin implementations become expensive 3D visualisation projects with no connection to real production data
We build digital twins on live IoT data feeds — the visualisation is the output, but the real value is the what-if simulation and predictive maintenance capability
Manufacturing Software Results — Real Projects, Measurable Outcomes
Below are examples of manufacturing software projects delivered by Automely. All client details are kept confidential.
SECTORS WE SERVE
Manufacturing Software Across Every Sector
Our manufacturing software developers understand the specific compliance requirements, production models, and integration challenges for each manufacturing sector below.
Automotive & Tier 1 Suppliers
Production scheduling, quality management (IATF 16949), IoT machine connectivity, and ERP integration for automotive manufacturers and component suppliers.
Automotive Manufacturing Software
Consumer Goods
Demand forecasting, multi-site inventory management, configurable product BOM management, and supply chain visibility for consumer goods manufacturers.
Consumer Goods Software
Food & Beverage Manufacturing
Recipe management, batch production tracking, allergen and compliance management, cold chain monitoring, and supplier traceability for food and beverage producers.
Food Manufacturing Software
Pharmaceutical & Life Sciences
21 CFR Part 11-compliant manufacturing execution, batch record management, environmental monitoring, and quality management for pharmaceutical manufacturers.
Pharma Manufacturing Software
Electronics & High-Tech
Component traceability, PCB assembly tracking, test data management, IoT yield monitoring, and supply chain visibility for electronics manufacturers.
Electronics Manufacturing Software
Industrial Equipment & Machinery
Digital twin development, predictive maintenance platforms, service lifecycle management, and IoT connectivity for industrial equipment manufacturers.
Industrial Equipment Software
FREQUENTLY ASKED QUESTIONS
Manufacturing Technology Questions
What is Industry 4.0?
Industry 4.0 is also called the Fourth Industrial Revolution. It describes the current phase of industrial change. Digital technology, data, and automation are now core to how factories run. The term came from the 2011 Hannover Messe. The core enabling technologies are:
- Industrial IoT (IIoT) — sensors and connectivity on machines enabling real-time operational data collection
- Digital twins — virtual replicas of physical production assets that mirror real-world behaviour using live data
- AI and machine learning — predictive maintenance, quality defect detection, demand forecasting, and autonomous production scheduling
- Cloud and edge computing — data processing close to the machine (edge) for low latency, with cloud aggregation for cross-site analytics
- Cyber-physical systems — integration of computational processes with physical production processes, enabling software to directly control and optimise physical operations
- Advanced robotics and cobots — programmable robots that work alongside human operators rather than in isolated cells
What is a digital twin in manufacturing?
A digital twin is a virtual model of a real physical asset. It could be a single machine, a production line, or a full factory. It uses live sensor data to mirror what is happening in the real world. The twin receives feeds from IoT sensors — temperature, vibration, pressure, cycle time, energy use. The model updates in real time.
| Digital Twin Type | What It Models | Primary Use Case |
|---|---|---|
| Asset twin | Individual machine or equipment | Predictive maintenance, performance monitoring |
| Process twin | Production line or workflow | Throughput optimisation, bottleneck analysis |
| System twin | Entire factory or supply chain | Capacity planning, scenario simulation |
What is a Warehouse Management System (WMS)?
A Warehouse Management System (WMS) controls and tracks inventory movement in a warehouse. It covers the full stock lifecycle. Inbound receiving handles purchase order matching, quality inspection, and put-away logic. Storage management tracks bin locations, zones, and batch or serial numbers. Outbound operations cover pick lists, packing, and carrier label printing. Inventory accuracy tools include cycle counting and stock adjustment workflows. The WMS integrates with your ERP to keep inventory valuation and order status in sync. Modern WMS systems go further. Real-time location tracking uses RFID or barcodes. AI-powered slotting puts fast-moving items closest to dispatch. Automation links to conveyor systems and goods-to-person robots.
How does AI inventory management software work?
AI inventory management uses machine learning instead of fixed rules. Traditional systems calculate reorder points with a formula: average demand × lead time + safety stock. AI systems learn from historical demand patterns. They account for seasonality, trends, and external signals like promotions or weather. They adjust when patterns change. In practice: demand forecasting predicts what you need at the SKU level, more accurately than time averages. Safety stock accounts for real lead time variability. And replenishment decisions are generated for buyers to review — not calculated by hand. For multi-site inventory, AI models optimise stock across all locations to cut fulfilment costs.
Build Your Manufacturing Software — Dedicated Senior Developer, Onboarded in 7 Days
Building custom manufacturing software, connecting machine data with IoT, integrating with your ERP, or deploying AI for predictive maintenance and inventory optimisation? Tell us what you are trying to solve and we will match you with a developer who has built for manufacturing operations before.
- Book a free 30-minute technical consultation — focused on your manufacturing operations and existing system landscape
- Receive a scoped proposal with integration architecture recommendation within 48 hours
- We onboard your dedicated manufacturing software developer within 7 business days
No lock-in contracts • NDA on day one • ERP, IoT & AI expertise