Softomate Solutions is a London-based software development company building IoT data platforms and analytics systems for UK manufacturers. Our work connects factory-floor machines, sensors, and production systems to cloud-based intelligence layers, turning raw operational data into the real-time visibility and predictive insight that operations directors, production managers, and maintenance engineers need to run efficient, competitive manufacturing businesses.
IoT (Internet of Things) in manufacturing refers to the network of sensors, controllers, cameras, and connected machines that collect real-time operational data from the factory floor and transmit it to software systems for monitoring, analysis, and automated response. A machine fitted with IoT sensors generates a continuous data stream covering variables such as spindle speed, motor current, vibration frequency, temperature, cycle time, and part count. That data, aggregated across dozens or hundreds of machines and transmitted to a cloud platform, gives operations teams a live picture of production that no paper-based or manual system can match.
The technical architecture of a manufacturing IoT system has three layers. The device layer consists of the sensors and edge computing devices attached to or embedded in machines. These may be purpose-built IoT gateways communicating via OPC-UA (the industrial protocol used by most modern CNC and PLC systems), Modbus adapters for older analogue equipment, or condition monitoring devices fitted to motors and bearings. The connectivity layer transmits data from the factory floor to the cloud, using wired Ethernet, industrial Wi-Fi (typically 802.11ac), 4G/5G cellular for remote or outdoor sites, or, for low-bandwidth sensor data, LPWAN protocols such as LoRaWAN.
The platform layer is where the data becomes useful. Cloud platforms such as Microsoft Azure IoT Hub, AWS IoT Core, or purpose-built manufacturing platforms aggregate the data streams, provide the data storage and processing infrastructure, and expose APIs for the analytics and business intelligence applications built on top. Made Smarter's IoT adoption programme has supported hundreds of UK manufacturers in building this architecture, with grant funding reducing the capital cost of implementation.
The UK's ambition under the Advanced Manufacturing Plan is to position Britain as a global leader in high-value manufacturing. IoT connectivity is identified as a foundational enabler: manufacturers that can demonstrate real-time production visibility and data-driven quality management are better positioned to win and retain contracts with demanding OEM customers in aerospace, automotive, and defence. Innovate UK has funded multiple IoT-for-manufacturing projects since 2018, and the pipeline of supported projects continues to grow.
IoT on the UK factory floor solves five categories of operational problem: reactive maintenance causing unplanned downtime, quality defects discovered too late to prevent scrap, energy consumption that cannot be optimised because it is not measured, production reporting that relies on manual data entry at the end of a shift, and capacity planning that cannot account for real machine availability because OEE data is not collected automatically.
Unplanned downtime is the highest-cost problem IoT addresses. A CNC machining centre that stops unexpectedly due to a spindle bearing failure not only loses the revenue from the parts it was producing; it may delay customer deliveries, trigger overtime costs to recover lost production, and, if the machine is a bottleneck, idle downstream processes. Continuous vibration monitoring of spindle bearings, motor drives, and coolant pumps allows maintenance engineers to identify degradation trends weeks before they become failures, scheduling planned interventions during programmed downtime rather than scrambling to recover from unplanned breakdowns. The Make UK Maintenance Matters report estimates that UK manufacturers lose an average of 8.6 per cent of available production time to unplanned downtime, at an average cost of ยฃ4,500 per hour across sectors.
Quality defects detected at final inspection represent wasted material, wasted machine time, and, if the defect has passed through multiple operations before being caught, wasted operator time across the full production sequence. IoT sensors monitoring process parameters (cutting forces, coolant temperature, feed rates) can flag deviations from the specification envelope in real time, alerting the operator and pausing the operation before a defective part progresses further down the production flow. Statistical process control (SPC) software, fed by real-time IoT data rather than manually entered inspection results, can detect trends toward out-of-control conditions before the specification limit is breached.
Energy consumption is a significant cost for UK manufacturers, and energy prices since 2021 have brought this issue to the boardroom. Smart meters and sub-metering at machine level reveal which processes, machines, and shifts consume the most energy, allowing targeted reduction without reducing output. A precision engineering company in the West Midlands supported by Made Smarter installed sub-metering on its 40-machine CNC floor and identified that three machines running idle overnight accounted for 18 per cent of its monthly electricity bill.
UK manufacturers connect legacy machines to IoT networks using protocol adapters, edge computing gateways, and non-invasive sensor retrofits that do not require the machine to be network-enabled natively. The majority of the UK's manufacturing estate consists of machines installed before the IoT era, including CNC machining centres from the 1990s and 2000s, injection moulding presses, hydraulic presses, and legacy conveyor systems that have no native network connectivity. Retrofitting these machines is technically achievable and commercially justified in most cases.
Protocol adapters translate the output signals of older machine controllers into modern IoT formats. Modbus RTU adapters connect to older PLCs and CNC controllers via serial communication, reading register values at defined intervals and formatting them for transmission over Ethernet or cellular to the cloud platform. OPC-UA servers bridge between older OPC DA servers (the predecessor protocol used in Windows XP-era factory automation) and modern OPC-UA clients used by cloud IoT platforms.
Edge computing gateways are industrial computers mounted in the control cabinet or on the machine that aggregate data from multiple machine interfaces, buffer it locally (so that data is not lost if the network connection drops), perform initial processing (calculating OEE from raw counters, detecting threshold breaches locally before transmitting to the cloud), and forward it to the cloud platform. Products from Siemens, Beckhoff, and specialist IoT hardware vendors such as Ewon (Cisco) and Red Lion are commonly used in UK manufacturing IoT projects.
Non-invasive retrofits use sensors that do not require any modification to the machine's wiring or control system. Clamp-on current transformers measure motor current without opening the electrical cabinet. Accelerometers are magnetically mounted on motor and gearbox housings. Infrared thermal cameras monitor electrical panels and process equipment for hot spots indicating failing components. These approaches are particularly appropriate for machines under active OEM warranty or located in potentially flammable environments where electrical work must be minimised.
Our manufacturing software development service includes IoT architecture design, edge gateway configuration, and cloud platform build for UK manufacturers at all stages of connectivity maturity. We also offer API integration services to connect IoT data platforms to ERP, MES, and business intelligence tools.
IoT data connects to business intelligence and ERP systems through APIs and integration middleware that translate real-time machine data into the operational records that planning, finance, and management teams use. The goal is a single operational picture: a production manager looking at a dashboard should see machine availability, current production counts, quality yields, and energy consumption without needing to query three separate systems, and that same data should automatically update the ERP with production completions, machine downtime reasons, and scrap quantities without requiring shop-floor staff to enter it manually.
The ERP integration typically involves two data flows. Works order release pushes the production schedule from the ERP to the MES or IoT platform, informing the shop floor what should be produced on each machine and in what sequence. Production completion feedback pushes good-quantity, scrap-quantity, and downtime data back from the shop floor to the ERP, closing works orders, updating inventory, and feeding job costing without manual entry. This bidirectional flow is the mechanism that eliminates the paper job card and the end-of-shift data entry that currently consumes significant operator and supervisor time in most UK manufacturers.
Business intelligence dashboards built on Power BI, Tableau, or Grafana display the aggregated IoT data in the operational and management views that different user groups need. The production supervisor wants a real-time view of every machine's current state (running, idle, changeover, maintenance, breakdown) and current production count against the schedule. The maintenance engineer wants a trend view of machine health parameters over time, with alerts when parameters cross defined thresholds. The operations director wants daily, weekly, and monthly OEE (Overall Equipment Effectiveness) trends by machine, by cell, and by site, alongside energy and quality metrics. A well-designed IoT platform serves all of these views from the same data foundation without requiring each group to maintain its own data collection process.
Manufacturing IoT systems in the UK are relevant to several ISO standards: ISO 27001 (information security management) for the data security of the IoT platform and the data it holds, ISO 9001 (quality management) for the traceability and quality data collected by IoT sensors and used in quality decisions, and IEC 62443 (industrial automation and control systems security) for the cybersecurity of operational technology networks. For manufacturers supplying the automotive or aerospace sectors, IATF 16949 and AS9100 impose additional requirements for process monitoring data and statistical process control that IoT systems must support.
ISO 27001 applies to the IoT platform's data security architecture: access control, encryption of data in transit and at rest, audit logging, vulnerability management, and incident response. Cloud-hosted IoT platforms from major providers (Azure, AWS) operate within ISO 27001-certified environments, but the manufacturer's own configuration of access controls and data handling practices must also be auditable.
Cybersecurity of OT networks is a growing concern for UK manufacturers following several high-profile cyberattacks on manufacturing businesses. The National Cyber Security Centre (NCSC) has published guidance on OT network security that recommends network segmentation between IT and OT environments, restricting remote access to industrial systems, and ensuring that IoT gateways and sensors receive firmware updates. Building these security controls into the IoT architecture from the start is significantly cheaper than retrofitting them after an incident.
5G connectivity changes manufacturing IoT in the UK by providing the bandwidth, low latency, and device density that industrial wireless networks need but that existing Wi-Fi and 4G infrastructure cannot reliably deliver. The relevance for manufacturers is in three areas: high-bandwidth video applications (AI-powered visual inspection cameras requiring high-resolution video streams), ultra-low latency control applications (collaborative robotics and AGVs that require sub-10ms command response times), and massive machine-type communication (connecting very large numbers of low-power sensors across a large factory without the coverage and interference constraints of conventional Wi-Fi).
Private 5G networks, hosted on spectrum licensed specifically to an industrial operator, are increasingly available in the UK. Manufacturers in sectors including automotive, aerospace, and logistics have deployed private 5G across their sites, with Ofcom's shared access spectrum licensing process providing a regulatory framework for private network deployment. The capital cost of a private 5G network is currently significant (typically ยฃ500,000 to ยฃ2 million for a medium-sized factory), making it an investment decision for larger operators; however, costs are expected to fall significantly over the next three to five years as the technology matures and more vendors enter the market.
For most UK SME manufacturers, the immediate relevance of 5G is as a future-proofing consideration for network architecture rather than an immediate deployment. Designing the IoT data platform and edge gateway infrastructure with 5G connectivity in mind ensures that the platform can be extended to 5G without requiring a full architectural rework when the economics become favourable. Innovate UK has funded 5G-in-manufacturing pilot projects at several UK sites, generating published case studies that provide a realistic view of current capabilities and costs.
OPC-UA (Open Platform Communications Unified Architecture) is the industrial communication standard used by modern manufacturing equipment, PLCs, CNC controllers, and SCADA systems to expose machine data to external applications in a secure, interoperable format. It matters for UK manufacturing IoT because it is the protocol that allows a cloud IoT platform or an edge gateway to read data from a Siemens CNC, a Fanuc robot, a Beckhoff PLC, or a Mitsubishi servo drive without requiring proprietary software from each individual vendor.
OPC-UA was developed by the OPC Foundation and is now embedded in virtually every new piece of industrial equipment manufactured in Europe and North America. It supports a structured data model (meaning that the machine exposes not just raw values but also the semantic meaning of those values, so that a platform receiving data knows it is reading spindle speed in RPM rather than a generic integer), built-in security (encryption and certificate-based authentication at the communication level), and publish-subscribe communication patterns that reduce network traffic compared with polling-based approaches.
For UK manufacturers with a mixed fleet of machines from different vendors, OPC-UA is the glue that makes multi-vendor IoT connectivity practical. Rather than building individual connectors for each machine brand, an OPC-UA-capable IoT gateway connects to all OPC-UA-enabled machines using the same protocol, reducing integration complexity significantly. Our API and system integration service includes OPC-UA server and client development for manufacturing IoT projects, connecting machine data to cloud platforms and ERP systems.
Yes. Legacy machines can be connected using protocol adapters (Modbus, OPC-UA), edge computing gateways, and non-invasive sensors such as clamp-on current transformers and vibration accelerometers. Most of the UK's existing manufacturing estate can be IoT-enabled without machine replacement, at a fraction of the cost of new equipment.
OEE (Overall Equipment Effectiveness) measures the proportion of planned production time that is truly productive, combining availability, performance, and quality metrics. IoT sensors automatically collect the machine state and production count data needed to calculate OEE continuously and accurately, replacing manual shift-end reporting which is prone to error and delay.
IoT platforms connect to ERP systems via REST APIs or integration middleware, pushing production completion, scrap, and downtime data from the factory floor to the ERP automatically. This closes works orders, updates inventory, and feeds job costing without manual data entry. Works order release from the ERP to the factory floor completes the bidirectional flow.
Made Smarter is a government-backed initiative supporting UK SME manufacturers in adopting digital and IoT technologies. It provides grant funding (typically 50 per cent match) for eligible technology projects including IoT sensor networks, MES implementations, and AI analytics. The programme is currently available in the North West, East Midlands, and several other English regions.
Manufacturing IoT systems must implement network segmentation between IT and OT environments, restrict remote access to industrial systems, and ensure IoT gateways receive regular firmware updates. The NCSC's OT security guidance provides a practical framework. ISO 27001 applies to the IoT platform's data security. IEC 62443 applies to the cybersecurity of the wider industrial control system environment.
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