Golioth
Firmware updates, device management and data pipelines for embedded products
FourJaw combines MachineLink current sensing with manufacturing analytics to relate machine activity, downtime and estimated energy use.
FourJaw relates machine activity to production performance and energy use. Its technology summary describes a manufacturing analytics platform for uptime, downtime, reasons for stoppages and job progress. The hardware supplies activity information while operators add the context that an electrical signal cannot reveal by itself. This is useful for understanding whether a powered machine is producing, waiting or stopped. The focus is therefore a combination of shop-floor operations and resource use. It does not depend on replacing the machine controller with a new one merely to obtain a first view of machine utilisation.
MachineLink captures signals from the machine and translates them into operational states after calibration. Current sensors provide a non-invasive sensing route, with the precise arrangement depending on the equipment and available signals. The system distinguishes raw activity from meaningful states such as running, idle or stopped. Operator input can then identify reasons including setup, missing materials or maintenance. That distinction matters because identical electrical inactivity can have different production consequences. The resulting information feeds dashboards and reports organised by machine, cell, shift or site rather than leaving the user with a raw current trace alone.
Utilisation, energy monitoring, benchmarking and alerts.6
Adds downtime context, job tracking, quantities and production planning.6
Managed cellular route for factory monitoring installations.6
The energy-monitoring documentation describes an estimate based on measured current and configured electrical assumptions, including voltage and power factor. It reports current-clamp accuracy of approximately ±5.5% over the stated 1–100A range. That makes the feature useful for trends, anomalies and relating energy use to machine activity, while distinguishing it from a precision revenue meter. Three-phase configuration also depends on the documented sensing arrangement. The useful comparison is not simply energy per day: users can identify energy associated with downtime, compare cells or machines and see where operating practice creates avoidable consumption.
The current plans separate a Standard package for utilisation, energy and benchmarking from Pro features that add downtime reasons, job management and wider production context. Pricing is expressed per machine, with a five-machine minimum and volume options. The published offering also includes hardware, support and onboarding arrangements, plus a managed 4G connectivity option. The hardware overview explains the emphasis on retrofitting existing manufacturing equipment. These details make deployment scope part of the comparison: production analytics requires appropriate sensor installation, calibration and operator adoption in addition to the software subscription itself.
FourJaw was formed in 2020 as a spin-out from the University of Sheffield’s Advanced Manufacturing Research Centre, according to its company history. The same page names Chris Iveson as CEO and co-founder and Robin Hartley-Willows as CTO and co-founder. Its origins explain the emphasis on manufacturing productivity and accessible machine data. Current documentation gives a Sheffield contact location and describes customers ranging from smaller manufacturers to larger organisations. The company combines its own monitoring hardware with software and customer support, providing a route for existing equipment to contribute to continuous-improvement work without a major machine-replacement programme. Its official company profile identifies Sheffield, United Kingdom as headquarters.
Firmware updates, device management and data pipelines for embedded products
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This profile does not imply a commercial relationship with FourJaw and may contain inaccuracies.