Factory sensors collect valuable data that rarely reaches decision-makers. Litmus captures this raw data from the floor, and InspireXT feeds it directly into your business systems (like ERP and planning) so you can actually act on it.
Machine data, OEE signals and line performance metrics are connected from PLC to ERP so production decisions run on what is happening now, not what was reported yesterday.
Equipment condition, batch parameters and environmental sensor data are connected to quality and compliance systems so deviations are caught in the run, not discovered in the review.
Production throughput and fulfilment signals from the shopfloor connect to planning and supply chain systems so stock commitments are made against what the line is actually producing.
Temperature, line speed and quality sensor data connect to traceability and compliance systems so a deviation in the run is visible before it becomes a batch failure or a recall.
Manufacturers have invested in automation, ERP and cloud infrastructure. The data produced on the shopfloor every shift from PLCs, sensors and SCADA systems still sits at the edge. It never makes it to the systems where production, quality and supply chain decisions are made.
PLCs log cycle times, temperatures and fault codes continuously. By the time that data is manually extracted, formatted and entered into the ERP, the shift has moved on and the decision it should have informed has already been made on a spreadsheet.
Sensor data shows a temperature drift at 11:20. The quality team sees it at the end-of-shift review. The batch affected ran for four hours after the drift started. Litmus captures it in real time. Without the right architecture, that signal still goes nowhere.
Plant A calculates OEE one way. Plant B uses a different definition of downtime. The consolidation runs through a spreadsheet that someone builds fresh each Monday. No two sites are comparable and no one trusts the numbers that come out of the centre.
The production manager knows what happened. The supply chain team, the finance team and the leadership team find out 24 hours later through a report that averaged away every signal that mattered. The business and the shopfloor are running on different clocks.
Deploying Litmus is the right call. Deploying it without connecting it to ERP, planning and quality systems means the data moves faster to a place where it still isn’t used.
A 5% OEE improvement on a line running at 80% utilisation recovers the equivalent of one full production shift per week. That is not an efficiency gain on a dashboard. It is recovered capacity with no capital investment.
Source: McKinsey Global Institute, Manufacturing Analytics
The sensors are running. The data exists. It just isn’t connected to anything that would trigger an intervention before the line stops. Predictive maintenance requires no new instrumentation in most plants. It requires the data to reach a system that can act on it.
Source: Deloitte, The Smart Factory
Every hour between a shopfloor event and a business decision is an hour of waste, quality risk or missed throughput that compounds across every shift, every site and every quarter. It does not appear on a single line of any report. It is distributed invisibly across every operational metric that underperforms.
A Litmus foundation is built that connects shopfloor data to the ERP, planning, quality and AI systems that need to act on it.
Litmus implementations get connected and go live. The InspireXT operating model makes shopfloor data govern operational and business decisions. Every programme runs on the same four Connected enablers.
Value-chain blueprints from shopfloor through operations, quality, planning and finance. Litmus is configured against how the business actually uses production data, not against a generic industrial IoT template.
Defined phases, deliverables and governance for edge deployment, OT integration and business connectivity. The programme stays on scope, auditable and connected to the operational outcomes it was built to deliver.
AI applied to the Litmus delivery itself: asset discovery, protocol mapping, integration testing and governance configuration. The team spends less time on manual connection work and more on the architecture decisions that determine long-term value.
The operating layer for Litmus programmes. It connects process knowledge, data definitions and integration governance from discovery through deployment, so architectural decisions made during design stay visible when the environment needs to change.
Tell us where your machine data stops before it reaches a decision. The architecture, integrations and governance model are built to make industrial data an operational asset, not a reporting afterthought.
