Common challenges, across every industry
Eight problems we hear from manufacturers in process, discrete and hybrid industries, and how we approach each. These are illustrative scenarios; verified client case studies will be published as clients approve them.
“Unplanned downtime keeps hitting output”
Output is below plan, but nobody can say with confidence how long machines actually ran, why they stopped or which failures keep coming back.
Our approach
Connect existing signals or add simple sensors, classify stoppages with operators, and make losses visible by machine and shift. Maintenance and production then work from the same facts.
Expected benefits
- Run, idle and stop time per machine
- Recurring downtime causes ranked
- OEE where inputs are available
- A fact base for maintenance planning
Taking it further with AI: see Predictive maintenance & asset reliability on our Industrial AI page.
Explore Performance
“Quality problems are found too late”
Defects are discovered at final inspection or by the customer, long after the material, parameters and decisions that caused them.
Our approach
Build quality into execution: in-process checks, quality gates, parameter capture against each product, and holds that stop non-conforming product moving on.
Expected benefits
- Problems caught at the step that causes them
- Parameters linked to each product
- Holds enforced in the workflow
- Less rework and scrap
Taking it further with AI: see AI-powered visual quality inspection on our Industrial AI page.
Explore SMART MES
“We can’t trace a product back”
When a customer raises a complaint, it takes days to reconstruct which material, machines, parameters and inspections were involved, and the answer is often incomplete.
Our approach
Map the process, define routes and identification points, connect machines and inspection systems, and record genealogy from material to dispatch.
Expected benefits
- Batch, lot or serial genealogy
- Faster, targeted containment
- Auditable records for customers
- Evidence for certification
“We don’t know where our material is”
Raw material, WIP and finished goods are tracked by hand. Stock figures are unreliable, items go missing between stations and dispatch waits on paperwork.
Our approach
Identify material at receipt, track WIP through every station, transfer and store, and control release to dispatch, with status shared with ERP.
Expected benefits
- Real-time WIP and stock visibility
- Fewer lost or misallocated items
- Controlled dispatch release
- ERP stock that matches the floor
“Energy costs keep rising”
Energy is one of the largest costs in the plant, but consumption is only seen on the monthly bill, not by line, machine or product.
Our approach
Connect suitable meters and machine states so energy use can be seen alongside production, idle running and losses.
Expected benefits
- Energy use by line and machine
- Idle consumption made visible
- Energy linked to output
- A baseline for improvement
Taking it further with AI: see Energy & process optimisation on our Industrial AI page.
Explore Performance
“Our controls are outdated”
Critical equipment runs on obsolete PLCs and HMIs. Spare parts are scarce, data cannot be extracted and every change is risky.
Our approach
Survey the installed base, plan a staged migration around production windows, modernise controls and standardise connectivity so higher-level systems can follow.
Expected benefits
- Lower risk from obsolete hardware
- Standardised, accessible machine data
- A foundation for Performance and MES
- Minimal disruption to production
“We have data, but not the insight”
ERP shows one figure and the floor another. Management reports are reconciled by hand, and nobody can link plant performance to cost and margin.
Our approach
Integrate MES and ERP with clear ownership, build connected reporting on execution data, and extend to cost, yield and margin analysis as the data matures.
Expected benefits
- One version of production and inventory
- Less manual reconciliation
- Operational losses in financial terms
- A trusted base for decisions
Taking it further with AI: see Demand forecasting & supply chain intelligence on our Industrial AI page.
Explore Enterprise Intelligence
“We’re building a new plant”
A new facility is in design. Equipment will be ordered from several OEMs, and the digital layer has not yet been specified.
Our approach
Define the digital architecture, write interface specifications into OEM purchase orders, design MES alongside the process and plan networks and data flows.
Expected benefits
- Equipment that arrives ready to connect
- MES that can go live with the plant
- Lower integration cost than retrofitting
- Ready for advanced industrial AI
Recognise your plant in one of these?
Whether the priority is equipment performance, controls modernisation, MES, traceability or ERP integration, tell us what is holding your plant back and we will suggest a practical way forward.