Cement makers are wiring raw mills with online chemistry analyzers and multivariable “autopilots” to keep fineness and oxide ratios on target in minutes, not hours — stabilizing kilns and cutting energy.
In the raw grinding process, every wobble in chemistry or fineness shows up downstream in the kiln and in final cement quality. Plants now use continuous, on-line analyzers tied to automated control systems to watch the raw meal’s composition and Blaine (a measure of particle fineness) and adjust the mill in real time — a shift away from slow lab cycles and operator guesswork.
The targets are nonnegotiable: tight oxide ratios and consistent fineness. The major control indices — Lime Saturation Factor (LSF; a CaO balance index), Silica Ratio (SR), and Alumina Ratio (AR) — steer burnability and clinker formation, while Blaine tracks grind. Variations in raw mix composition directly hurt burnability: a calcium‑rich mix or erratic LSF leads to harder‑to‑calcine feed, higher fuel consumption, and weaker clinker that then demands even finer grinding (cementequipment.org). One analysis notes that fluctuations in raw oxide content force extra energy use (harder‑to‑burn mix) and degraded quality, as clinker must be over‑grinded to meet strength (cementequipment.org). In short, maintaining stable oxide ratios and fineness is essential for consistent thermal performance and cement quality (lyncis.lt).
Raw meal quality targets and challenges
Raw mill output (“raw meal”) must meet narrow chemical and physical specifications for the kiln to run efficiently and for cement to meet strength specs (cementequipment.org). The key metrics — LSF, SR, AR, and Blaine — are monitored continuously so the plant can react to quarry variability, feeder drift, or process upsets. Stable indices mean predictable heat demand and fewer quality corrections; unstable indices do the opposite (cementequipment.org).
On-line analyzers for real-time composition
Modern plants deploy continuous analyzers that measure raw material chemistry in real time, replacing traditional 1–2‑hour lab sample cycles (ResearchGate). Technologies include:
- PGNAA (prompt‑gamma neutron activation analysis), which reads bulk elemental composition on belts every 1–2 minutes (ResearchGate).
- XRF (X‑ray fluorescence), LIBS (laser‑induced breakdown spectroscopy), and NIR (near‑infrared) systems on cross‑belts or air‑slides for continuous CaO, SiO₂, Al₂O₃, and Fe₂O₃ tracking (Global Cement, lyncis.lt).
Vendors report that real‑time analysis lets manufacturers automatically adjust raw material dosing and mixing to keep LSF, SR, and AR within very tight deviations (lyncis.lt). Beyond speed, these analyzers cover the full material stream, not just spot samples (Global Cement).
Analyzer placement and measurement accuracy
Typical installation points include quarry or stockpile reclaim belts, just before the raw mill inlet, and on the airslide after grinding. A LIBS unit may sit ahead of the mill to watch blended feed, while an “air‑slide” NIR analyzer measures pulverized meal exiting the mill (Global Cement). Reported accuracies for oxide measurements are on the order of 0.05–0.3 wt.% for key elements, with data feeding directly into the plant control system (ResearchGate, Global Cement).
Automated blend control and feeder logic
Analyzer data are tied into the plant’s PLC/DCS (programmable logic controller/distributed control system), often through MPC (model‑predictive control) layers. The system adjusts raw mill feeder speeds and mix proportions on the fly. If the analyzer sees high‑CaO limestone, the controller throttles the limestone feeder and enriches clay to rebalance LSF; if alumina is low, the clay feeder opens to maintain AR within narrow bands (Global Cement, cementequipment.org). Plants run this in continuous blending mode or via multivariable loops that coordinate all feeders together.
Closed‑circuit mill control: feed and separator
In a closed‑circuit mill, the two primary manipulated variables are fresh feed rate and separator speed (mydokument.com). When product fineness drifts coarse, the controller may increase separator speed or reduce feed. Because separator speed also affects mill fill and airflow, simple PID (proportional–integral–derivative) loops often struggle with the coupling. Plants therefore implement MIMO MPC (multi‑input multi‑output model‑predictive control) to compute coordinated setpoints for feed and separator speed, balancing production and energy targets (mydokument.com).
One industrial case (FLS ProcessExpert) reported switching from cascaded PIDs to MPC with a cost function, delivering stable operation, lower energy use, and higher throughput; the system also handles changing recipes by auto‑adjusting “target vectors” (mydokument.com).
Practical loop behavior and safeguards
In practice, analyzers measure raw mix chemistry every few minutes, feeding blend‑control logic that compares measured LSF, SR, and AR to setpoints and computes feeder adjustments (via PI control or MPC). Simultaneously, internal mill loops maintain fineness by adjusting feed and separator speed using Blaine analyzers or surrogate measurements such as power draw or airflow. If analyzers detect a sudden composition offset — from a feeder blockage or an ore change — alarms or feed‑rate limits protect the mill. Some systems integrate predictive models so quality corrections are proactive rather than purely reactive (mydokument.com).
Measured outcomes and quantified benefits
Plants report significant gains. SpectraFlow notes that an airslide analyzer with mix‑proportioning software “balances out variation in the local raw materials to increase consistency of the raw meal and kiln feed” (Global Cement). One implementation of advanced control reported up to 6% higher mill throughput, 4% lower specific energy, and a 30% reduction in product variability (mydokument.com).
An industry study found higher‑level automation (on top of normal control) improved energy efficiency by ~2.5–5% (ResearchGate). Even a few percent fuel saving is critical in a raw mill (which is ~30% of plant energy use). In concrete terms, tighter LSF control means the kiln sees minimal swings in CaO and fuel use per tonne of clinker becomes more predictable. Better fineness control avoids over‑grinding or undershooting Blaine; for each 1–2% decline in raw mix fineness, specific energy can increase several percentage points.
Vendors often quantify ROI: maintaining LSF within ±0.5% rather than ±2% can save on the order of 0.5–1% in thermal fuel. One new 5000 t/d line installed both an airslide analyzer and a cross‑belt analyzer at stockpile to lock down feed chemistry (Global Cement).
Knock‑on process stability and workload
Better raw mix control yields indirect benefits: a stable sub‑raw stream supports more consistent kiln operation, fewer production upsets, and reduced downstream sorting or quality adjustments. Advanced controls also reduce operator workload and embed “best practice” settings. The combined result — continuous composition monitoring plus automated feed/separator control — lowers energy use, lifts throughput, and cuts variability in ways that directly impact cost of production (mydokument.com, Global Cement).
Sources: Authoritative industry and research publications, including cement process textbooks, instrumentation notes and recent case studies (Global Cement, lyncis.lt, mydokument.com, ResearchGate, ResearchGate, ResearchGate, cementequipment.org, Global Cement).
