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Start with a dependable core set: fresh-feed rate and feeder response, mill power or load, separator speed, product fineness (typically Blaine or residue), circuit pressure or draft, and mill temperatures. Then add airflow or fan data, vibration, reject or recirculation flow, water injection, and material-property measurements that fit the installed circuit and the optimization target.
There is no universal sensor count or package. A closed-circuit ball mill, a vertical roller mill (VRM), and a hybrid roller-press/ball-mill circuit expose different process states and require different control strategies. The right design is the smallest set of trustworthy measurements that describes feed, grinding load, classification, gas-path condition, equipment health, and product quality.
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An optimizer needs measurements of what enters the mill, how hard the mill is working, what the separator sends forward or back, and whether the finished cement meets specification. These signals form a practical starting point for an assessment or advanced process control (APC) project.
| Process question | Core measurement | What it tells you |
|---|---|---|
| How much material is entering? | Fresh-feed rate; feeder setpoint and actual response; feeder ratios | Feed loading, recipe changes, and feeder performance |
| How heavily is the mill loaded? | Motor power or current; mill load indicator; ball-mill sound or elevator power where applicable | Grinding effort, loading changes, and operating constraints |
| How is classification performing? | Separator speed; reject or recirculation flow; product particle-size or fineness data | The relationship between classifier settings, circulating load, and product quality |
| Is the gas path stable? | Differential pressure or draft; inlet and outlet temperature; airflow; fan speed or power; damper position | Ventilation, drying capacity, heat balance, and pressure stability |
| Does the product meet specification? | Blaine, residue, particle-size distribution (PSD), and, where required, SO3 and loss on ignition (LOI) | Quality constraints that prevent an optimizer from trading compliance for throughput |
Every tag should have a defined engineering unit, location, range, timestamp, update rate, and maintenance owner. A value that looks precise but is stale, drifting, incorrectly ranged, or disconnected from the control system can mislead an optimizer more than a missing tag.
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Instrumentation by process function
Feed and material properties
Measure total fresh-feed flow and each feeder’s setpoint and actual response. Ratio information is important when clinker, gypsum, limestone, slag, fly ash, or other constituents change. Where variability is significant, capture feed particle-size distribution, moisture, and chemistry. These properties explain why identical feeder rates can produce different mill loads, temperatures, or fineness.
A feeder command is not proof that material is flowing. Compare the requested rate with the measured response, and flag periods of empty bins, bridging, weigh-belt slip, or calibration work. If a feeder ratio changes, retain the recipe state alongside the process data so later analysis can distinguish a control effect from a materials change.
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Grinding load and power
Motor power or current is a primary load indicator for both major mill families. For a ball mill, mill sound level and elevator power can add information about filling and material transport. For a VRM, differential pressure, bed thickness where instrumented, grinding pressure, and mill power describe the grinding bed and the gas-solid balance.
Interpret these signals against the installed machine and operating state. A power increase can represent higher feed, a changed material, a mechanical problem, or an intentional operating move. The signal becomes useful for optimization only when it is analyzed with feed, separator, pressure, temperature, and quality data rather than treated as a stand-alone target.
Classification, rejects, and recirculation
Separator speed is a principal manipulated variable. Pair it with product fineness or PSD and with reject or recirculation flow. The combination reveals whether a finer product is being achieved through classification, through higher circulating load, or through a change in grinding conditions.
On circuits with a recirculation damper or separate reject path, record damper position and measured flow. A rising reject stream may indicate a deliberate fineness change, excessive feed, inadequate ventilation, worn internals, or an unstable material bed. The cause cannot be inferred from separator speed alone.
Gas path and thermal state
Draft or differential pressure, inlet and outlet temperatures, airflow or velocity, fan speed or power, and damper position describe the circuit’s ventilation and thermal condition. These measurements are especially important where gas carries material through the mill and separator, or where hot gas is used for drying.
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Use pressure and temperature measurements at clearly identified locations. “Mill pressure” is ambiguous unless the tag specifies the tapping points and reference pressure. Likewise, an outlet temperature may describe the mill, the separator, or a downstream duct depending on where the sensor is installed.
Product quality
Quality measurements are feedback, not optional reporting. Blaine and residue are common fineness indicators; PSD can provide a fuller picture of the product. SO3 and LOI may be needed where additive content, gypsum dehydration, or volatile loss affects the specification.
Document the laboratory method, sample point, sample mass, analyst or analyzer, and reporting delay. The same product can show different results when Blaine, sieve residue, or laser PSD methods are changed. An APC model must know which method generated each value and when that result actually represents material leaving the circuit.
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Vibration supports both process monitoring and equipment-condition awareness. On a VRM, hydraulic pressure and relevant bearing or roller-condition measurements can identify changes in the grinding system. FLSmidth’s instrumentation examples also include bearing temperature, shaft speed, roller position, and liner-wear thickness for rollers and table liners.
Record water injection or spray, booster or vent-fan speed, recirculation-damper position, and grinding pressure where fitted. These variables can be actuators, constraints, or state indicators depending on the control design. Their role should be defined explicitly in the control narrative.
Ball mill and VRM require different signal priorities
| Comparison axis | Closed-circuit ball mill | Vertical roller mill |
|---|---|---|
| Useful load indicators | Mill sound level or power and elevator power are identified in FLSmidth’s application material. | Mill differential pressure and power; bed-thickness and grinding-pressure measurements may be included. |
| Classification and flow | Fresh feed, separator speed, and reject feed are named parameters. | Fresh feed, separator speed, recirculation damper, and fan conditions are examples. |
| Quality and process state | Blaine or fineness, SO3, LOI, draft, and temperature are named monitoring variables. | Residue or Blaine, vibration, draft, temperature, and online process-state estimation are named. |
| Control selection | FLSmidth describes adapting sound or power and elevator-power targets while maintaining Blaine or fineness requirements. | FLSmidth states that process measurements, control variables, and setpoints are customized to the process configuration. |
Closed-circuit ball mill
For a ball-mill circuit, prioritize reliable feed measurement, mill power or sound, elevator power, separator speed, reject feed, draft, temperatures, and fineness. FLSmidth’s application description discusses adapting sound or power and elevator-power targets while keeping Blaine or fineness within requirement. That approach treats energy-related signals as adjustable targets constrained by product quality, not as goals that can be maximized independently.
Vertical roller mill
For a VRM, add the measurements that describe the grinding bed and hydraulic system: differential pressure, bed thickness where available, grinding pressure, vibration, fan conditions, and relevant bearing or roller temperatures. Feed moisture and hot-gas conditions can have a stronger immediate effect on stability than in a dry, mechanically different circuit, so material and gas-path tags should be time-aligned with mill load and product data.
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Hybrid roller-press and ball-mill circuits
Hybrid circuits need a boundary definition: identify which measurements belong to the roller press, which belong to the ball mill, and where the combined product is sampled. ABB says its Expert Optimizer is applied to single ball mills with dynamic separators, VRMs with dynamic separators, and hybrid roller-press/ball-mill circuits, with strategies tailored to each configuration.
Separate measurements from control actions
A sensor reports a process condition; a control action changes that condition. Keeping the two categories separate prevents a model from confusing cause and effect.
| Measurements (observations) | Typical control actions (manipulated variables) |
|---|---|
| Feed actual rate, mill power, pressure, temperature, vibration, airflow, reject flow, Blaine, residue, PSD | Feed setpoint, separator speed, fan speed, damper position, water injection, grinding-pressure setpoint |
| Feeder response, elevator power, hydraulic or bearing condition | Recipe ratios, recirculation-damper command, hot-gas or ventilation command where the circuit permits it |
Some tags can occupy both roles. Fan power is an observation of gas-path demand and may also be the controlled variable’s feedback. Label each tag according to the control loop in which it is used.
Prepare the data before tuning APC
- Map the process. Draw the material and gas flows from feed bins through the mill, separator, rejects, product collection, and sampling point. Mark every sensor location and the direction of each flow.
- Inventory tags and controls. Record tag names, units, ranges, calibration status, scan rates, historian availability, alarm state, and whether the value is measured, calculated, or manually entered.
- Check signal health. Look for flat lines, impossible values, clipped ranges, implausible step changes, duplicate timestamps, communication gaps, and disagreement between redundant instruments. Correct the instrument or exclude the period; do not silently fill bad data.
- Align cause and response. Compare feed changes, separator and fan settings, pressure, temperature, rejects, power, and quality over a window long enough for the circuit and the laboratory or analyzer to respond. There is no universal interval; residence time, sampling location, and product-delay characteristics determine it.
- Define operating states. Separate startup, shutdown, product change, stable production, maintenance, upset recovery, and manual-control periods. A model trained on mixed states can recommend unsafe or ineffective moves.
- Set constraints with the plant team. Document minimum and maximum feed, fan, separator, pressure, temperature, vibration, hydraulic-pressure, and quality limits using mill-specific engineering procedures. Vendor application pages identify these variables but do not establish universal alarm thresholds.
- Test the control path. Confirm that an approved setpoint change reaches the intended actuator, that feedback returns to the control system, and that operators can return to a stable manual or baseline mode.
Handle laboratory and analyzer delays explicitly
Quality data rarely arrive at the same instant as process tags. A laboratory Blaine or residue result may represent material produced earlier, while an online analyzer may have its own transport and calculation delay. Store the sample timestamp, result timestamp, sample location, method, and product grade. Analyze quality against the process conditions that produced the sample, not merely against the time at which someone entered the result.
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When product changes occur, mark the transition until material from the new recipe reaches the sampling point. Otherwise, the optimizer can attribute a previous product’s quality to the new settings and move the mill in the wrong direction.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use alarms as engineered protection, not generic numbers
Pressure, temperature, vibration, hydraulic pressure, and bearing-temperature limits depend on the mill design, sensor location, operating range, and equipment manufacturer. Establish alarm and trip levels from the plant’s engineering documentation, commissioning data, and maintenance procedures. Do not copy a value from another mill.
For each critical signal, define a response: hold feed, reduce feed, change ventilation, stop water injection, switch to manual control, or initiate a controlled shutdown. Include a bad-signal response so a failed transmitter cannot drive an automatic move.
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What an APC readiness audit should cover
ABB describes beginning its APC journey with a plant process audit that checks instrumentation and control-system suitability, studies process constraints, and considers economics. In practical terms, the audit should answer:
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- Are the core feed, load, classification, gas-path, and quality measurements available and trustworthy?
- Can the control system read them with consistent timestamps and write approved setpoints?
- Which constraints are hard safety or equipment limits, and which are economic preferences?
- What is the optimization objective: higher throughput, lower specific power, tighter fineness, reduced variability, smoother operation, or a defined combination?
- Can operators understand, approve, override, and recover from every automatic action?
The objective determines which additional sensors are worth installing. For example, a project focused on fineness stability may need better quality feedback and separator or reject measurement, while a project focused on VRM stability may first need reliable pressure, vibration, bed, hydraulic, and fan data.
Reported performance and what it does not prove
ABB’s Cemindo Gemilang case study reports a 9–12% increase in production and a 2–8% decrease in specific power consumption in a cement mill. ABB says its process-data fingerprint used logs from November 2021 through February 2022. These are vendor-reported, project-specific results; they are not a guaranteed range for another plant.
ABB’s product page also states that more than 200 cement-mill optimization installations are active. The page does not attach a publication date to that portfolio figure. Neither that claim nor the case study establishes a universal sensor count, accuracy, or sampling frequency.
Site-acceptance checklist
- Mill type, separator arrangement, circuit boundaries, product grades, and optimization objective are documented.
- Fresh-feed rate and feeder actual response are validated under low, normal, and high loads.
- Mill power or load and the mill-specific load indicators are calibrated and historized.
- Separator speed, rejects or recirculation, fan and damper states, draft, airflow, and temperatures have known locations and units.
- Blaine, residue, PSD, SO3, and LOI methods are identified, with sample delays recorded where applicable.
- Vibration, hydraulic, bearing, roller, and wear measurements are assigned to maintenance owners where fitted.
- Water injection, grinding pressure, and other auxiliary actuators are included in the control narrative.
- Bad-quality data, startup, shutdown, product-change, and maintenance periods are clearly marked.
- Alarm limits and automatic responses are approved for this mill rather than borrowed from another installation.
- Operators have a tested manual fallback and a documented procedure for disabling automatic optimization.
Source-specific wording and evidence limits
FLSmidth Cement’s 2024 vertical roller mill brochure states: “the selection of process measurements, control variables, and setpoints is customised to the given process configuration of the mill.” That qualification is central: instrumentation is an engineering design decision, not a shopping list.
ABB and FLSmidth application materials provide useful examples of measurements and control variables, but they do not define a universal installation. Final sensor selection, location, range, accuracy, calibration, hazardous-area suitability, and safety implications must be confirmed by the plant’s instrumentation, process, electrical, and maintenance engineers.
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