How it works
In fluidized-bed spray granulation, seed particles (nuclei) are kept fluidized by a gas stream while a liquid suspension is sprayed onto them. The liquid spreads over the particle surfaces and the solvent evaporates, leaving a thin solid shell — so each pass through the spray adds a layer and the particle grows. This layering mechanism makes growth roughly proportional to the available surface area: the more total particle surface in the bed, the thinner each layer.
The two operating modes differ in how the bed is managed. In continuous operation, fresh nuclei enter and grown product is withdrawn, so the bed reaches a steady size distribution set by the balance of spray rate, nuclei feed, and product withdrawal. In batch operation no product is withdrawn, so the whole size distribution shifts upward over time and the total solid mass in the bed increases. In both modes the model follows the whole distribution by a population balance, conserving solid mass.
Not all sprayed material lands on particles — a fraction (overspray) dries in flight and leaves as dust. The practical challenge in both modes is to grow granules to target size and strength without overwetting or defluidizing the bed. In high-shear granulators — a different mechanism — growth is dominated by coalescence under impeller shear; that route is better represented by the agglomerator.
The model
The granulator is a simplified fluidized-bed granulation reactor modelling both continuous and batch operation. It solves a population balance with a size-independent growth rate driven by the sprayed solids over the total particle surface area; an overspray fraction K_os reports to dust, and a granule-moisture parameter sets the liquid leaving with the product. It deliberately does not account for attrition and keeps no secondary distributed property besides size.
- Continuous — Fresh nuclei enter and grown product is withdrawn; the bed reaches a steady size distribution. Validated against the continuous-granulation start-up analysis of Heinrich et al.
- Batch — No product is withdrawn — the total bed mass grows as sprayed solids deposit and the whole PSD shifts upward over time toward the endpoint.
Equipment this model can represent
Any fluidized-bed process that grows particles by layering sprayed suspension.
Continuous FB granulators
Steady spray-on-fluidized-bed layering with continuous product draw.
Batch FB granulators
Spray-on-fluidized-bed layering of a fixed charge.
Spouted-bed granulators
For coarse or sticky granules.
Wurster-type coaters
Bottom-spray layering for uniform shells and pellets.
Typical engineering studies
What teams investigate with the granulator model.
Product PSD prediction
Predict the steady-state product PSD (continuous) or the PSD-versus-time growth curve and endpoint (batch).
Start-up & transients
Study start-up, feed fluctuations, and the approach to steady state dynamically.
Granulation circuits
Couple with screens/mills and recycle to study size control and recycle load.
Dust quantification
Quantify dust (overspray) losses and couple a downstream cyclone/filter.
Sensitivity & scale-up
Run sensitivity/DoE on spray rate, charge, and seed PSD, then calibrate and scale up from pilot to commercial throughput.
Technical FAQ
How do I determine the endpoint of a batch granulation process?
The endpoint is when the granules reach target size (and strength), which for layering corresponds to a spray duration. DyssolPro models the PSD growth over time, so you can read off the spray time that reaches the target size and use that as a model-based endpoint, before refining it experimentally.
Why is my batch granulator producing inconsistent granules?
Inconsistency usually traces to variable seed PSD, spray rate, or wetting between runs. DyssolPro lets you vary those inputs and see how sensitively the product PSD responds, pinpointing which to control tightest for reproducibility.
How does liquid addition rate affect batch granulation?
The spray (liquid) rate sets how fast solids are deposited and how wet the bed gets — too fast risks overwetting. DyssolPro couples the deposited-solids growth to the spray rate, so you can study how it drives the growth trajectory and final size.
How can I avoid overwetting in batch granulation?
Overwetting is avoided by keeping spray rate below the bed’s drying capacity. DyssolPro tracks the solids growth and the liquid leaving via exhaust, so you can study spray rates that keep the bed within a safe wetting balance — the detailed drying capacity is richer in the fluidized-bed spray granulator model.
What causes large lumps in a high-shear granulator?
Lumps come from localized overwetting and uncontrolled coalescence under shear — a high-shear mechanism. DyssolPro’s granulator models layering growth, not high-shear coalescence, so it represents controlled growth; the lump-forming coalescence is better captured with the agglomerator’s kernel approach.
How do impeller and chopper speed affect granule size?
These are high-shear mixer variables that drive coalescence and breakage — not represented in this fluidized-bed layering model. Their net effect on size can be captured through calibrated growth (or via the agglomerator), but the impeller/chopper mechanics themselves are out of scope.
How can I improve reproducibility between batch granulation runs?
Reproducibility comes from controlling the critical inputs (seed, spray, endpoint). DyssolPro identifies which inputs most move the product PSD via sensitivity studies, so you know what to standardize to tighten run-to-run consistency.
What are critical process parameters in batch granulation?
Typically spray rate, total liquid, seed PSD, and endpoint timing. DyssolPro lets you rank these by their effect on the product PSD in a model-based DoE, focusing experimental effort on the truly critical ones.
How do I transfer a batch granulation recipe to larger scale?
Scale-up transfers the fitted growth behavior and matches the spray-to-surface balance at larger charge. DyssolPro lets you calibrate the growth parameters on lab batches and run the model at the larger charge to predict the growth curve and endpoint.
How can I model particle growth in batch granulation?
This is the unit’s purpose: a population balance with surface-area-coupled layering growth and increasing bed mass. In DyssolPro you set the spray and charge and it returns the PSD-versus-time growth trajectory.
How can I identify the optimal granulation endpoint using torque?
Torque-based endpoints belong to high-shear granulation, where torque tracks wet-mass consistency — a mechanical signal this model doesn’t compute. DyssolPro instead gives a size-based endpoint from the PSD growth curve; torque correlation stays an experimental, high-shear technique.
Why does my batch granulation produce too many fines?
Excess fines mean insufficient growth or too much overspray/seed carryover. DyssolPro tracks the PSD growth, so you can study how spray rate and duration shift the fine fraction toward the target.
How does fill level affect batch granulator performance?
Fill (charge mass) sets the total surface area sharing the spray and therefore the per-particle growth rate. DyssolPro couples growth to total surface area, so you can study how charge mass changes the growth rate and time-to-endpoint.
How can I avoid overgranulation in high-shear mixing?
Overgranulation is runaway coalescence from too much liquid or massing time — a high-shear regime. DyssolPro’s layering model represents controlled growth; for the coalescence-driven overgranulation regime the agglomerator’s kernel model is the better tool, while here you study growth time against target size.
What causes poor binder distribution in batch granulation?
Uneven binder comes from spray pattern, droplet size, and bed mixing — partly equipment, partly formulation. DyssolPro doesn’t resolve in-bed spray distribution, but it propagates the net growth effect through the PSD; the distribution itself is a nozzle/mixing matter.
How do I optimize wet massing time?
Wet massing is a high-shear step where the wetted mass is worked before/after liquid addition — not part of the fluidized-bed layering model. DyssolPro addresses layering growth time; wet-massing optimization is specific to high-shear granulation.
How does powder cohesiveness affect batch granulation?
Cohesion affects fluidization and wetting behavior — a material property the model doesn’t simulate mechanically. DyssolPro represents the resulting growth through calibrated parameters; the cohesion effect on fluidization is an equipment/operation matter.
How can I improve granule flowability after batch granulation?
Flowability improves with larger, rounder, less dusty granules. DyssolPro predicts the product PSD (and dust), the main driver of flowability, so you can target a size distribution that flows well — the shape/surface aspects remain experimental.
How do I reduce cleaning time after batch granulation?
Cleaning time is an operational/equipment-design matter (geometry, deposits) outside the process model. DyssolPro doesn’t address cleaning; it models the granulation itself.
How can I model batch granulation using population balances?
This is exactly what the unit does: a population balance advancing the PSD by layering growth with increasing bed mass. In DyssolPro you parameterize the growth and run it to get the PSD trajectory, the basis for endpoint and scale-up studies.
How does continuous granulation differ from batch granulation?
In continuous operation nuclei are fed and product withdrawn so the bed runs at a steady size distribution, whereas a batch grows the whole charge over time. DyssolPro provides both modes of the granulator, so you can simulate the continuous steady state (and its dynamics) or the batch growth curve and compare them directly.
How can I control residence time in a continuous granulator?
Residence time is set by the bed holdup divided by the throughput, which you adjust through nuclei feed and product withdrawal. DyssolPro models the holdup and flows dynamically, so you can study how feed and withdrawal set residence and therefore the product size.
Why does continuous granulation produce variable particle size?
Size variability comes from fluctuations in spray rate, nuclei feed, or recycle, and from the granulation dynamics amplifying them. DyssolPro’s population-balance model lets you impose those disturbances and see how the product PSD responds, helping you find stabilizing operating points.
How do feed rate fluctuations affect continuous granulation quality?
Feed swings shift the surface-area balance and therefore the growth rate and product size. In DyssolPro you apply feed-rate transients and track the PSD response, quantifying how much a given fluctuation moves the product — and how a buffer or control loop would damp it.
How can I control moisture content in continuous granulation?
Granule moisture is set by the balance of sprayed liquid against evaporation and the moisture leaving with product. DyssolPro carries a granule-moisture parameter and the liquid balance, so you can study how spray rate and gas conditions set the product moisture.
What sensors are useful for real-time granulation control?
Real-time control typically uses PSD (spatial filter velocimetry), bed temperature, and humidity sensors. DyssolPro doesn’t select sensors, but it predicts the PSD, moisture, and flows those sensors measure, giving a model basis for control design and soft sensors.
How do I start up and shut down a continuous granulation process?
Startup and shutdown are transient operations where the bed builds up or runs down toward/away from steady state. DyssolPro is dynamic and was validated on continuous-granulation startup, so you can simulate these transients and design the procedure and off-spec handling.
How can I prevent clogging in a continuous granulator?
Clogging (nozzle fouling, sticky deposits) is an operational/mechanical issue tied to overwetting and stickiness. DyssolPro doesn’t model deposits, but it tracks the liquid balance and overspray, so you can study spray rates that avoid the overwet conditions that cause clogging.
How do I compare twin-screw granulation and drum granulation?
These are different growth mechanisms (shear/coalescence vs. tumbling/layering) and equipment. DyssolPro’s granulator models fluidized-bed layering growth; you can represent a different mechanism’s net effect through calibrated growth parameters and compare process behavior, though the unit is not a mechanistic twin-screw model.
How can I model continuous granulation dynamics?
This is the unit’s purpose: a population balance with surface-area-coupled growth, overspray, and continuous feed/withdrawal. In DyssolPro you set those parameters and it returns the dynamic and steady-state PSD inside the flowsheet.
How can I stabilize product quality in continuous granulation?
Stable product comes from steady operating points and control of size via recycle/classification. DyssolPro lets you find stable windows and test control strategies on the dynamic model before applying them to the plant.
What causes residence time distribution broadening in a continuous granulator?
RTD broadening comes from back-mixing in the bed and recycle loops. DyssolPro models the bed holdup and any recycle, so you can study how mixing and recycle widen the RTD and affect product uniformity.
How do screw configuration and speed affect twin-screw granulation?
Those are mechanical variables of a twin-screw machine, which this fluidized-bed model doesn’t represent. Their net effect on growth and PSD can be captured through calibrated growth parameters in DyssolPro, but the screw mechanics themselves are out of scope.
How can I control liquid-to-solid ratio in continuous granulation?
The liquid-to-solid ratio drives both growth and moisture, set by spray and solids feed rates. DyssolPro tracks both the solids growth and the liquid balance, so you can study how the ratio shifts product size and moisture.
How do I handle off-spec material during continuous granulation startup?
Off-spec product during startup is screened and often recycled. DyssolPro simulates the startup transient and any recycle/classification, so you can estimate the off-spec quantity and design how to rework it.
What is the best control strategy for continuous wet granulation?
Effective control targets PSD and moisture against feed and recycle disturbances. DyssolPro lets you test candidate strategies on the dynamic model — how the PSD and moisture respond to control moves — before commissioning.
How can I integrate drying after continuous granulation?
Granules usually need post-drying to final moisture. In DyssolPro you connect the granulator to a fluidized-bed dryer and study how the granule moisture evolves through the combined process.
How do I reduce waste in continuous granulation?
Waste is mainly dust (overspray) and off-spec product. DyssolPro quantifies the overspray-to-dust split and the off-spec fraction, so you can study operating points and recycle that minimize both.
How can I scale continuous granulation from pilot to commercial scale?
Scale-up transfers the fitted growth and overspray parameters to larger throughput and bed. DyssolPro lets you calibrate at pilot scale and run the model at commercial throughput inside the flowsheet to check PSD and dust before building.
How do I simulate recycle loops in continuous granulation?
Recycle of screened fines/oversize is central to granulation circuits. DyssolPro solves the recycle loop dynamically, so you can study how cut sizes and recycle ratios set the product PSD and the circulating load.