Keywords: Fluid energy milling, classification, modeling, particulate systems.

Transcription

1 and modeling of partiulate systems in an industrial sale plant. Proeedings of European Congress of Chemial Engineering (ECCE-6) Copenhagen, September 2007 On the ontrol problem in fluid energy milling and air lassifiation proesses: approahes for eperimentation and modeling of partiulate systems in an industrial sale plant. L. Coutinho, a M. Embiruçu a a Universidade Federal da Bahia Esola Politénia, PPGM - Programa de Pós Graduação em Meatrônia Mestrado. Rua Prof. Aristides Novis, 02 Federação zip ode: Salvador-BA. Phones: / / Fa: Brazil Abstrat The objetive of this paper is to study the ontrol problem in partiulate proesses, speifially the opposed air jet milling followed by partile size lassifiation with a fored vorte air lassifier. An overview of both proesses is given and the ontrol problem is defined, based on inputs, outputs and disturbane variables from a perspetive of eperimenting and modeling these proesses on an industrial sale plant. The multivariable ontrol problem and ausality diagrams are presented and eperiments to model these plants are desribed. The interations eisting between milling and lassifiation operations are onsidered in order to identify a ontrol strategy that enables inreased energy effiieny and maintained or improved produt quality. Diffiulties in performing model identifiation of partiulate proesses without a pilot plant available and without on-line partile size measurement are disussed and results from preliminary eperimentation are presented. Keywords: Fluid energy milling, lassifiation, modeling, partiulate systems. 1. Introdution Partiulate systems and powder materials are used in many different industries suh as pharmaeutial produts, food proessing, powder metallurgy, painting, mineral proessing and hemials in general. Partile size distribution and energy effiieny are important performane outputs for size redution and lassifiation proesses. Partile size is important to provide quality harateristis for partiulate produts. For instane, it affets the most different things as the taste of the hoolate

2 L. Coutinho, M. Embiruçu and the mehanial resistane of erami utting tools. Partile size is signifiant for the quality of laser printing and an also modify the absorption of drugs by the human organism. In addition to the quality aspets, it is important to emphasize that size redution proesses are inherently poor in terms of energy effiieny. Many authors have reported that less than one perent of the total energy input is used in the breakage proess. In fluid energy milling, where the omminution results prinipally from partile to partile ollisions, most of the energy is onsumed in plaing partiles in motion, and only around 0.1% of the total energy is involved in the breakage reation (Gommeren, 1997). It is self evident that energy effiieny is probably the most important problem that the industry has faed in the reent past and industrial engineers will ontinue to fae this problem now and for long time in the future. A onsiderable effort has been invested by many sientists and powder proessing researhers in order to obtain suitable models for this branh of industrial systems. Most of the works desribing these systems are based on population balane models and breakage and seletion funtions (Epstein, 1948; Reid, 1965; Austin, 1971; Dodds, 1996; Dods, 1997; Berthiau, 1999; Gommeren, 1999). More reently, a stohasti model based on Markov hains theory has been applied to study stirred bead mills and lassifiers network (Berthiau & Dods, 1999; Berthiau, 2000). Some of the mentioned approahes are often deemed to be very time-onsuming and testing intensive when defining and adjusting model parameters related to mehanial properties for the proessing partiles. It is not very ommon to find works in openliterature dealing with multiple operating input and outputs variables and very little researh has been onduted based on blak-bo and nonlinear identifiation methods. In this paper, (1) fine grinding and air lassifiation proesses are desribed from a perspetive of eperimentation and modeling in an industrial sale plant. (2) Size redution operation is defined as the ombination of both air jet mill and air lassifiation plants. (3) The multivariable ontrol problem and main ontrol objetives are disussed and (4) a detailed analysis on the input-output relationships is presented onsidering the real-world industrial environment. (5) Diffiulties in performing proess identifiation of dynami partiulate systems without a pilot plant available and without on-line partile size measurement are disussed. (6) Finally, the eperimentation plan and preliminary results are presented. 2. Proess Overview Powder proessing of bulk solids and partiulate materials inlude operations suh as size redution and partile size lassifiation. Size redution, grinding, or omminution is the operation to redue the partile size of solids. In most ases, size redution is based on applying mehanial energy to redue the partiles via ompression, ollisions or frition to produe partile breakage. As an inherent result of the breakage phenomena, different sizes of partiles are generated and it is not possible to define a unique partile size for the output material, but rather a partile size distribution. In the majority of ases of omminution, it is diffiult, or even impossible, to ontrol the shape of the size distribution by manipulating proess variables. Thus, when size distribution is an imperative property for the partiulate, subsequently partile size lassifiation is neessary to separate the oarser partiles

3 and modeling of partiulate systems in an industrial sale plant. from the fine fration to adjust the shape of the size distribution. For the material in study, an eess of fine partiles has negative influene on produt and the lassifiation proess is used to redue the fine fration present in the produt. The following sessions desribe a size redution plant (fluidized opposed jet mill) and posterior air lassifiation proess (fored vorte or rotor air lassifier). 2.1 The fluidized bed opposed jet mill The fluidized bed opposed jet mill is one of the most ommon fluid energy milling systems. The priniple of operation of this mill is based on the onversion of high air pressure from air jet nozzles into kineti energy for the grinding of partiles. The material is aelerated during the epansion of the air and the breakage ours mainly by mutual ollision, frition and impat against internal wall or targets. This type of mill is espeially suited for ultra-fine grinding of heat sensitive materials, with very narrow partile size distribution (Gommeren, 1997). Another important aspet of jet milling is the possibility of grinding without risk of ontamination from other materials, whih is possible beause fragmentation is prinipally aomplished by autogenous omminution or mutual redution of the partiles that are being milled (Wellenkamp, 1999). Due to its high energy onsumption it is reommended for high value added powder materials. The basi design onfiguration of the mill is omposed by a hamber, a group of five onvergent nozzles, and a set of wheel lassifiers, assembled in the top of the hamber. For the milling operation, ompressed, ooled and dry air is supplied from entrifugal air ompressors, with flow rate from 100 to 300 Nm 3 /h, and pressure from 6 to 10 Kgf/m2. An ehaust system is used to balane internal pressure of the grinder hamber and remove partiles from the mill. Eletri motor Solids feeding Air nozzle Ative grinding zone Rotor lassifier Cylone Produt + Air Produt Air nozzle Filter Fines + Air Fines Air to atmosphere Figure The Fluidized Bed Opposed Jet Mill AFG-100. Bulk solids to be milled are stored in a loss-in-weight feeder. A rotary valve and pneumati onveyor are used to transport the material into the grinder. After entering the mill, the partiles are entrained and aelerated by several high veloity air jet nozzles that are foused towards the enter of the hamber, olliding with other partiles, eisting targets and internal walls. At the top of the hamber, a rotor lassifier separates the partiles with speified size that are ready to leave the mill or to return as oarse partiles to the grinding zone. The partile size seletion results from the fore balane between the drag fore, produed by the ehaust system, and

4 L. Coutinho, M. Embiruçu the entrifugal fore, aused by the rotor veloity. The partiles of speified size leave the mill mied on the air stream and pass to the air ylone that separates the partiulate material from the air flow. Jet mill produt is olleted from the bottom of the ylone separator, while the air with residual fines partiles is direted to the bag filters for final separation. Dust olletor Loss-in-weight Feeder Rotary valve Bulk solids Pneumati onveying Jet Mill Air Cylone Jet mill produt Fines Safety Filter Blower After ooler Centrifugal ompressor Inlet filter Atmosphere Fig General arrangement of the grinding plant Energy effiieny of Air Jet Milling For the purpose of this work, energy effiieny of air jet milling an be epressed as the speifi energy applied to produe a given amount of speified ground produt. Jet milling effiieny is affeted by many variables related to proess parameters, equipment design and material properties. Some of these variables, if not orretly manipulated, may lead to undesirable ollateral effets that an inrease power onsumption or introdue risks of produt quality losses. The objetive of proposed ausality diagram showed in Figure is to desribe the omple ause-effet relationship whih eists between jet milling energy effiieny and input variables related to proess, design and material properties. This diagram takes into aount the output of the jet mill plant as the total amount of the oarse produt that is olleted on the bottom of the air ylone as ground produt. The fines that are olleted in the bag filter onsist of out of speifiation material and an not be yielded as aepted produt.

5 and modeling of partiulate systems in an industrial sale plant. Inrease required power Improve jet mill energy effiieny Risk of quality losses Inrease produt throughput rate Create proess instability Improve ylone effiieny Inrease size redution rate Redue fines generation Augment air flow veloity Inrease partiulate friability Redue residene time Redue overgrinding Inrease blower apaity Intensify partiulate kineti energy Inrease probability of ollision Keep internal pressure Improve flow pattern inside the mill Augment irulating load Inrease grinding air pressure Modify ylone design Redue grinding temperature Modify previous proessing Modify hemial omposition Improve nozzle design Improve mill hamber design Inrease feed rate Redue rotor lassifier speed Fig Multivariable ausality diagram for jet mill energy effiieny. ( No opposition between ation and main objetive; --- potential ations onstrained by potential undesirable effets; manipulated input proess variable) In fat partiular, the effiieny of the breakage proess is affeted by two main drivers: the energy of partile to partile ollisions and the probability of partile ollision. Aordingly, higher grinding rates an be ahieved by inreasing ollision energy and augmenting the quantity of partiles entrained in the air jet streams. The ollision energy is related to the veloity of the partiles when the ollision ours. One inside the mill hamber, the partiles are entrained in the boundaries of the air jets and targeted by the nozzles to onverge at the enter of the mill, whih is onsidered the ative grinding zone. The majority of the ollisions and the more energeti ones our at the ative mill zone. The initial partile veloity is proportional to the veloity of the air jet, whih for a given nozzle geometry is inreased with grinding air pressure. However, high pressure demands high power onsumption and the problem is ultimately one of determining an operation point that delivers optimum energy effiieny, with maimum produt throughput rate, and minimum power onsumption. Probability of partile to partile ollision an also be improved, for instane, by inreasing of the irulating load inside the mill hamber. However, the effetiveness of this strategy is limited due to the proess instability that an be generated with high feed rates. Inreasing of grinding air pressure as well as augmenting of the irulating load are eamples of proess adjustments that an lead to potential undesirable effets as multivariable ausality diagram is showed in the proposed ausality diagram.

6 L. Coutinho, M. Embiruçu 2.2 The Auut Air Classifier Air lassifiation is a solid-gas separation method used to lassify partiulates aording to their size. The air lassifier used in the plant is an Auut C-24 lassifier, a type of high energy fored vorte air lassifier, manufatured by Hosokawa Miron Powders In. An overview of several modern air lassifiation devies, their operation priniples, features, proessing and performane parameters was given by Shapiro & Galperin, 2005, whom also refers to the Hosokawa lassifiers as blade lassifiers. The lassifier and the lassifiation plant are shown in Figures and Feeding Air + Fines from Cylone Produt to Cylone Air intake filter Fines to bag filter Figure Frontal and side view of a Donaldson Auut Air Classifier Hosokawa Miron In. Edutor Air Bag Filter Cylone Jet Mill Produt Auut Classifier Blower Fines Pneumati onveying system Classifier Produt Figure Classifiation plant Its priniple was patented by Lapple in 1970 (Lapple, 1970; Lapple & Shaller, 1971). This type of lassifier is also referred to as entrifugal ounterurrent lassifier. A model for performane of ounterurrent lassifiers and a phenomenologial desription of them was presented by Wang & others, Partile size lassifiation plants are omprised of a pneumati onveying system for

7 and modeling of partiulate systems in an industrial sale plant. feeding ground material, a ylone to ollet oarse produt, a bag filter to ollet the fine fration, and an ehaust system as the soure of the air flow for the plant. As shown in Figure 2.2.3, the air enters the lassifiation equipment from an inlet filter loated on the rear of the lassifier, passes through a flow meter and enters the lassifier housing. One inside the housing, the air flows into the rotor by a very narrow annular spae between outside diameter of the rotor and inside diameter of the stator. This is the pre-lassifiation area, also referred to as the high dispersion zone (Allen, 1990). This design provides the dense partile medium to be dispersed to enable posterior partile size lassifiation. Inside the rotor, smaller partiles are dragged by the air flow and moved radially inward to the entral outlet. Larger partiles and soft agglomerates are moved towards the stator until they reah the oarse outlet. Smaller partiles, onsidered as fine fration, are arried out with the air and to a bag filter, whih is used to separate the air from the fines and ollet the partiulate material. Fines are further reyled as part of the raw material in the first step of the produt proessing The oarse fration that was direted to the oarse outlet flows to a ylone separator where the lassified produt is olleted through the bottom of the ylone. The vorte tube of the ylone is the outlet for rejeted fine fration that returns to the lassifier housing to be relassified. Air + ylone fines Feeding Cylone Feeding Housing Rotor Coarse eit Air + Fines Plane 1 Plane 2 Stator High dispersion zone Rotor Vanes Stator Classifying zone Main input air Figure Donaldson Auut Air Classifier Classifiation proess performane The performane of a lassifiation proess an be epressed by different methods. Grade effiieny analysis is the most ommon approah to assess separation effiieny (Allen, 1990), (Gommeren, 1997). A summary of the grade effiieny method is given in Figure

8 L. Coutinho, M. Embiruçu M Separation proess M M f M = M + M ( ) df ( ) M = M d M E = M M G ( ) = M f df ( ) + M d df f ( ) d df ( ) df ( ) f G ( ) = M M d f d df ( ) G ( ) = E df ( ) f ( ) ( ) ( ) ( ) ( ) Figure Grade effiieny method for a single separation proess The mass balane and grade effiieny an be epressed by the equations to , where: M is mass of feed material, M is the mass of oarse produt and M f is the mass of fine produt. The subsript inde in M, M and M f is used to designate theses quantities for partiles with size. F() is the umulative distribution for the partiles with size in feed material. F () is the umulative distribution for the partiles with size in the oarse produt. df ()/df() is the relative fration of partiles with size reovered in the oarse produt. E is the total mass effiieny for the oarse produt. G () is the grade effiieny whih desribes how effiient a given partile with size is reovered from the feed material and olleted in the oarse produt. Grade effiieny desribed in this way assumes perfetly dispersed partiles in the air and no dead flu or by-pass, whih is represented by a fration of feed material that passes throughout the lassifier without separation. In a theoretial ase of total by pass, there is no separation and the produt is olleted after lassifiation with virtually the same partile size distribution. Agglomeration and poorly dispersed partiulate in lassifiation zone are possible auses for inreased dead flu. 3 The multivariable ontrol problem for the etended size redution operation. For the objetive of this work, the etended size redution is defined as the operation that omprises both grinding and lassifiation plants. The main ontrol objetive for the size redution plant is not quite different from any other type of industrial proess: improve or maintain produt quality and redue manufaturing ost. In spite of the physial arrangement of jet milling and lassifiation equipments as stand alone operations in the size redution plant, it is not possible to meet main ontrol objetives unless onsidering them as an integrated plant. In fat, quality and ost of size redution produt depends not only on eah plant as stand alone

9 and modeling of partiulate systems in an industrial sale plant. operations but on the interation of these proesses. This setion desribes the ontrol objetive and the ontrol problem for eah proess and the reasons why they must be studied as an integral operation. In fat, most of the open literature on the related ontrol problem, as desribed by many authors, deals with pilot plants or stand alone equipment. Regardless of the quality of the proposed models, onstruted upon the pilot plant ontrol problem, many of the noise fators were not taken into aount aordingly. A realisti disussion on the diffiulties of implementing partile size ontrol in partiulate proesses is found in Heiskanen, This paper, issued in the middle 90 s, refers to ertain reasons why partile size was not utilized as the ontrol objetive: Lak of proper models for the proesses relating produt size to input variables Lak of on-line partile size measuring methods Need for sophistiated ontrol systems Need for heap omputing power Lak of property funtions Lak of ontrol atuators (input variables) to allow inreased state spae dimensions Inreased system ompleity Inreased researh effort involved. Some of these reasons remain unsolved until today, and others, espeially those referring to tehnology onstraints were solved during the last deade. Not withstanding the advanes in on-line partile size measurement and the urrent availability of omputational power at dereasing osts, the physis of the milling and lassifiation proesses, ertainly the kernel of the problem is still a ompliated question to be solved, mainly beause of the lak of proper phenomenologial equations relating proess input variables to produt partile size. In this ase, when the physis of the proess is not suffiiently known, it is preferable to use system identifiation tehniques to desribe proess behavior in terms of ause and effet relationships. Suh models, also designated as blak-bo models, or empirial models, an be obtained from proess plant eperimentation, looking at the system as a set of input and output variables empirially orrelated. In this ase, previous knowledge about the identified system is required, but the phenomena ourring inside the blak-bo are less relevant than the effets that they produe. Nevertheless, it is not very ommon to find works in available literature dealing with multiple inputs and output variables (MIMO) in grinding and air lassifiation operations, and only very little researh has been published based on blak-boes and nonlinear identifiation methods. 3.1 The opposed jet mill problem Comparing all industrial grinding proesses, air jet milling is the most energy ineffiient as virtually all energy supplied to a jet mill is being dissipated in the turbulent flow that leads to ollisions needed for partile breakage (Gommeren, 1997). In a typial grinding plant with opposed jet mills most of the energy is applied to air ompression neessary to plae partiles in motion inside the mill and the

10 L. Coutinho, M. Embiruçu variable resultant ost of prodution is strongly influened by the energy ost. The quality of the ground produt depends prinipally on its partile size distribution (PSD) that is affeted by proess input variables, mainly the wheel lassifiers speed, grinding air pressure and partiulate feed rate. Suitable ombination of proess input variables must be pursued to improve energy effiieny and deliver ground produts with the desired partile size distribution. After desribing the fundamental aspets of the fluidized grinder and rotor lassifier, it is possible to initiate a desription of the inputs-outputs variables. The following diagram in Figure represents the real jet milling proess as a blakbo, with some of the multiple inputs and outputs that are measured. Grinding air pressure (OLMM) Wheel lassifier speed (OLMM) Solid feed rate (OLMM) Ehaust air flow rate (OLMM) Rinsing air flow rate (OLMM) Grinding air temperature (OLMR) Grinding air moisture (NDDM) Feeding material moisture (OFIM) Feeding material properties (NDDM) Nozzle, hamber and rotor geometry (Fied) Fluidized bed opposed jet mill PSD Volume median (OFIM) MCO PSD Fine fration (OFIM) MCO PSD Coarse fration (OFIM) MCO Produt throughput rate (OLMR) MCO Grinding energy effiieny (OFIM) MCO Cirulating load or hold-up (NDDM) Wheel lassifier eletrial urrent (OLMR) Wheel lassifier pressure drop (OLMR) OLMM On line measured and manipulated OLMR On line measured and reorded NDDM Non diretly or diffiulty measurable OFIM Off line infrequent measured MCO Main ontrol objetive Figure The fluidized opposed jet mill as a blak bo: Inputs, outputs and available data aquisition. Considering that identifiation problem was developed in a real industrial plant, it was neessary to onsider possible onstraints regarding proess instrumentation availability. Eah proess variable was designated in terms of available instrumentation, inluding sensors and atuators, sampling or measurement interval, eletroni data aquisition and reording. Aordingly, this work was instrumental in enabling further eperimentation and visualizes instrumentation opportunities and onstraints. 3.2 The fored vorte air lassifiation problem The priniple of operation of the Donaldson Auut lassifier was presented in the earlier setion dediated to the lassifiation proess overview. The phenomenon of fluid lassifiation whih ours in this type of lassifier is based on the fore balane between the drag fore, provided by the air ehaustion system, and entrifugal fore that omes from the revolving lassifier rotor. As mentioned before, the lassifiation objetive is to remove the eess of fine partiles, or undersized partiles, from the ground material. Hene, produt olletion effiieny is dependent on the partile size distribution that omes from the grinding proess. For a given maimum allowable fine fration, produt olletion will derease with the amount of fines in the feed material. Additionally, due to several stohasti and operational

11 and modeling of partiulate systems in an industrial sale plant. fators, suh as flow turbulenes, air to partile onentration, partile to partile ollisions and partiulate agglomeration, some fines get into the oarse fration and vie versa, whih leads to a separation proess that is not totally effiient. Therefore, produt olletion effiieny of partile lassifiation is a ombination of two fators: i) An eternal fator, whih is the size distribution of the ground material, and ii) The separation effiieny of the lassifiation proess itself. The energy effiieny for lassifiation is also important, but not as ritial as in air jet mill plant. The power usage of the lassifiation plant is around 20% of the grinding plant power. Subsequently, the ontrol problem for lassifier system relies more on produt quality aspets, whih has diret influene on the produt olletion effiieny and onsequently on the proessing osts. Given the eplanation above, improving the lassifiation proess an be ahieved by inreasing the oarse produt olletion rate, with a maimum allowable perentage of fines in the lassified produt, whih an not be aomplished with grinding and lassifiation proess as stand alone operations. Beause omminution inside the lassifiers is fairly ineistent, the volume median is determined mainly by the grinding operation, even though a slight inrease in an be observed with the redution of the fines ontent. On the other hand, fines ontent for the final lassified produt is a funtion of the lassifiation proess only, sine the etra amount of fines generated in the grinding proess an be theoretially removed, regardless of the yield of the proess. Thus, the higher the fines ontent in the produt, the poorer is the lassifiation proess in terms of produtivity and the higher is the proessing ost, given the rejeted fine fration Input-output variables in lassifiation proess It is possible to define input variables for lassifiation proesses in many different ways, depending on the sale from whih the partile-to-gas separation is observed. The table provides a summary of different input variables to be onerned when analyzing partile size air lassifiation, even for stati or dynami modeling. A similar struture applied for the analysis of the omminution problem was presented in Gommeren, Input variables for the partile level were defined based on the variables of influene for the resistive fore against partile movement defined in Massarani, Table Problem sales for the onerned input variables in the fored vorte air lassifiation proess. Problem sale Plant Classifier Conerned input onditions and variables Partiulate feed system: lay-out, mass flow regime, metering devies. Feeding system operational parameters Classifiation plant lay-out (number of lassifiers, arrangement, et) Rotor and stator design (diameter, number of blades, blade profile, dispersion zone) Inlets and outlets position and dimensions Classifier air flow rate Wheel speed Partiulate feed regime and mass flow rate Variable type Design Control Design Design Design Control Control Control

12 Partile L. Coutinho, M. Embiruçu Fluid to partile interation Material Partile size and shape Material Veloity field without the influene of the partiles Design / Control Physial boundaries Design Partile to partile interation (surfae properties, partile Material tribology) Air properties (density, visosity, thermodynami Material / properties) Control Some of the variables in Table 3.1 are inputs or disturbanes in relation to the ontrol problem and others are fied and dependent on the equipment or plant design. For the eperimental work in the lassifiation plant the following blak-bo diagram was onsidered. Wheel lassifier speed (OLMM) Classifier air flow rate (OLMM) Solid Feed Rate (OLMM) Feed partile size distribution PSD (OFIM) Other partiulate properties (NDDM) Classifiation air properties (NDDM) Equipment and plant design (Fied) OLMM On line measured and manipulated OLMR On line measured and reorded NDDM Noise variable or not diretly and diffiulty measurable. OFIM Off line infrequent measured MCO Main ontrol objetive Auut Air Classifier PSD Volume median (OFIM) MCO PSD Fine fration (OFIM) MCO PSD Coarse fration (OFIM) MCO Coarse produt yield (OFIM) MCO Grade effiieny results (OFIM) MCO Cirulating load or hold-up (NDDM) Wheel lassifier eletrial urrent (OLMR) Figure 7 - The Auut Air Classifier as a blak bo: Inputs, outputs and available data aquisition 3.3 Control objetives Produt quality A powder generally onsists of a olletion of partiles with different sizes. Partile size distribution (PSD) desribes the frequeny distribution of the sizes that are present in a partiulate sample. A omplete disussion on partile size measurement is presented in (Allen, 1990). In order to represent PSD it is ommon to use density distributions and umulative distributions. The distribution of density q(), epresses the amount of partiles in eah size lass, in relation to the total amount of partiles either by volume, mass or number. The umulative distribution Q() desribes the perentage of material in whih size is smaller than the upper limit, or top size, of eah lass interval. Mathematially Q() is an integral of q(), being represented by the S urve in the Figure These urves are widely used in the industry beause they enable a fast omparison of PSD, in both qualitative and quantitative perspetives (Gommeren, 1997). The graphs below show the PSD of a partiulate material after grinding and after air lassifiation. When visualized with the aid of a sanning eletron mirosope, samples of material that were measured are given in Figure The visual appearane of the ground material onfirms

13 and modeling of partiulate systems in an industrial sale plant. measurement results shown in the distribution graphs. Notie the large population of fine partiles in the illustration at left and the narrow distribution ehibited at right. In fat, the lassifier redues the amount of fine partiles represented by the fration at the low end of the distribution. 30% 100% 30% 100% 25% 20% 15% 10% q() number% Q() number% 80% 60% 40% 25% 20% 15% 10% q() number% Q() number% 80% 60% 40% 5% 20% 5% 20% 0% 0% 0% 0% Figure Size distribution and of the material after the grinding proess (left) and after air lassifiation (right). (Sanning eletron mirosope AMRAY, magnifiation 5.000X) In several instanes, measures of entral tendeny and statistial dispersion are quite suffiient to onisely desribe a typial PSD enountered after milling and lassifiation proesses. Hene, in spite of onsidering the entire distribution as one unique output variable, what is obviously more ompliated, speifi statistial metris are utilized to represent PSD. The following metris are used to haraterize PSD, and thus produt quality, for the partiulate material in referene: Median ( 50 ) - It is a entral tendeny measure given by the partile size that divides the area under the distribution urve into equal parts. When the distribution is alulated by volume, 50% of the sample volume is omposed by partiles larger than the volume median and the other 50% ontains partiles smaller than the volume median. Considering all partiles have the same density, the volume median is the same as the median by weight. In ases where the distribution is alulated by number, 50% of the ounted partiles are omposed of partiles larger than the number median and the other 50% ontains partiles smaller than the number median. Maimum oarse fration (M ) The funtional performane of a partiulate material an be also influened by the amount of partiles larger than a referene size. Similar to the median, the oarse fration an be epressed as the perentage of partiulate within a speifi size range ( u - l ), either by volume or number, whih depends on the produt requirements. Partiles larger than an upper limit

14 L. Coutinho, M. Embiruçu level ( u ) are not onsidered as oarse fration but as individual large partiles, whih are measured in parts per million or individual ounting. 100% 90% 80% M Cumulative frequene (%) 70% 60% 50% 40% 30% 20% 10% M f 0% f 50 Partile Size l u Figure Cumulative frequeny distribution - PSD parameters used to epress produt quality. Maimum fine fration (M f ) Represents the eess of very fine partiles in the produt, smaller than a referene diameter, whih may have a negative influene on produt quality. As mentioned early in this paper, the fine fration is an intrinsi output of the breakage proess, and one of the objetives of this work is to eplore ertain possibilities to redue the total amount of fines in the ground produt without reduing material yield. An air lassifier is used to redue the amount of fines inoming from the grinding proess, whih results in material losses beause of the eess of fines generated during the partiles breakage. The Figure illustrates PSD parameters taken as quality harateristis for the produt in referene Prodution rate, energy onsumption and ost of operation in the etended size redution plant. The ost of prodution in industrial ativities omprises different fators suh as energy, labor, taation and the ost of added servies. For the sope of this paper, the ost of operation in the etended size redution plant is represented by the eletrial energy onsumed for the following equipments: Grinding air ompressor and dryers, EGA. Jet mill ehaust and fines olletion system, EGF. Classifier fines olletion and ehaust system, ECF. Jet mill ATP lassifier motor, EGC. Auut lassifier motor, ECC. Considering that the fine fration an not be used as final produt, due to quality requirements desribed in the previous setion, size redution produt is only the

15 and modeling of partiulate systems in an industrial sale plant. oarse produt olleted at the end of the proess, whih is represented in Figure 2.4 as the lassifier produt. Aordingly, it is possible to define ost of the etended size redution by means of the speifi energy onsumed in the plant to produe a ertain amount of lassifier produt with a speified PSD. As eplained in the setion dediated to the lassifier effiieny, the amount of oarse partiles reovered in the oarse produt depends on the total mass effiieny of the separation proess and also depends on the separation effiieny of partiles with size, as epressed by the equation In fat, the etended size redution plant omprises several lassifiation proesses, as represented in Figure Therefore, the prodution rate is a funtion of the jet mill rate but is also affeted by the grade effiieny of the ATP lassifier, jet mill ylone, Auut lassifier and oarse produt ylone. E GC G 2 ATP lassifier M ma G 3 Jet mill 2 ylone 3 M mf G 7 Jet mill filter 7 M gr M gm M m E GF M e E GA Grinder hamber Jet Mill 1 G 4 Auut lassifier M M r G 5 Coarse ylone 4 5 M f G 6 Classifier filter 6 Classifier fines olletion system Jet mill fines olletion system M Produt M f Classifier fines M fm Jet mill fines E CC E CF Figure Energy effiieny of the etended size redution plant. 4 Eperiments with an industrial size redution plant This topi desribes the objetives of the proposed eperiments and ountermeasures that must be adopted to prevent equipment damage and inidents with the personnel involved with the eperiments. A previous assessment of the possible behavior of the system was onduted based on the available pratial knowledge, literature and preliminary eperiments performed in the plant. The eperiments were arried out in order to evaluate the dynami response of the plant under manipulation of seleted input variables. Only one input variable was seleted to be manipulated eah time, while keeping all the others fied. Measurable disturbane variables were monitored and measurable fied input variables were also evaluated depending on neessity. 4.1 Jet mill plant The table ehibits the general design of eperiments and qualitative orrelations that were onsidered a priori. Basially two aspets of the response were evaluated: the idealized intensity of the orrelation and the response time of the

16 L. Coutinho, M. Embiruçu output variable under evaluation. This previous assessment in addition to serving as a theoretial basis for the design of the eperiments, aimed to enabling visualization of possible unsafe onditions and operational onstraints given the eistent interloks with the automati ontroller and supervisory system. Table Jet Mill Plant - Eperiment plan and qualitative orrelations between input and output variables. Eperiment identifiation and manipulated input variable #1 ATP lassifier speed variable #1. Eletrial urrent in ATP lassifier motor variable #2. Pressure drop trough the rotor lass variable #3. PSD Coarse fration variable #4. PSD % Fines fration variable #5. PSD Volume median variable #6. Produt throughput rate variable #7. Pressure drop throughout the ylone variable #8. Grinding energy effiieny #2 #3 #4 #5 Grinding air pressure Material feed rate Grinding air temperature Nozzle diameter #6 A/D rate * Legend: Arrows up: positive orrelation, arrows down: negative orrelation. The many arrows, the stronger the orrelation: ( ) fairly or not orrelated; ( ) fairly positive; ( ) positive strong; ( ) positive very strong. The less rossed the arrow, the more rapid response: ( ) Slow response, ( ) fast response, ( ) very fast response. The manipulated variables in the eperiments #1 to #3 onsist of the most ommon proess adjustments made by the operators in order of dereasing frequeny. The ATP lassifier speed manipulated in eperiment #1 is the most ommon proess adjustment used by engineers and operators. This parameter is the first hoie to ontrol the produt quality, given its response speed and the strong orrelation with partile size distribution. Eperiment #2 objetives to evaluate the energy effiieny as a funtion of grinding air pressure. Eperiment #3 was planned to define the threshold values for the solid feed at whih the milling proess enters the instability zone disussed earlier in this paper. The feed rate threshold values were planned to be enountered by onservative inrements in the feed rate set points while monitoring the power onsumption of the eletrial motor that drives the ATP lassifiers and the pressure drop for the lassifiers vanes. In the lak of an on-line PSD measurement, samples of milled material were olleted in a fied sample interval in order to evaluate partile size distribution response. Eperiment #4 was planned to evaluate the influene of the grinding air temperature on the grinding energy effiieny and on the others output variables. Temperature range was limited by the urrent available air ooling apaity. Eperiments #5 and #6 were planned to study the influene of nozzle design in the involved output variables. The main objetives of the proposed eperiments were:

17 and modeling of partiulate systems in an industrial sale plant. i) Evaluate the effet of input variables in the speifi grinding energy. ii) Identify possible orrelations between produt PSD, whih is measured offline, and other proess variables measured on-line, suh as pressure drop for the lassifier vanes and ATP lassifier power onsumption. 4.2 Classifiation plant Eperiment plan for the lassifiation plant is showed in Table The same proedure used for qualitative analysis of the jet mill eperimentation was developed. Given its physial onstrution, the response of the output variables in lassifiation plant is in general muh faster than the responses in jet mill plant. Eperiment #1 was planned to evaluate the dynami behavior of the output variables whit variation in lassifier wheel speed. This variable, besides the lassifying air flow rate manipulated in eperiment#2, is the most ommon adjustment made by the operators to ontrol fine fration on lassifier produt. The solid feed rate was inluded as manipulated variable prinipally to investigate the response in grade effiieny. Inreasing in solid feed rate is a hoie to inrease prodution rate but is limited beause of the risk of equipment damage and quality losses due to generation of fused material in the lassifier produt or and must be used with aution. Grade effiieny is negatively influened by the augmenting in solid feed rate beause of the agglomeration and poor partile dispersion. Eperiments #4, #5 and #6 were introdued to evaluate the influene of the jet milling in lassifiation proess. Table Classifiation Plant - Eperiment plan and qualitative orrelations between input and output variables. Eperiment identifiation and manipulated input variable #1 #2 Classifier wheel speed variable #1. PSD Fine fration variable #2. PSD Volume median variable #3. PSD Coarse Fration variable #4. Coarse produt total mass effiieny variable #5. Grade effiieny variable #6. Classifier motor eletrial urrent variable #7 Prodution rate Classifying air flow rate #3 Solid feed rate #4 #5 #6 Feed material PSD Volume median Feed material PSD Fine fration Feed material PSD Coarse fration * Legend: Arrows up: positive orrelation, arrows down: negative orrelation. The many arrows, the stronger the orrelation: ( ) fairly or not orrelated; ( ) fairly positive; ( ) positive strong; ( ) positive very strong. The less rossed the arrow, the more rapid response: ( ) Slow response, ( ) fast response, ( ) very fast response.

18 The main objetives of the proposed eperiments were L. Coutinho, M. Embiruçu i) Identify possible orrelations between produt PSD, whih is measured offline, and other proess variables measured on-line, whih ould allow an indiret measure of the produt PSD. ii) Evaluate the effet of input variables in the grade effiieny and PSD. 5 Results from preliminary eperiments The eperiments in tables and were oneived for realization in an industrial plant without put in risk equipments or people, prodution plan, produt delivery or quality. This was the prinipal hallenge in the eperimentation ativity. Part of the eperiments were already realized and others are urrently sheduled or waiting for a window in the prodution plan. The objetive of the following trial was to evaluate the pressure drop for the lassifier as an indiret measure of partile size. An indiret measure of the irulation load or hold-up using the power draw of the ATP lassifier motor is showed in Figure 5.1 (Gommeren, 1997). Figure Power draw of the ATP lassifier motor as an indiret measure of irulation load (left) and orrelation between hold-up and partile size (Gommeren, 1997) The results obtained by Gommeren, 1997 shows that it is possible to use the power draw as an indiret measure of partile size. The following eperiment was used to demonstrate that the pressure drop for the lassifier wheel is a possible alternative to estimate ground produt partile size (Figure 5.2).

19 and modeling of partiulate systems in an industrial sale plant ATP Velo. lassifier Real CL01-B speed Feed Solid rate feed rate Classifier 100*Corrente power do draw lassif. B Pressure 1000*Diferença drop for de lassifier pressão :00 36:30 41:00 45:30 50:00 54:30 59:00 03:30 08:00 12:30 17:00 21:30 26:00 30:30 35:00 39:30 44:00 48:30 53:00 57:30 02:00 Figure Pressure drop for the lassifier and power draw in the ATP lassifier motor Pressure drop for the lassifiers was measured by the differene between pressure upstream and downstream the ATP lassifiers. The power draw and the pressure drop are learly orrelated, whih besides the results obtained by Gommeren, Classifier Pressure Drop (PSI*1000) PSI 130 PSI 133 PSI Linear (133 PSI) Linear (125 PSI) Linear (130 PSI) y = 0, ,156 R 2 = 0,9086 y = 0, ,65 R 2 = 0,9326 y = 0, ,03 R 2 = 0, Classifier wheel speed (rpm) suggests the possible use of pressure transmitter readings as a virtual on line sensor for partile size. An additional eperiment was used to evaluate the influene of rotor speed and Figure Regression Analysis for pressure drop and wheel lassifier speed

20 5 Conlusion and reommendations L. Coutinho, M. Embiruçu A omprehensive study of the ontrol problem in opposed jet mill and fored vorte air lassier was made. It as possible to onlude that optimization in the etended size redution plant is not possible onsidering both plants as stand alone equipments given the influene of the grade effiieny of the internal lassifiation proesses in the overall lassifiation effiieny. The eperimentation plan provided a suitable understanding of the required ountermeasures neessary to safe eperimentation in industrial plants in order to avoid ompromising of prodution and quality. A new possible estimator for partiles size was showed. Future investigation is neessary to omplete planned eperiments and onfirm pressure drop for the lassifiers as a indiret measure of partile size in opposed jet milling. 6 Aknowledgements This work was possible beause of the ontribution of Xero Corporation. Speial thanks to my olleagues in Xero for the revising the tet and ontributing in several aspets for the onlusion of the ontrol problem analysis. Also thanks for my professors in Federal University of Bahia, speially for Professor Marello Embiruçu, for the ontinued motivation and important opinions and orientation on the struture of this work. 7 Referenes B. Epstein, Logarithmio-normal distribution in breakage of solids, Ind. Eng. Chem. 40_ K.J. Reid, A solution to the bath grinding equation, Chemial Engineering Siene. 20_ L.G. Austin, Introdution to the mathematial desription of grinding as a rate proess, Powder Tehnology Dods, John. Berthiau, Henri. Varinot, Christelle. Approimate alulation of breakage parameters from bath grinding tests. Chemial Engineering Siene, Vol. 51, No. 19, pp Berthiau, H; Dods, J. Modelling fine grinding in a fluidized bed opposed jet mill part 1: bath grinding kinetis., Vol.106 no.1-2, Nov Berthiau, H; Dods, J. Modelling fine grinding in a fluidized bed opposed jet mill Part II. Continuous grinding., Vol.106 no.1-2, Nov Eskin, D. Voropayev, S.;VASILKOV, O. Simulation of jet milling. Powder Tehnology, v105, p , Berthiau, Henri. Analysis of grinding proesses by Markov hains. Eole des Mines d'albi-carmau, Campus Jarlard, Route de Teillet, 8113 ALBI, Frane. Chemial Engineering Siene 55 (2000) 4117}4127. Gommeren, Herius J. C. Study of a losed iruit jet mill plant using on-line partile size measurements. PhD Thesis. Delft University Press. Delft, The Neterlands, 1997.

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