Characterizationof the
Perfor orm manceof BinBlenders Part 1of 3:Methodol olog ogy Albert Alexa Alexander nder,, Paulo Arratia, Arrati a,Chris Chris Goodridge,Osama Goodridge,Osama Sudah,Dean Brone, Brone, and Fernando Fernando Muzzio* Muzzi o*
In this thi s series series of articles articles,, bin blende bl enderr performanc perf ormance e is is comprehensively comprehensively reviewed using both bo th free f ree-fl -flowing owing and cohesive cohesive mixtures. mixtures. In part 1,an 1, an introduction introduction to tools t ools and and techniques techniqu es is presented, presented,fol followed lowed by an examinatio exa mination n of parameter parameter eff effects, ects,mixing mixing mechanism me chanisms, s,and and the effects effects of cohesio cohesion n on mixing.
B
lendin g powder lending powder and gra gr anul nula ar consti tu tue ent nts s plays plays a vita vit al role in the producti production on of a wide arr rra ay of cons onsume umerr and indus in dustr trial ial products, products, includi including ng ce ceramics ramics,, plastitics cs, foodstu tuff ffs s, and pharma pharm aceut utiica cals. ls.Among Among the th e ava vaiilable equi equippment me nt for powde powderr mixi m ixi ng, tum tumbli bling ng blende blenders rs rema remain in the most most prevalent. preva lent. A number of di diff ffe erent geome geometr tr ies are ava vailila able from blenderr manufac blende manufactu turers rers,, in includi cluding ng V-blenders, V-blenders, cube blende blenders, rs, and double doubl e cone cones s. Howe Howeve ver, r, a more rece recent addit ion to tum tumbli bling ng blender geometr geometriies is the bin ble bl ender, nder,whi which ch is is also known asan intermediate bulk container (see Figure 1). 1). The bin ble bl ende nderr wa was sori originally ginally designed so that after blending is completed the container can be removed from the drive and transported to the t he next process of of ope operati ration on withwi thout discharging its contents into a secondarr y ves onda vessel (i.e., ( i.e., hoppe hopper, r, ba barr rel, etc.). Thi This s adde dded d functiona functi onalility ty elimielimi nates the need for additional transport containers and avoids tying up the produc productition on liline ne.. Furt urthe hermore, rmore,thi this s (b) (a) design minimizes operator contact with wit h the t he blende blenderr co contents, ntents,which which can can Figure 1: Tw o variations of the bin blen der. (a) is a rectangu lar design by Gallay (Birmin (Birmin gham, UK UK), ), be haz hazardous. ardous.Thi This s ser ies of th three reearand (b) is a cylindrical design by L.B. Bohle Bohle (Ennigerloh, (Ennigerloh, Germ any). titicle cles s providesan ove overr vi vie ew of rec rece ent A l b e r t A l e x a n d e r a nd C h r i s comput co mputa atitiona onall and experi experime ment nta al fifindi ndings ngsreg rega ardi rding ng the perf perfororG o o d r i d g e are post-doctoral researchers, mance manc e of bi bin n ble bl enders ove overr a range range of proce proces ssing conditi condit ions and io , P h D , is a and F e r n a n d o M u z z io mixture types. professo r, all in in the Depa rtment of Chemical and Biochemica l Engin Engineeri eering ng a t Rutgers University, 98 Brett Road, Piscataway, NJ 08854, tel. 732.445.3357, fax 732.445.6758,
[email protected]. P a u l o A r r a t ia is a post-doctoral researcher at Haverford Co ll lleg eg e (Haverford, PA) PA),, D e a n B r o n e is a se nior principle principle s cientist of Formulat ion R&D a t P fizer (Ann (Ann Arbo Arbo r, MI), MI), a nd O s a m a S u d a h is an engineering associate at Merck Research Laboratories (Rahway, NJ). Fernando Muzzio, PhD, is also a member of P harm harmaceutical aceutical Technolog Technolog y ’s ’ s ed itori torial al advisory board. *To who m all correspo correspo ndence s hould be ad dressed . 7 0
Pharmaceutical Technology MAY 2004
Characteri haracterizati zation on of mixi xing ng processes Mixingin intumbli bling ngblenders. The simpl imple est function f unction of a tumbl tumbling ing blenderr i s to ble blende bl end all t he co cons nstitituents tuents of a give given n mixtur mi xture e in a sin ingle gle proce proces ssin ing g step step.. I n thi t his s funct function ion,, each ingredient ingredient is loaded loade d separa separately tely i nt nto o t he blender, blender, and the blender blender rot ates untilil a homoge unt homogenous nous mi mixtu xture re has has be bee en forme for med. d. The tu tumbl mblin ing g blenderr also may be us blende use ed to t o ble bl end l ubr ubrii ca cant nts s into int o an already already homoge homog enous powde powderr mixtur mi xture e. In addition, additi on, tumbl tumblin ing g blende blenders rs can be used as preblenders for mixing a low-dose active ingredi gre die ent ( oft ofte en cohes cohesive ive)) with wi th a port portion ion of the exc xcipi ipie ents. nts.Once Once thi s preble preblendi nding ng step step is complete completed, d, the mixtur mi xture e then then is i s transtransferred to a la l arge rgerr ble blende nderr (t umbli ng, co conve nvective ctive,, pne pneuma umatiti c, www.pharmtech.com
Figure 2: The cross section of the groove sampler when the sampler is open and empty (a), open and full (b), closed and full (c). The sample collection procedure (discharge into trays) is illustrated in (d).
etc.) and mixe mi xed d with wi th t he res restt of the excipi excipie ent nts s be befor fore e fur th the er processing. Many experimental investigations regarding the performance manc e of tu tumbl mblii ng blenders blenders have have appe ppea ared in t he li teratur terature e over t he past past few decade decades s. Som ome e stud udii eshave use used d broad br oad compari pa ri sons of the uti utilility ty of dif differe ferent nt blender blender type t ypes s (2 or more at a titime me)) for f or one or two par par titicula cularr mixtur mi xture es (1–3). Other studstudiesha have veinve nves stitiga gated the the mixing mixi ng eff effiicie ciency ncy of one or two t wo blenders blenders for mult ipl iple e mi mixtur xture es to compare compare eff effici icie ency (4–6). (4–6). Only a few few studies have used a single blender with a single mixture to determine termi ne the eff ffe ects of va varrious ope operration iona al pa parame rameters ters on blender efficiency (7–10). Bin blenders have only recently been specifically examined (11–13)) . However, th (11–13 the ese stu tudi die es foun found d bin bi n ble bl enders to be si mil ar i n geome geometr tr y and and functi f unctiona onalili t y to double doubl e cone cone blende blenders, rs, which whi ch have have bee been n more mor e ext xtens ensii ve velly cover covered (8, (8, 14–17). Es Ess senti alllly y, a bi bin n blender blender is i s a “ si ngle cone cone blende blender” r” —a double cone cone blende ble nderr cut in i n half. In the inves investitig gatitions ons of double cone cones s, radia radiall mixin mi xing g (i .e .e., ., pe perpendicular rpendicular to the t he axis of of rot rota ati on) has be bee en found foun d to be more th tha an an order of mag magni nitu tude de fas faster ter than t han axi axia al mixing mixi ng (para (paralllle el to the axis of rotation). Furt he hermore, rmore, insert ing baffles to increase axial displacement has been shown to markedly increa i ncreas se mixing mixi ng rate r ates s. Thes These e ge generi neric c char characteri cteriza zatiti ons of double cone cone blende blenderr pe perf rformanc ormance e are are sim similila ar to the mixi ng perf pe rf or ormance mance i n bi n ble bl enders for some mater mater i als and proce pr oces ssing conditions conditi ons.. Howe Howeve ver, r, for othe otherr mixt mixture ures s, cert ain ba baffl ffle e conconfifig gur ura atitions ons,, and proce proces ssin ing g conditi ons ons,, dif differe ference nces s in blending perf pe rfor ormanc mance e occ occur, ur, whi which ch will wil l be discus discuss sed in de detail tail th throu roughghout this article.
Sampl pliingtool tools sandmet ethods hods The opa opacit city y of granular materi materi als often requi requires resth the e ext xtrr acti ction on of spot sampl sample es for compos composii ti onal analys analysii s to determ determii ne mi mixxture tur e qua qualility. ty. Curre Currentl ntly y, the cha charac racte teri ri za zatition on of granula ranularr mixmi xtures is limited by the errors and biases associated with most ava vaililab able le means means of sampl mple e ext xtrracti ction. on. The most most commonl commonly y used devi de vice ces for sampl mple e retr retr ieva ievall are thief th ief probes. Endnd-s sampl mplii ng and and side-sampling thieves have been shown to produce erroneous inf ormation reg rega ardi rding ng spot spot sample compos compositit ions (18, 19 19). ). A 7 2
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Figure 3: A sketch of a core sam pler is show n in (a). The sample collection procedure is shown in (b). The metal rod is pushed by hand or by a threaded rod, and sample size is controlled by placing a scale under the sample collector collector.. As the powder em erges from the sampler sampler,, a spatula is used to scrape powder into the collection collection vial, which enables better control of sample weights.
major problem with most thieves is that the retrieved sample is not repre repres sentati ntative ve of the true tr ue conce concent ntrati ration on at the t he loca locatition on from fr om whi wh i ch the t he sample sample was was suppose supposed d t o be obtaine obtain ed. Thes These e sampl mplin ing g err errors ors are are caus use ed by contamination contaminati on with wi th mate materrial fr from om other locati locati ons in t he mi mixtur xture e dur durin ing g probe in ins ser ti on. Also Also,, nonuniform nonunif orm flow f low of dif diffe ferent rent compone components nts into the sa sampli mpling ng cavity can skew the sample concentrations (which is common when diff diffe erent sizepart partiiclesare pr pre esent nt)). Recent wor work k has shown tha th at two sampl mple ers—t —the he groove sampl mple er and the core sampler— which whi ch are are use used exclusive exclusively ly i n t hi his s ar ar ti cle cle,, are more eff effe ecti ctive ve,, accurate,, and re curate r elilia able than typical t ypical si si de de-sa -sampl mplin ing g or end-sa end-sampli ng thii eve th ves s ( 19 19,, 20 20)) . The groove groove thi thie ef co cons nsists ists of a hollow slee sleeve ve (1 in. i n. in diame diame-ter) surrounding a solid inner steel rod with a groove bored along most most of the length length of the pipe (19). The in inne nerr pipe pi pe ha has sa sampling cavity that is 1/2 in. in . de dee ep and and wide wi de alon long g th the e mi midddle 80% 80% of of the rod. Rotati otating ng the i nner pipe pip e relative to the t he outer pipe pi pe opens opens and and clos cl ose es the sampler. The sampler sampler i s inse nserr ted int i nto o the th e powde powderr bed while whil e ope open; n; rot rota ati ng the i nner tube t ube t raps material teri al with withii n the the sampl mple er (s ( see Figure 2a–c). Aft Afte er being being remove removed d from fr om the t he powde powderr bi n, the sa sampl mple er is then place placed hori hor i zo zontall ntally y on a stand stand while whi le open, open, and the t he ent ntii re devi device ce i s rot ated to di scharge cha rge the colle collected mater material int nto o a se ser ies of small trays(see Fi Figure ur e 2d). Sampl mple e sizeca can n vary vary dependi nding ng on the t he si zeof the samplerr or the ple t he widt width h of the containe containers rs into which whi ch the ma mate teri ri al is discharged. The other sampling technique uses a core sampler (a hollow tube filed to a thin edge at one end) to gather samples. The tube is thr us ustt into i nto t he mi mixtur xtur e and retrieve retr ieved, d, lea leavi ving ng a core of mate materi ri al i n the t he sampl mple er t hat is held held i n pla pl ace by stati static c fricti fr iction on forces forces, and is i s then extr extrude uded d in a las lastt-in–fi in–fi rst-out ma mannner (see Figure Figur e 3). The use use and accur accurac acy y of th thiissampl mple er hasbe bee en descri cribe bed d extensive extensivelly (20). (20). Thi This ssampl mple er haspr prove oven n to t o give more moreacc ccur ura ate repres represent nta atitions ons th tha an typical typical thie thi ef probesof mi mixtu xture re disdiswww.pharmtech.com
(a)
(b)
(c)
Figure 4: Segre Segregation gation patterns in a 14-L bin blender for a mixture of 1800 gold and 800 purple glass beads. Different patterns are noted when the blender is run at 5 rpm (a),15 r pm (b), and 25 rpm (c).
tr ibut ion tribut ions s whil while e simul multane taneous ously ly causin ing g les less distur disturba bance nce of the powder bed. Avoidi Av oiding ng contamination contamination duri ng sa sample coll colle ection is vit al, but de determi termini ning ng the locati location on and number number of sampl mple es to extra extr act from fr om the t he mi mixtur xture e is equa equalllly y import i mport ant nt.. Oft Ofte en, sampl mple es are taken from fr om throughout t hroughout the bed bed to t o ens ensure ure compl comple ete cove coverr age of the ent ntii re mi mixt xtur ure e. Al Alth though ough this thi s approach gua guarr ant nte ees th thoroughoroughnes ne ss, i t can can lead lead to was wasted ti me me,, eff ffort ort , and materi materia al if i f more efficient means are available. Mixing in tumbling blenders is often limited by the axial tr ans nsfer fer of mate materr i al or by se segre grega gatiti on of the components components (u (us sually caused by variations in particle characteristics such as size or sha hape pe). ). Previous work ha h as shown t ha hatt segre grega gatiti on of mi mixxtures in some tumbling blenders creates axial gradients in concent ntrr atition on (16, 21 21)) . Sim imii lar resul results ts occur occur in i n a bin ble bl ender when when a binary-dis binary-di str ibut ibute ed mixtur mi xture e of gla glas ss be bea ads i s ru run n at constant constant rot ati on rate rate.. Figur Figure e 4 shows the thr hre ee t ypesof segreg gregati ation on patterns that form for m in a binary mixture mixt ure of 1.6 1.6mm mm and and 600 600 glass beads be ads when run at di diff ffe erent rot ati ation on rate r ates s. Thes These e segreg gregati ation on patterns correspond exactly to those seen in double cone blenders blende rs over over a wide rangeof rot ati on rate r ates s and pa p ar ti cle si si ze zes s. The mecha mechani nis sms and eff effe ects of part partii cle si ze and par par t i cle si ze ratio have been discussed in detail (16). Thes The se data data imply i mply that axial sampli sampli ng of the blender blender is vit al whereas radial sampling (sampling at multiple locations on the same li ne pe perr pe pendi ndicular cular to t o the axi axis s of rot rota ati on) may be superflfluous. uous.Thi This s conc conce ept hasbe bee en te t ested in i n a 56-L 56-L bin blende blender. r. Figure 5a shows a typical total sampling scheme for a circular openi ng usi usi ng 14 14 core core sa sampl mple er loca l ocatiti ons. ons.II n Figure 5b, 5b, th the e va varr i ance mea me asured usi usi ng only onl y the t he axial axial sampl mple es (i.e (i .e., ., co cores res1, 1,8, 8,9, 9,12 12,, 13 13)) is compared to the results obtained from using all the probes. Altthou Al hough gh the numbe number of samples has been re r educed by almost a factor of 3, 3,th the e res resul ultiting ng var varianc ance e ve versus rsus revolut revolutiions data show verry good agre ve agree ement, indi ndica catiting ng that li l imi mited ted axi axia al sampl sampliing gives gives information equivalent to that obtained from total sampling (19).
Stati atisti stic cal methods
Figure 5: (a) A typical sampling scheme for a blender w ith a round opening on the top. The sampling locations highlighted in blue are the axial samples and the locations in red are the radial samples. The number corresponds to the order order in which cores w ere taken from the mixture. The decrease in variance for measurements using all samples or just axial samples is shown in (b), using a top-to-bottom loaded mixture of 40 0 sand run at 10 rpm.
Typi callly, a meas Typica measur ure e based on tot t otal al mixt mi xtur ure e vari variance ance has been use us ed asthe mea means to tr ack the evoluti evoluti on of mi mixtur xture e qua qualility ty in tumbli tu mbli ng blende blenders. rs.Whe When n gene nerr ati ng tot tota al mixtu mi xture re va vari ance nce,, all of the sa sampl mple es fr from om a given given tim t ime e point are use used to t o gene generrate var vari-
ance ( 2), standa tandard rd de deviation viation ( ), or re r elati lative ve standa tandard rd deviation (RSD /M where where M me mea an) n),, which can can be i nput nputted ted into a sui uitable table mi mixin xing g inde ndex x and and tra tr acked over tim t ime e. In laboratorylaboratory-
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for Figure 6b, 6b,th the e oppos opposii te, low axi axia al and high radial var var i ance nces s would be detec detected. ted. The extr extra a informati inf ormation on supplied from fr om axial and r adi dia al va varr i ance mea meas sur ure ements would give impor tant clues on the t he bes best mea means ns for appr pproa oaching ching a spe specif cifii c mixi mi xing ng proble probl em. The spli tt in ing g of va vari ri ance is es establi tablis she hed d by first fi rst defini defin i ng an an axial zone j as
[ 1]
i n whi which ch th the e local ( core core)) mea mean n i s , x ij i s a gi gi ve ven n sampl sample e, and number of samples wi withi thi n tha t hatt zo zone ne/core. /core. The stanN i is the number dard da rd defi definit nition ion of va vari ria anc nce e is
Figure 6: Two mixture distributions are shown corresponding to high radial variance (a) and high axial variance (b). (b). In mixtu re (a), (a), each core has the same average concentration,but the sample concentrations within the core vary considerably. considerably. In mixture (b), (b), each core has a different mean concentration, concentration, but every sample within each core is uniform in c oncentratio oncentration. n.
sca cale le experi experiments, ments,tthe blender blender is i scommonl commonly y loa loaded anew anewfo forr eac ach h titime me poi poi nt nt,, and at la l arge rgerr sca cales les,, the blender blender oft ofte en is i s pe peri ri odically stop topped ped and sa sampl mple ed. Thi s experi xperimental/ mental/ stati sti ca call approach provide provi des s broa broad d ins i nsight ight in into to t he rate rate at at which diff di ffe erent materi materi als will wil l mi m i x in a si ngle blender, blender, or can distinguish disti nguish one blender from fr om another another for similar simi lar parame parameter ter se sett ttings ings (f (filill,l, rotati rotation on rate, rate, etc.). The drawba drawback ck is that using a sin ingle gle me mea asure of mi mixtur xture e quality does not give much insight into mixing mechanisms withi wit hin n a spe specifi cific c blende blender. r. For in ins stanc tance e, a poor poor mi mixtur xture e ca can re r esult from fr om diffe dif ferent rent regions regions of the blende blenderr containing containi ng material material with wi th moderately different concentrations or from a few wayward sample pl es (ve verr y high high or ver ver y low) ca cause used by agg agglo lomerati meration on of the active substance or dea dead d zonesin the t he blender. A single single meas measur ure e of varriancemay not di va diff ffe erenti rentia ate betwee between n the t hes se situ tua ati ons ons,, whi which ch is impor mporttant be beca caus use e radically radicall y diff di ffe erent appr pproac oaches hesare neede needed d to to fifix x the these di diff ffe erent cla classes of mi mixi xing ng proble probl ems. One way to gather more information without the need for more sampling is to split up the total variance measurement i nt nto o separate separate depe dependent ndent mea meas sur ure ements of axial vari var i anc ance e and and r adial vari ance. Ra Ratther than th an use use all obt obtained ained sampl sample es to genergenerate a sin ingle gle mea measure of mi mixtur xture e qua qualili ty (i .e .e., ., tot tota al va vari ri ance nce), ), samples are grouped together in such a way to generate individual vi dual me m easureme urement nts s of axi xia al va varr i anceand r adi dia al va vari ri ance nce.. Ra Ra-dial varia vari ance ca can n be int erpr rpre eted as as WL ( wit withi hin n loca l ocatition) on) va vari ri ance anc e and and axial axi al varianc vari ance e as as BL (be ( bett we wee en loca l ocatiti on) on).. The use of core or groove sampl mpliing greatly greatly aids aids th thiis di diff ffe erent rentiiation beca becaus use e the ave averr ag age e val value of ent ntii re cores ( grooves grooves)) ca can n be used used to t o determi ter mine ne axi axial al variance vari ances wherea whereas s the var var i anceof sampl ample es take aken n from fr om a si single core (groove groove)) ca can n determine determi ne radial vari variance nces s (22) (22).. Figure 6 shows two mi m i xtu xtures resth tha at would give si mi milar lar res resul ults ts for tota tot al sampl mplin ing g but ver ver y diff di ffe erent re r esult s whe when n the t he va vari ance i s spli plitt in into to axial and radial radial co compone mponents. nts. For Figure 6a 6a, high ra r adial di al varianc vari ance e and low axia axial vari varia ance woul would d be meas measur ure ed, whereas 7 6
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[ 2]
in which whi ch 2 is variance, N is the numbe numberr of samples mples,, and is the me mea an compos composii tition. on. Subs ubstititut tut in ing g equa quatition on [1] [ 1] int i nto o equa quatition on [ 2] and re r earr rra anging, lea leads ds to
[3].
In equa quatition on [ 3], the firs fir st te t erm is a me mea asure of axial vari vari ance and the second term radial variance. To quant quantii tati tative vely ly compare compare mixing mixi ng eff effii cie ciency ncy,, i t is i s us use eful to deterr mi dete mine ne the rate of va varr i anc ance e ( or RSD) RSD) dec decrea reas se at di d i ff ffe erent proces proce ssi ng condit i ons ons.. A quant quantii tati tative ve mea meas sur ure e of t he r ate of variance decrease can be obtained by assuming exponential deca de cay y (7, 8) and defi defini ning ng a mi mixi xing ng cons constant tant k such such that
[ 4]
i n whi which ch i s th the e va varr i ance at revolut revolutii on M , isvari ria ance at revolution N , and (N M ) is i s the elaps elapse ed number number of revo revolu lutitions ons 2 (RSD can be substituted for in equa equati tion on [4]) . The mixing constant k yields a quantitative measure that can be used to evaluate how changes in process parameters or mixture composition affect mixing rates in the blender. The use use of vari varianc ance e-r -re elated meas measur ure ements is is th the e most most common wa way to ass assessmi mixt xtur ure e quali qualitty. y.II n someca cas ses, however, ot other her varia vari abl ble es can can be use used to t o aid i n t he as assessment of mi mixi xing ng phenomena in the t he blende blender. r. For exa exampl mple e, tr tra ackin cking g the sampl mple e mea mean n (average (ave rageof all th the e ext xtrracte cted d sampl sample es) ca can n indi i ndica cate te tha that the blend blend is not unif u niform orm if the sa sample mea mean deviates deviatessignif ignifica icantl ntly y from fr om the t he expe xpecte cted d mean. mean. Anot Anothe herr strateg tegy y is is to tr tra ack the the cha change nge in mini mi ni-mum and and maxim maximum um sa samples ove overr ti t i me me.. I f the minimum mini mum and and maximum sampl mple esare highly highly abe aberrrant fr from om the t he mean, thi this scould i ndi ndica cate te agg agglom lome er ati on or th the e pres presence of de dead ad zones zones i n t he blender, both of which can can be extr extre eme mely ly detrim detr ime ental to overall ble bl ender perform performa ance nce.. Whe When n analyzing analyzing mixi mixing ng perf rfor ormanc mance e in a www.pharmtech.com
blender, it is i mport ant to t o use use all ava vailila able in infor forma matition on to build buil d the th ebe bes st possibl ble eunderstandi understanding ng of thedynami dynamics cswi witthi hin n the thebl ble ender.
Param Pa rametereffects: effects:s speed, loading, fill For mi xing in i n bin bi n blenders blenders (or any tumbling tumbl ing blender) blender),, pe perhaps rhaps the most most i mpo mporr tant aspec aspectts to assess are the eff effe ects of the bas basi c parameters parame ters (i.e (i .e., ., th thos ose e th tha at ca can n be var var i ed for f or a si ngle blender usii ng one or many us m any mi mixt xtur ure es) on the t he mi mixi xing ng proces process. Tw Two o parameters rame ters,, the loading method method (h (how ow the cons constititu tue ent ma materi teria als are put into the blender) and the fill level (the percentage of tota tot al bl ble ender capac capacii ty occupi occupie ed by the the materi material) al) are alwa always ys va varriable, whi while le in some some ca cas ses, th the e rot rota ati on ra r ate of th the e blende blenderr also also can ca n be adj adjusted. usted. Ge General neral guideli gui delines nes and cave caveats ats rega regarrdi ding ng the th e eff ffe ects of fifillll,, loading, and rotation r otation rate are are des descri cribe bed d below. below. Lowerfil fill levelsindu inducefastermixingrates. Whe When n the t he amount of materi mate ria al in i n the the blende blenderr is i sreduc reduce ed, mi mixi xing ng shoul hould d be faster. ter.HowHoweve ver, r, ve verr y low fill fi ll leve levels ls (25%) interfere with natural mixing in g mecha mechani nis sms and hinder hi nder mixi mi xing ng rates rates. Fil Filliling ng the blende blenderr to to more mor e than 60% 60% of i ts capac capacii t y can can le l ead to t o dead dead zones zones i n the t he middle of of the mixtur mixture e tha thatt do not inte i nterac ractt with wi th the t he re res st of the mixture. Loading. Symmetrical top-to-bottom loading will stress radial mixin mi xing g and, and, he hence nce,, mi mix x faster faster tha th an loa l oadi ding ng the blende blenderr le l eft ft-to-rr i ght, whi towhich ch emphas mphasii ze zes s slower axi axia al mixi mi xing. ng. Rotati otation onrate. Cha Changin nging g the rota rot ati on r ate hasbe bee en shown to to have ha veno effect effect on mixi mi xing ng rates rates for fr fre ee-f -flowi lowing ng materi materia als at at modm oderate rotation rates ( 25 rpm) using relatively small blenders (7, 8). Howeve However, r, these fi ndi ndings ngs havenot be bee en adequately adequately test tested using usin g cohe cohes si ve mi mixt xtur ure es. For ver ver y cohes cohesii ve mi mixt xtur ure es, shea hearr becomes come s the domina domin ant factor and rotati r otation on ra r atesmay play ade decicisive role in determining mixing rates.
flow patterns on the surface of Figure 7: Sketches of the visible flow mixtures in rotating cylinders for mixtures of free-flow ing (a) and cohesive particles particles (b). For For free-flowing mixtures, the flow is straight, regular,, and downstream. For cohesive regular cohesive mixtures, groups of particles avalanche avala nche dow n the c ascade in multiple directions and these failures can start from almost any point on the surface of the mixture.
standing of tumbl tumblin ing g ble blende nderr operati operation. on. Effectsof mixturecharacteristi characteristics csonmixi xing ngmechanisms.The major obstac obs tacle le plagui plaguing ng the defifini nitition on of mi mixtur xture e cha charac racteri teris stitics csis the lack lac k of ava vaii lable me mea ans for me mea ani ningful ngful compari compari sons of mi mixtu xture re cohe co hes sion. The inabil inabilitit y to us use eful fully ly and quanti quantitati tative vely ly define defin e pa parrticle and/or mixture characteristics means that mixtures become quali qualittati ative velly char char acteri cterize zed d as free-flowing, co cohesi hesive ve, so somewhat cohesi sive ve, mostly free-flowing, etc. Mixing Mixi ngmechani hanism sms A fre free e-flo -flowin wingg mixture is one for which flow is determined Befor Be fore e discuss discussing spec specii fific c mixi mi xing ng mechanisms mechanisms for bi bin n ble bl enders, by th the e dynamics of i ndi ndivi vidual dual par par ti cles. I n es essence nce,, each part partii it is useful to examine some common rules that apply to tum- cle can can be tra tr acke cked d and account account ed for f or separate parately ly and mi mixi xing ng bliing blender bl blender perfor perf ormance mance.. Perhapsthe most obvious obvious (and most most mec mechanisms hanisms ar i se fr from om the t he t i me-av me-ave er age ged d flow fl ow of th the ese i ndi ndi-important) observation is that radial mixing has been found to vidual par par titicle cles s. A cohesi sive ve mixture is one for which single parbe more than one orde orderr of ma magnit gnitude ude fas faster tha t han n axial mixin mi xing g titicle cles s do not flflow ow independe ndentl ntly; y; rathe rather, r, groupsof pa part rt iclesact (8). Ra Radial dial mi xing is i s be belili eve ved d to oc occur cur as the mixt ure winds in concert when force is applied to the entire mass (avalancharound a central point at the interface between the cascading i ng). Henc Hence e, mi mixi xing ng mecha mechani nis sms de deri ri ve fr from om the motions moti ons of laye lay er and materi materia al undergoin undergoing g soli olid-body d-body rotation, rotati on, for formi ming ng groups of part partii cles r ath the er than t han si si ngle par par ti cles and the t here re may may striations and layers that become finer with increasing rotations not be any meaningful time-averaged flow field. (23). Axial mi mixi xing ng is beli belie eve ved d to t o be depe pendent ndent on random axial Outs Out si de of sphe pherr i ca call glass beads ds,, ve verr y few mater mater i als are are tru t ruly ly fluctuations in particle velocities as the particles flow down the fr fre ee-f -flowi lowing. ng. Granulate Granulated d la l actos ctose e and and sand sand both bot h exhibit exhibi t some cas ca sca cade, de,ge generat neratiing aslow dispersive mi mixi xing ng process (24). How- ava valanchin lanching g tendencies tendencies but are sti sti ll cons consii de dered red free f ree-f -f lowi ng. eve ver, r, th the ese ge generi neric c mixi mi xing ng mecha mechani nis sms fai fai l to provi de any any ini n- Other typical pharmaceutical materials such as microcrystalline sight into approaches for improving mixing performance be- ce cellll ul ulos ose e and and mi micron cronii ze zed d lac l actose tose clea clearr l y are cohes cohesi ve and and exyond prefere preference nce for radial mixin mi xing g ove over axial mixin mi xing. g. Another hi hibi bitt strong str ong ava avall anchi nching ng dynami dynamics cs.. Thes These e di diff ffe erence rences s i n mixmi xfeatu fea ture re that has not be bee en addressed is i s th the e cri crititi ca call role r ole of mi mixx- ture characteristics have a significant effect on the resulting flow ture properties (especially cohesion) in generic mixing mech- characteristics and mixing mechanisms. ani nis sms ms.. A major major run runni ning ng theme theme thr througho oughout ut t his se seri es of art iThe most recognizable change in mixture behavior that recles is that mixture characteristics (however poorly defined they sul ultt s fr from om the t he de degre gree e of cohe cohes si on is i s th the e flflow ow patt patte er ns th that at are are may ma y be) be) ca can n be much much more import im porta ant for de determi termini ning ng mixing mixi ng obs obse er ve ved d in i n tr t r ans ansparent parent vess vessel s, i l l ustr ustrate ated d here as a ro rott ati ating ng rates and overall performance than blender or operational cy cylilinde nderr (se (see e Figure Figure 7). 7). For rot rota atition on ra r atesin the rollin roll ing g regime regime spe pecifi cifi cs cs.. Thi This s obser va vatiti on in indicate dicates s that the deve developm lopme ent of ( 25 25)) , fr fre ee-f -flowi lowi ng mixtur mixt ure es are charac characteri terize zed d by areg regul ula ar flow f low effective methods for defining and measuring critical material wit with h a nea nearl rly y fla fl at surf urfa aceand lit l ittltle e or no n o vari varia abil bilitit y in be bed d height height properties will be crucial for a more comprehensive under- pe perp rpe endi ndicular cular to t he me mea an flow; f low; pa parr titicle cles s tr tra ave vell alon long g pathl pathlin ine es 7 8
Pharmaceutical Technology MAY 2004
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nearl nea rly y perpendicular perpendicular to the axis axis of of rot rota ati on. In contra contr ast, co cohe he-si ve mi mixtu xture re flow fl ow is charac characteri terize zed d by a ser i es of fail failur ure es on the t he surf urfa aceof the mixture mixtur e, which mark mark the t he ons onse et of flflow ow for a discrete cre te port port ion of the mixture mixt ure (the size size of the fail fail ures is most most likely dependent on mixture properties and blender rotation r ate). The flow of th the ese ava valanche lanches s i s t ypi ypica calllly y both downward and outwa out ward. rd. Thus, Thus,the the sur surfac face e of the cohesive mixture mixt ure is marked marked by many hill hil ls and val valleys ys,, and the t he flow down down the t he ca casca cade de is rare arely ly str tra aight or perpendi perpendicula cularr to t o the axis of of rot rota atition. on. Charac Cha racteriza terizatition on of flflow ow patt patte ern rns s is furthe furt herr co compli mpli ca cated ted bebecaus ca use e mixtur mixt ure es are oft ofte en composed of many compound compounds s wi with th diff di ffe erent degree degrees s of cohe cohes si on. Di Diff ffe erent compli ca cated ted flows ca can n occur occ ur de depe pendi nding ng on the fractiona fracti onall composi composi ti on of each conconsti tuent, the relati relative ve cohe cohes sion bet betwe wee en the th e component components s, the de de-gree gre e of dil dila ati on, elec lectr tros ostati tatic c cha chargin rging, g, and the distr distribut ibution ion of these materi materia als in the mixtur mi xture e (es (espe pecially cially the t he initi ini tia al co condi ndititions ons). ). In mixtures for which actives and excipients have similar flow propert pr opertiies, th the e ge general neral flow fl ow typesdi dis scus cuss sed previously previously will wil l pre pr evailil.. Howe va Howeve ver, r, whe when n one pa parr t of the mixture mixt ure is cohesive and and the t he other part is fre fr ee-f -flowi lowing, ng, les less s predictable predictable beha behavior vior wil willl oc occur. cur. Fur urthermore, thermore,the the relati relative ve amount mounts s of of the vari vari ous compone components nts willl pla wil play y an an import i mporta ant role in de determini termini ng the flow beha behavior vior and mixi m ixing ng mecha mechanisms nismsof the mixtur mi xture e. In gene neral, ral, expe xperi ri ence i ndi ndica cates testh tha at even small small amounts amount s of hi highly ghly flowa fl owable ble materi materia als can ca n signi signififica cant ntly ly improve im prove flflow ow propert propertii es of the whole mi mixtur xture e, but more work is needed before a clear theory emerges.
Computat putatiionalmet ethods hods: di disc scret rete eelementmet ethod hod One avenue that may eventually lead to a fast and effective means for testing new blender designs and process parameter effects on ble bl ende nderr pe perf rf ormance i s the use use of of compute computerr sim imulati ulation. on. Some promi prom i si ng re r esul ults ts have have bee been obt ained comparing compari ng bin bi n blenderr pe blende perf rf ormance i n experi experi me ment nts s and simula simul ati ons for t he mixi mi xing ng of large fr fre ee-f -flowi lowing ng glas glass be bea ads ds.. A commonly used particle dynamics method for the modeliling ng of gra granular nular flow f low is i s the discre discrete te eleme element nt me method thod (DEM) ( DEM).. DEM us use es Newton Newtonii an phys physii csto de determi termi ne the veloci velocitt y, y,a angular momentum, and posit position ion of pa part rticles icles. Each part particle icle is tra tr ack cke ed in the system and particle–particle and particle–boundary interactions teracti ons are comput compute ed. DEM si si mul mula ati ons are oft ofte en thought th ought of as a mac macrosc roscopic opic equi equiva valent lent of shor hortt- range mol mole ecular dynamics in whi ch the in ine elas lastiti c natur natur e of pa parr ti cle colli collis sion ions s is taken take n into in to account. account. I n rece recent years, years, th the e us use e of part partii cle dynamic sim imul ula atitions ons has has prol prolii fera ferated ted (26–29), (26–29), and currentl cur rently y is i s be bei ng apapplie pli ed to t o cer cer tain co complex mplex indus in dustr trial ial problems (30–3 (30–32). 2). DEM simulati simu lations ons cons consii de derr granular ma m ateri teria al as a coll colle ecti ction on of fr fricti ictiona onal,l, pa part rt iall ially y elas elastitic c sphe pheri ri ca call particles part icles(33). Each parparticle may interact with its neighbors or with the boundary of the th e blende blenderr throu t hrough gh both nor mal and and tangent tangentii al force f orces s. The elas lastitic c modulus modul us and and computati computational onal ti t ime-s me-step tep are chos chose en so tha that defor de formation mations s of pa parr titicle cles s rema remaii n small small when compare compared d with wi th the th ei r di spl pla ace cements ments and dia di amete meterr s. Par ti cle i nt nte er acti ctions ons are tra tr acke cked d using linke li nked d list l ist algorithm algori thms s and the t he res result ult i ng equa equatitions ons of moti motion on are are in integ tegrate rated d usin using g a “ lea leap-f p-frog” rog” algori lgorithm. thm. Good agreement can be obtained with experiments for freeflflowin owing g par par titicles cles. Exper i me ment nts s we were re run at 10-rpm 10-r pm and 60% 60% of total capacity with 8-mm glass beads in a 14-L bin blender of 8 0
Pharmaceutical Technology MAY 2004
Figure 8: The RSD RSD is plotted agains t the num ber of revolution s for simulations and experiments experiments of 8-mm spherical particles, particles, which ran at 10 rpm in a 14- L bin blender. blender. The The mixing rates show good agreement between simulation and experiment.
t he same same ge geometr ometr y as shown i n Figure Fi gure 1a. 1a. A vacuuming vacuumi ng and counting technique was used to generate concentration data ( 33). Si mul mula at i ons we were perf perf or ormed med at at t he 1:1 sca call e used in i n the t he expe xperi ri me ments. nts. The sim simulati ulation on was“ sampled” by defi defini ning ng cubic sampl mplii ng boxes boxes in t he si si mul mula ati on. Ea Each ch box was cons consii de dered red a separate sampl mple e and cont contained, ained, on ave averag age e, 40 par par ti cles. I n Figure 8, 8, the evoluti evolution on of mixt mixture ure vari vari ance is shown shown for t op-tobottom and left-to-right loading for both simulations and experr i me pe ment nts s. The DEM and exper exper im ime ent nts s showe showed d very good agreement in i n both bot h the th e de degree gree and rate of mi mixi xing ng under the th ese proce pr ocessing condi condititions. ons.Howeve However, we must caut cautii on that t hat the t hes se encouraging results have been obtained for perfectly spherical, fre fr ee-f -flowi lowing ng part partii cles. Si mul mula at i ons are curr curre ent ntly ly hampered hampered by both th the e lack of good models models for cohe cohes sive forces forces and the t he li mi ted number of part partii clesth tha at can be si mul mulate ated d in i n a rea reasonable amount of titime me.. Furt urthe hermore, rmore, de dea aliling ng with wit h nons nonsphe pheri rica call pa parrticles or size distributions increases the computational time neede ded d for eve ven n a relati relative vely ly small small number n umber of part partii cle cles s. At pre pr esent nt,, si mul mula ati ons are are far from f rom clos close e to being bein g appl applii ca cable ble to re r ealworld worl d applica appli catiti ons and and are only useful useful for small mall-- sca cale le theoreti ca call inve i nves sti ga gatiti ons of spe pecif cifii c gr gr anul nular ar phenomena phenomena..
Anexampl ple e A pre pr eli mi minary nary exa exampl mple e of how to dis di ssect and analyz analyze e mi mixin xing g data da ta is presented: the mixing mixi ng of 1% w/ w/ w% diphenhydramine diphenhydramine HCl wit with h an an exc excipi ipi ent ma m atr ix i n a 56-L 56-L Gall Galla ay bin ble bl ende nderr r un at 10 rpm (se (see e Fi Fi gure 1a 1a) . The excipi excipie ent matr matrii x is i s compos compose ed of microcrys mi crocrystall tallii ne ce cellllulose ulose(PH102 Avice Avicel,l, FMC Corp., Phi hilade ladellphia phi a, PA) A),, granulated lactose lactose(Fastt-Flo, Flo, Foremos oremostt Farms,Ba Farms, Barr aboo, WI WI)) and magne magnes siu ium m stea stearate rate (n (nonbovine, onbovine, Mall Mallin inckrodt, ckrodt, Hobart Hoba rt , NY) with wit h a formul formula atition on of 39 39%, %, 60 60%, %, and 1% 1% w/w%, w/w%, respec res pectiti ve vely. ly. Core sa sampl mplii ng was used to t o gath gathe er samples amples;; ni nine ne cores core s fr from om throughout t hroughout the blender blender surf urfa ace(i .e .e., ., tot tota al sampl mplin ing) g) were taken for every time-point and each core yielded 15–25 samplesof 0.8g 0.8g.. I n thi t his s study, UV spectr spectros oscopy copy was was used to determine termi ne the compos composiitition on of sampl mple es ext xtrracted fr from om the the blende blender. r. To useUV spe pectr ctros oscopy copy,, a line li nea ar ca calilibr bra atition on curve cur veof abs bsor orba bance nce www.pharmtech.com
Figure 9: Mixing perform ance of Benadryl in a 56-L bin blender is assessed by examining total variance decrease (a), (a), variation in maximum and minimu m samp le concentration (b),radial variance decrease (c), and the time evolution of the sample m ean (d). (d). The The grey line is the mixture m ean.
versus acti versus ctive ve concent ntrr ati ation on was obt obta ai ned for a se ser i es of 1:50 1:500 0 dillut di utii ons in de-ioni de-i onize zed d water. water. A sharp sharp peak peak wasobs obse er ve ved d at 215 nm and shown to correspond solely to the active and not the excipients. The evolut volutii on of th the e RSD for expe xperr i me ment nts s ru run n at at 50%,65 50%, 65%, %, and 85% of tot tota al blender ca capa pacity city is shown shown in i n Figure 9a 9a. I n the t he earl arly y phase phases of the mixi mixing ng proce proces ss, the 50% 50% cas case had the the hi highghest mi mixt xtur ure e va varr i ance nce,, whi which ch is cont contrr ar y to th the e expe xpecte cted d re r esul ultt s. At late l aterr t imes, th the e 50% cas case“ ca caught ught up” u p” and eve event ntuall ually y beca became me the th e lowest RSD (be ( bes stt-mi mixe xed) d) mi m i xt xtur ure e aft fte er 200 revolut revolut i ons. ons.At At 65% 65 % and and 85% fill fi ll,, th the e RSD wasne nea arl rly y cons constant tant th throughout roughout the mixi mi xing ng proces process, whi which ch appe appears ars to indi i ndica cate te that mi m ixi xing ng was was complete aft fte er only 4 re r evoluti ons ons.. Thi This s curi curious ous result at short mi mixxi ng ti mes ca can n be bett bett er unders understood tood by analyzi analyzing ng othe oth er computed statistics rather than conjecturing solely based on interpreti in terpreting ng the de deca cay y of the RS RSD. In thi s ca cas se, tr acking the change cha ngei n the t he minimum mini mum and maximum maximu m sampl sample e conc conce ent ntrr atitions ons provides more insight into mixture distributions (see Figure 9b). 9b ). At earl early y mixing mixi ng time tim es (64 revolut revolution ions s), the diff di ffe erenc rence e between twee n the t he maxi maximum mum and mi m i ni nimum mum va valu lue es wa was s gre greate aterr for t he 50% ca case t han for ei th the er t he 65% or 85% ca case. Thi This s di dis st r i buti on impl i mplii es th tha at th the e 50% ca case wa was s r adi dia alllly y mixe mi xed d more mor e poor poorly ly than the other cases, whi which ch is conf confiir med by examin xaminiing the evoevolution lut ion of radial varia vari ance(se (see e Figure Figure 9c). 9c). Earl rly y in th the e mi mixi xing ng proces process, th the e mi mixt xtur ure e be beca came me radi dia alllly y well well-mixe mi xed d at both 65 65% % and and 85%, but rema remaii ne ned d ra r adiall dially y unmixe unmi xed d at 50% fi llll.. Thes These e res resul ults ts cont contrr adict the t he expec xpected ted outcome outcomes s that lowerr fifillll lev lowe leve els would would mi mix x faster faster tha t han n highe hi gherr fifillll lev leve els. Eva valulu8 2
Pharmaceutical Technology MAY 2004
ati ng the evolut volutii on of sampl mple e me mea an provide provi des s mor more e i ns nsii ght int i nto o the th e ca caus use e of thi s quanda quandarr y (see (see Figure 9d) 9d).. For all th three reefifillll levels, ls,the the data data in Figure 9d, 9d,in indicate dicatethat earl early y in the mixing mixi ng process the sampl ample e mea mean n is i s much highe hi gherr than t han the the expected mean, mean, whi which ch appears to indicate that the blend is superpotent in the sampled regi regi on. In titime me,, th the e sampl mple e mea mean decrea decreas ses for all thr thre ee fill fil l levels, leve ls, but onl only y at the t he 50% 50% fill fi ll leve levell doe does s the sampl mple e mea mean approach the tr t r ue mea mean. The loading loadin g procedur procedure e i nvolved the use use of a hopper to t o dedeposiit ma pos m ateri teria al in i n the t he cent nte er of th the e blende blender. r. The acti active vewa was s loade loaded d lastt and, he las hence nce,, in initit iall ially y was was co conce ncent ntrate rated d in the middle middl e of the blender. blende r. Sampl mplii ng was was lilimi mited ted to the t he mi middle ddle 40 40% % of the mixture tu re beca becaus use e of li mi mited ted acc acce ess fr from om the t he ope openi ning ng of th the e blende blenderr to the t he mi mixtu xture. re.Thi This s loading and sa sampl mplin ing g meth methodology odology place placed a premium on axial axial t rans ranspor portt t o the edge edges s of the blende blenderr f or achie chievin ving g auni unifor formly mly well-mi well- mixe xed d product. Appa Apparently, rently,a at highe higherr fifillll leve levels, ls, th this is axi axia al t r ans nspor portt wasdi dimi mini nis she hed d and and the t he acti ctive ve remain ma ine ed trappe t rapped d in i n the t he middl middle e of of the blende blender, r, which rapidly le l ed to a we wellll -mi xe xed d but supe superp rpotent otent blend blend in the t he mi middle ddle of the mixtur mi xture e whi while le leavin leaving g the blender blender extr xtre eme mes s defi deficie cient nt in acti ctive ve (l eadi ding ng to fas fastt de decli clines nes i n r adi dia al va varr iance but hi high gh sa sampl mple e means mea ns). ). I n the t he 50% ca case, howe howeve ver, r, axi xia al tr ans nspor portt was more eff ffici icie ent at moving the active to all all port ions of of the mixture mixtur e, but led to increased radial variances because active concentrations were constantly in flux as higher potent material from the center intermingled with subpotent material from the edges. This Thi s example i ll us ustr tr ates th that at usi usi ng mult i ple mea means of de detertermining mixture quality can provide important insight into the www.pharmtech.com
Figure 10: Measured RSD in situ and in a container post-discharge for a cohesive mixture of salt and microcr ystalline cellulose cellulose (a), (a), and a free flowing sand mixture (b), both at 60% fill level.
Figure 11: For the sand mixtu re, the radial variances (a) and axial variances (b) are compared before and after discharge.
mi xing mixi ng mechanis mechanisms ms wit within hin the blende blender. r. In addit ddition, ion, it servesas a wa warn rnin ing g that relying relyi ng on a single mea measur ure eof mi mixtu xture re quali qualitty can lead to misleading and erroneous conclusions about the mixing in g proces process in the blender. blender. Finally, thi s exa exampl mple e also also shows shows that loading and sampling methods must be included in the analys nalysiis of any mi m ixi xing ng proce pr ocess.
clues (see Figur clue Figure e 11). On di dischargethe meas measur ure ed radial r adial vari var iance incr ncre eased whi while the axi axial al vari variancedecreased; the RS RSD incr i ncre eased because the rise in radial variance was greater than the drop in axial varianc vari ance e. There are are two two lil ikely caus cause es of the increa increasing RSD with wi th dis di scha charge rge:: ini nititia al conditi condit ions and sa sampl mpliing bi bia as. The blende blenderr was loaded top-to-bottom to produce an axially symmetrical inititia al conditi condi tion. on. However, be beca caus use e th the e blende blenderr is i s not symmetr symmetr ic in a toptop-toto-bott bottom om se sens nse e, the initi ini tia al conditi condit i ons produce produced d a gradient in i n conce concent ntrati ration on from fr om the middle middl eof the blende blenderr outwa out ward rd (s ( see Figure 12 12). ). As sampl mplin ing g in situ sit u was was lilimi mited ted to the mi middle ddle of the blender,th blender, thiis axi xial al gradient wasove overl rlooked ooked and the t he mi mixt xtur ure e may have hav e appea ppeared red to be bett tte er blended than it i t rea realllly y was was. Aft Afte er di dis scharge cha rge,, the mi mixt xtur ure e wa was s mor more e thorou horoughly ghly sampled sampled which resul ults ts in thi t his s appare pparent nt separa paratition on dur durin ing g discha discharge rge that wasactually the result of be bett tte er sampl mplin ing g techniques techniques. Dur Durin ing g discha discharge rge,, the axial axial vari va ria abil bilitit y was was tr tra ans nsfor forme med d into int o radial radial vari vari abil bilitit y. Alt Althoug hough h in this thi s ca cas se (a nonse nonsegre grega gatiting ng mixture) mixt ure) the t he qua qualilitt y of the mixture mixt ure wasexpected to impr i mprove ove upo upon n dis di scharge charge,, the appar ppare ent dec decrrease in qua qualility ty wassole olely ly a function functi on of impr improv ove ed sa sampli mpling ng of the mixture. tu re.The The differe dif ference ncebe betwee tween the t he axi axia al and ra r adi dia al va varriance iances sin situ sit u and pos postt- di dis scha charge rge vir tu tua all y dis di sappe ppea ared as th the e mixt ur ure e apapproaches proache s a we wellll-m -mii xe xed d state state (32 revolut revolutii ons ons)) . Thus, whe when n dis di schargi cha rging ng anonse nonsegreg grega ating mixtur mixt ure e fr from om a bi bin n blender,i blender, it can be expe xpecte cted d tha t hatt we wellll-mi -mi xe xed d products pr oducts will not be aff ffe ecte cted d but that poorly mixed blends may actually improve in mixture quality. Any results that contradict these general expectations are likely caused by sampling biases or segregation.
Discharge Mixing materials in a tumbling blender does not end the processing of that mixture. mi xture. At some some point point,, the mixture mixtur e ha has to be dis di scha charge rged d from fr om the th e mi mixe xerr i nt nto o a conve conveye yer, r, a large largerr mi xe xer, r, a table tabl et pres press s, etc. Expe Experr iments were run th that at compared compared the mea measured vari varia ancein the blende blenderr (i (in n si si tu) to tha t hatt in a container container tha t hatt colle coll ected th the e di dis scha charr ged mater mater i al from f rom t he bl ble ender. Tw Two o mixmi xture tur es we were use used: a 50/ 50/ 50 mixture mixt ure of 45 4500-m of sand of two colcolors and and a 3% 3% mixture mi xture of sodium ch chlor loride ide with 96 96% % micromi crocrystallii ne ce crystall cel lu lull os ose e and and 1% mag m agnes nesii um stea tearr ate ate.. Figur Figure e 10 shows th the e res resul ultt s of sampl mplii ng the blender blender before dischargin discharging g and then sampling the discharged matter in a bucket for both mixtu mi xtures res.. For t he cohe cohes si ve salt mi m i xt xtur ure e, di dis scha chargi rging ng into in to a se secondary container had a mixing effect and the RSD declined. For th the e sa sand mi mixt xtur ure e howeve however, r, th the e RS RSD i ncrea ncreas sed slightl sli ghtly y afte aft er the mixture was discharged. Logicalllly Logica y, th the ere is lilitt ttle le appare apparent nt re r eason for th the e mi mixt xture ure to se separate when when di discha charrged unl unle ess the mixt mi xtur ure e had had strong str ong se segreg gregati ation on tendencies,, whi tendencies which ch was wasnot the ca cas se. Exa Exami mini ning ng the diff diffe erence be be-tween twee n radi dia al and axi xia al va varriance nces s for the sand mixt mi xtur ure e gives givessome 8 4
Pharmaceutical Technology MAY 2004
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10.. S.S. Wiedenba 10 nbaum, um,““ Mi xing of Solids in a Twin Twin She hellll Ble Blende nder, r,”” C Ce eramic Age(Augus (August) t),, 39 39–43 –43 (1963). (1963). 11.. O. 11 O.S Sudah, udah,D. D.Coffi Coffin-Be n-Beac ach, h, and F.J. Muzzio,“ Qua Quanti nti tative Cha Characte racterrization of Mi xing of Free-Flowing Granular Granular Materi Materi als in Tote (Bin) Blenders,” P Powde owder Tec Technol. hnol. 126(2), 19 191–2 1–200 00 (2002). (2002). 12.. O. 12 O.S Sudah, udah,D. D. Coffi Coffin-Be n-Beac ach, h, and F.J. Muzzio,“ Eff ffe ects of Ble Blender nder Rotati onal Speed and and Di Dis scha charge rge on the t he Homogeneit Homogeneit y of Cohe Cohes sive and FreeFlowing Mi xtur xture es,” I nt. J. Pharma. 247(1, 2), 57 57–68 –68 (2002 (2002). ). 13.. O. 13 O.S Sudah et al.,“ al., “ Mi xing of Cohesive Pharmac rmace euti ca call Formulations in
Figure 12: For a top-to-bottom loading in a bin- blender blender,, the initial radial concentrations concentrations are not equivale equivalent. nt. At position position 1, the mixture is mostly blue, at position position 2, it is equivalently equivalently blue and and red, and at position 3 it is mostly red.
Conclusi onclusion on Bin blenders continue to play an increasingly important role i n the th e proce proces ssin ing g of of granular and and powdered powdered materi materia als. The dea de art h of spe pecifi cific c informa infor matition on about about the perf rformanc ormance e of bin blenders (and other tumbli t umbling ng blende blenders) rs) makes makes it im import porta ant to determi de termine ne the pe perf rform orma anceof th the ese de devi vice ces i n a vari vari ety of processing situations. I n thi t his sartiticle, cle,th the e basic appr approa oache ches sto gather gatherin ing g and and analyzi analyzing ng perfor perf ormance mancedata havebeen addre addr essed along along wit wi th a sum summar mary y of bas ba sic operatitional onal guidelines guideli nesboth in i n te terms of blende blenderr parameters parameters and mixt mi xtur ure e type ypes s. An exampl example e of mi mixi xing ng analys analysiis hasbe bee en pre pr esent nte ed and the the effffe ects of di dis schargehavebeen dis di scus cuss sed, alon along g with wit h some ca cauti utiona onarr y infor i nforma matition on about about mixt mixture ure sa sampli mpling. ng.The The next next two article arti cles s in thi this s seri rie es wil willl de des scribe, cribe,in in de detail tail,, bin ble blende nderr pe perrformance using free-flowing and cohesive materials.
References 1. J. Ada Adams ms and A. Ba Bake ker, r,“An “An Assessme ment nt of Dr Dry y Blendin Blending g Equipment,” Equipment,” Trans Tr ansac actitions onsof theI nsti nstituti tution on of Chem Chemii cal Engine Engi nee ers 34, 91– 91–107 107 (1956). (1956). 2. J.T. .T.Ca Carste rstens nse en and M.R. Pate atel,l, “ Ble Blendin nding g of Ir reg regularl ularly y Shaped ParParticles,” P Powde owder Tec Technol. hnol. 17, 273– 273–282 282 (1977). 3. N. Ha Harnby rnby,, “A Compa Compariso rison n of the Performanc rformance e of of Indus Industri tri al Solids Solids Mixers Using Segregating Materials,” P Powde owder Tec Technol. hnol. 1, 94–10 94–102 2 (1967). 4. Z.T Z.T.. Cho Chowha whan n and and E.E E.E.. Linn, “ Mi xing of Pha harmac rmace euti utica cal Solids Solids I: Effect of Parti cle Size on Mix M ixin ing g in Cylindr Cyli ndrii cal Shea Shear and V-Shape V-Shaped d Tum Powde owder Tec Technol. hnol. 24, 237 bling Mixers,” P 237–244 –244 (1979). 5. A. A.Ka Kaufma ufman,“ n,“ Mixing of Solids olids,,” I nd nd.. Eng. Eng.Che Chem. Fun Fund d. 1, 104–10 –106 6(196 ( 1962). 2). 6. J.C. Samyn and and K.S. K.S. Mur thy, thy,““ Expe xperi ri ments in Powde Powderr Blending and and Unblending,” J. Pha P harm. rm. Sci. 63(3), 370 370–37 –373 3 (19 ( 1974). 74). 7. D. Brone, A. Ale Alexa xande nder, r, and F.J. Muzz Muzzio, io, “QuantitativeCharac Characteriza terizati on of Mi xing of Dr Dry y Powders in V-Blenders,” A AII ChE Journa Journall 44(2), 271–278 (1998). 8. D.Brone D. Brone and F. Muzzio,“ Enhanced Mixin Mi xing g in Double-Cone Dou ble-ConeBle Blenders nders,,” Powder Tec Technol. hnol. 110(3), 17 179–1 9–189 89 (2000). (2000). 9. D.S. Ca Cahn, hn, T.W T.W.. Healy, and D.W D.W.. Fuerste rstenau,“ nau,“ Ble Blendin nding g Geome ometr tr y in the Mixing Mixi ng of Soli olids ds,,” I nd nd.. Eng. Chem Chem. PD& PD & D 4, 318– 318–322 322 (1965). 8 6
Pharmaceutical Technology MAY 2004
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