937 resultados para Process control -- Statistical methods


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En este artículo abordamos el uso y la importancia de las herramientas estadísticas que se utilizan principalmente en los estudios médicos del ámbito de la oncología y la hematología, pero aplicables a muchos otros campos tanto médicos como experimentales o industriales. El objetivo del presente trabajo es presentar de una manera clara y precisa la metodología estadística necesaria para analizar los datos obtenidos en los estudios rigurosa y concisamente en cuanto a las hipótesis de trabajo planteadas por los investigadores. La medida de la respuesta al tratamiento elegidas en al tipo de estudio elegido determinarán los métodos estadísticos que se utilizarán durante el análisis de los datos del estudio y también el tamaño de muestra. Mediante la correcta aplicación del análisis estadístico y de una adecuada planificación se puede determinar si la relación encontrada entre la exposición a un tratamiento y un resultado es casual o por el contrario, está sujeto a una relación no aleatoria que podría establecer una relación de causalidad. Hemos estudiado los principales tipos de diseño de los estudios médicos más utilizados, tales como ensayos clínicos y estudios observacionales (cohortes, casos y controles, estudios de prevalencia y estudios ecológicos). También se presenta una sección sobre el cálculo del tamaño muestral de los estudios y cómo calcularlo, ¿Qué prueba estadística debe utilizarse?, los aspectos sobre fuerza del efecto ¿odds ratio¿ (OR) y riesgo relativo (RR), el análisis de supervivencia. Se presentan ejemplos en la mayoría de secciones del artículo y bibliografía más relevante.

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Background: Molecular tools may help to uncover closely related and still diverging species from a wide variety of taxa and provide insight into the mechanisms, pace and geography of marine speciation. There is a certain controversy on the phylogeography and speciation modes of species-groups with an Eastern Atlantic-Western Indian Ocean distribution, with previous studies suggesting that older events (Miocene) and/or more recent (Pleistocene) oceanographic processes could have influenced the phylogeny of marine taxa. The spiny lobster genus Palinurus allows for testing among speciation hypotheses, since it has a particular distribution with two groups of three species each in the Northeastern Atlantic (P. elephas, P. mauritanicus and P. charlestoni) and Southeastern Atlantic and Southwestern Indian Oceans (P. gilchristi, P. delagoae and P. barbarae). In the present study, we obtain a more complete understanding of the phylogenetic relationships among these species through a combined dataset with both nuclear and mitochondrial markers, by testing alternative hypotheses on both the mutation rate and tree topology under the recently developed approximate Bayesian computation (ABC) methods. Results Our analyses support a North-to-South speciation pattern in Palinurus with all the South-African species forming a monophyletic clade nested within the Northern Hemisphere species. Coalescent-based ABC methods allowed us to reject the previously proposed hypothesis of a Middle Miocene speciation event related with the closure of the Tethyan Seaway. Instead, divergence times obtained for Palinurus species using the combined mtDNA-microsatellite dataset and standard mutation rates for mtDNA agree with known glaciation-related processes occurring during the last 2 my. Conclusion The Palinurus speciation pattern is a typical example of a series of rapid speciation events occurring within a group, with very short branches separating different species. Our results support the hypothesis that recent climate change-related oceanographic processes have influenced the phylogeny of marine taxa, with most Palinurus species originating during the last two million years. The present study highlights the value of new coalescent-based statistical methods such as ABC for testing different speciation hypotheses using molecular data.

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The present study explores the statistical properties of a randomization test based on the random assignment of the intervention point in a two-phase (AB) single-case design. The focus is on randomization distributions constructed with the values of the test statistic for all possible random assignments and used to obtain p-values. The shape of those distributions is investigated for each specific data division defined by the moment in which the intervention is introduced. Another aim of the study consisted in testing the detection of inexistent effects (i.e., production of false alarms) in autocorrelated data series, in which the assumption of exchangeability between observations may be untenable. In this way, it was possible to compare nominal and empirical Type I error rates in order to obtain evidence on the statistical validity of the randomization test for each individual data division. The results suggest that when either of the two phases has considerably less measurement times, Type I errors may be too probable and, hence, the decision making process to be carried out by applied researchers may be jeopardized.

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The present work focuses the attention on the skew-symmetry index as a measure of social reciprocity. This index is based on the correspondence between the amount of behaviour that each individual addresses to its partners and what it receives from them in return. Although the skew-symmetry index enables researchers to describe social groups, statistical inferential tests are required. The main aim of the present study is to propose an overall statistical technique for testing symmetry in experimental conditions, calculating the skew-symmetry statistic (Φ) at group level. Sampling distributions for the skew- symmetry statistic have been estimated by means of a Monte Carlo simulation in order to allow researchers to make statistical decisions. Furthermore, this study will allow researchers to choose the optimal experimental conditions for carrying out their research, as the power of the statistical test has been estimated. This statistical test could be used in experimental social psychology studies in which researchers may control the group size and the number of interactions within dyads.

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Quality management concrete allows the contractor to develop the mix design for the portland cement concrete. This research was initiated to gain knowledge about contractor mix designs. An experiment was done to determine the variation in cylinders, beams, and cores that could be used to test the strength of the contractor's mix. In addition, the contractor's cylinder strengths and gradations were analyzed for statistical stability and process capability. This research supports the following conclusions: (1) The mold type used to cast the concrete cylinders had an effect on the compressive strength of the concrete. The 4.5-in. by 9-in. (11.43-cm by 22.86-cm) cylinders had lower strength at a 95% confidence interval than the 4-in. by 8-in. (10.16-cm by 20.32-cm) and 6-in. by 12-in. (15.24-cm by 30.48-cm) cylinders. (2) The low vibration consolidation effort had the lowest strength of the three consolidation efforts. In particular, an interaction occurred between the low vibration effort and the 4.5-in. by 9-in. (11.43-cm by 22.86-cm) mold. This interaction produced very low compressive strengths when compared with the other consolidation efforts. (3) A correlation of 0.64 R-squared was found between the 28 day cylinder and 28 day compressive strengths. (4) The compressive strength results of the process control testing were not in statistical control. The aggregate gradations were mostly in statistical control. The gradation process was capable of meeting specification requirements. However, many of the sieves were off target. (5) The fineness modulus of the aggregate gradations did not correlate well with the strength of the concrete. However, this is not surprising considering that the gradation tests and the strength tests did not represent the same material. In addition, the concrete still has many other variables that will affect its strength that were not controlled.

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It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

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BACKGROUND: We assessed the impact of a multicomponent worksite health promotion program for0 reducing cardiovascular risk factors (CVRF) with short intervention, adjusting for regression towards the mean (RTM) affecting such nonexperimental study without control group. METHODS: A cohort of 4,198 workers (aged 42 +/- 10 years, range 16-76 years, 27% women) were analyzed at 3.7-year interval and stratified by each CVRF risk category (low/medium/high blood pressure [BP], total cholesterol [TC], body mass index [BMI], and smoking) with RTM and secular trend adjustments. Intervention consisted of 15 min CVRF screening and individualized counseling by health professionals to medium- and high-risk individuals, with eventual physician referral. RESULTS: High-risk groups participants improved diastolic BP (-3.4 mm Hg [95%CI: -5.1, -1.7]) in 190 hypertensive patients, TC (-0.58 mmol/l [-0.71, -0.44]) in 693 hypercholesterolemic patients, and smoking (-3.1 cig/day [-3.9, -2.3]) in 808 smokers, while systolic BP changes reflected RTM. Low-risk individuals without counseling deteriorated TC and BMI. Body weight increased uniformly in all risk groups (+0.35 kg/year). CONCLUSIONS: In real-world conditions, short intervention program participants in high-risk groups for diastolic BP, TC, and smoking improved their CVRF, whereas low-risk TC and BMI groups deteriorated. Future programs may include specific advises to low-risk groups to maintain a favorable CVRF profile.

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Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

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We present in this paper the results of the application of several visual methods on a group of locations, dated between VI and I centuries BC, of the ager Tarraconensis (Tarragona, Spain) a Hinterland of the roman colony of Tarraco. The difficulty in interpreting the diverse results in a combined way has been resolved by means of the use of statistical methods, such as Principal Components Analysis (PCA) and K-means clustering analysis. These methods have allowed us to carry out site classifications in function of the landscape's visual structure that contains them and of the visual relationships that could be given among them.

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Verkkovaihtosuuntaajalla pystytään muuntamaan tasajännite vaihtojännitteeksi ja päinvastoin. Verkkovaihtosuuntaajan toiminta perustuu tehokytkinten ohjaukseen ja sopivan modulointimenetelmän käyttöön. Vektorisäädössä vaihtosuuntaajanvirrat ja jännitteet esitetään kompleksitasossa, jolloin virta- ja jännitekomponentit voidaan esittää vektoreina. Vektorisäädössä verkkovaihtosuuntaajan ohjaustoteutetaan laskemalla kompleksitasossa vektoreille arvot, jotka tuottavat vaihtosuuntaajan lähtöön halutun vektorin. Koska FPGA-piirit mahdollistavat nopean rinnakkaisen laskennan, soveltuvat ne hyvin vektorisäädön toteuttamiseen. FPGA-piirien rakenteesta johtuen on säätöjärjestelmän suunnittelussa huomioitava kiinteän pilkun lukujen riittävä bittileveys ja järjestelmän diskretointiaika. Työssä suunnitellaan verkkovaihtosuuntaajan vektorisäätö ja tutkitaan bittileveyden vaikutusta säädön toteuttamiseen FPGA-piirillä. Bittileveyden tarkasteluun esitetään käytettäväksi tilastollisia menetelmiä. Työssä tarkastellaan kiinteän pilkun järjestelmän ja liukulukujärjestelmän erosuureen tilastollisia tunnusmerkkejä sekä histogrammia. Tarkasteluissa huomattiin, että maksimivirhe itsessään ei tarjoa riittävästi tietoa erosuureen jakautumisesta. Näin ollen maksimivirhe ei ole kaikissa tilanteissa sovelias menetelmä riittävän bittitarkkuuden määrittämiseen. Työssä esitetään riittävän bittitarkkuuden määrittelemiseen käytettäväksi otossuureista otosvarianssia, keskipoikkeamaa ja vaihteluväliä.

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Työn tavoitteena oli pienentää kuorinnassa syntyviä puuhäviöitä ja parantaa linjan käytettävyyttä nykyaikaisella puunkuorimolla. Tavoitteet toteutettiin automaatiojärjestelmään tehdyillä muutoksilla. Rumpukuorintaprosessi on säilynyt pitkään samanlaisena. Viime vuosina on markkinoille tullut uusia älykkäitä mittalaitteita ja optimointiin kykeneviä säätöjärjestelmiä. Uudenlaisella automaatiotekniikalla on mahdollista mitata kuorintatulosta ja kuorinnassa syntyneitä puuhäviöitä reaaliaikaisesti. Laaduntarkkailun lisäksi tietoja hyödynnetään kuorintaprosessin automaattisessa ohjauksessa. Optimaalisen kuorintatuloksen saavuttaminen edellyttää virheetöntä automaation toimintaa ja tarkkaa viritystä säädöiltä. Työssä perehdyttiin kuorimon perusautomaatioon ja ylemmän tason säädön toimintaan. Prosessinohjauksessa havaitut ongelmakohdat korjattiin. Lopputuloksena saatiin vakiokuorintatehon malli, joka pienentää puuhäviöitä ja parantaa linjaston käytettävyyttä. Saaduilla tuloksilla on merkittävä taloudellinen arvo, ja menetelmät ovat hyödynnettävissä myös toisilla rumpukuorimoilla.

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To enable a mathematically and physically sound execution of the fatigue test and a correct interpretation of its results, statistical evaluation methods are used to assist in the analysis of fatigue testing data. The main objective of this work is to develop step-by-stepinstructions for statistical analysis of the laboratory fatigue data. The scopeof this project is to provide practical cases about answering the several questions raised in the treatment of test data with application of the methods and formulae in the document IIW-XIII-2138-06 (Best Practice Guide on the Statistical Analysis of Fatigue Data). Generally, the questions in the data sheets involve some aspects: estimation of necessary sample size, verification of the statistical equivalence of the collated sets of data, and determination of characteristic curves in different cases. The series of comprehensive examples which are given in this thesis serve as a demonstration of the various statistical methods to develop a sound procedure to create reliable calculation rules for the fatigue analysis.

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Paperin pinnan karheus on yksi paperin laatukriteereistä. Sitä mitataan fyysisestipaperin pintaa mittaavien laitteiden ja optisten laitteiden avulla. Mittaukset vaativat laboratorioolosuhteita, mutta nopeammille, suoraan linjalla tapahtuville mittauksilla olisi tarvetta paperiteollisuudessa. Paperin pinnan karheus voidaan ilmaista yhtenä näytteelle kohdistuvana karheusarvona. Tässä työssä näyte on jaettu merkitseviin alueisiin, ja jokaiselle alueelle on laskettu erillinen karheusarvo. Karheuden mittaukseen on käytetty useita menetelmiä. Yleisesti hyväksyttyä tilastollista menetelmää on käytetty tässä työssä etäisyysmuunnoksen lisäksi. Paperin pinnan karheudenmittauksessa on ollut tarvetta jakaa analysoitava näyte karheuden perusteella alueisiin. Aluejaon avulla voidaan rajata näytteestä selvästi karheampana esiintyvät alueet. Etäisyysmuunnos tuottaa alueita, joita on analysoitu. Näistä alueista on muodostettu yhtenäisiä alueita erilaisilla segmentointimenetelmillä. PNN -menetelmään (Pairwise Nearest Neighbor) ja naapurialueiden yhdistämiseen perustuvia algoritmeja on käytetty.Alueiden jakamiseen ja yhdistämiseen perustuvaa lähestymistapaa on myös tarkasteltu. Segmentoitujen kuvien validointi on yleensä tapahtunut ihmisen tarkastelemana. Tämän työn lähestymistapa on verrata yleisesti hyväksyttyä tilastollista menetelmää segmentoinnin tuloksiin. Korkea korrelaatio näiden tulosten välillä osoittaa onnistunutta segmentointia. Eri kokeiden tuloksia on verrattu keskenään hypoteesin testauksella. Työssä on analysoitu kahta näytesarjaa, joidenmittaukset on suoritettu OptiTopolla ja profilometrillä. Etäisyysmuunnoksen aloitusparametrit, joita muutettiin kokeiden aikana, olivat aloituspisteiden määrä ja sijainti. Samat parametrimuutokset tehtiin kaikille algoritmeille, joita käytettiin alueiden yhdistämiseen. Etäisyysmuunnoksen jälkeen korrelaatio oli voimakkaampaa profilometrillä mitatuille näytteille kuin OptiTopolla mitatuille näytteille. Segmentoiduilla OptiTopo -näytteillä korrelaatio parantui voimakkaammin kuin profilometrinäytteillä. PNN -menetelmän tuottamilla tuloksilla korrelaatio oli paras.

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Tutkielman tarkoituksena on tutkia oppimisprosessin muodostumista ja toteutumista sekä prosessijohtamisen ja prosessien roolia SAP:in käyttöönottoprojektissa. Tutkielman case-organisaationa toimii Kespro Oy ja tutkimuskohteena on SAP:in käyttöönottoprojekti Kespron tukuissa. Tutkimus- ja tiedonkeruumenetelmänä käytetään kvantitatiivista kyselylomaketta. Tutkimuksessa saatiin selkeä kuva prosessijohtamisen ja prosessien roolista muutostilanteessa sekä oppimisprosessin muodostumisesta jatoteutumisesta. Johdon ja esimiesten tuen korostuminen sekä onnistunut strategisten linjausten tiedottaminen tulivat esille käytännön työssä prosessien toimivuuden ja oman työn merkityksen kautta. Tärkeänä haasteena osaamisen varmistamiseksi käyttöönoton yhteydessä oli varmistaa koulutuksen ja käyttäjäohjeiden riittävä taso ja sisältö. Käyttöönoton aikana ja sen jälkeen korostuivat tiedon jakamisessa pääkäyttäjien ja henkilöstön keskinäinen yhteistyö ja avunanto. Tehokas tiedon jakaminen mahdollisti käyttöönoton onnistumisen. Käyttöönottoon vaikutti oleellisesti myös tietotekninen näkökulma: käyttäjien kyky erottaa toisistaan oma osaaminen ja tietotekniset ongelmat. Näiden tekijöiden huomioiminen mahdollisti SAP-toiminnanohjausjärjestelmän sujuvan liikkeellelähdön Kespron tukuissa mahdollisimman vähillä operatiivisilla ongelmilla.

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Concerning process control of batch cooling crystallization the present work focused on the cooling profile and seeding technique. Secondly, the influence of additives on batch-wise precipitation process was investigated. Moreover, a Computational Fluid Dynamics (CFD) model for simulation of controlled batch cooling crystallization was developed. A novel cooling model to control supersaturation level during batch-wise cooling crystallization was introduced. The crystallization kinetics together with operating conditions, i.e. seed loading, cooling rate and batch time, were taken into account in the model. Especially, the supersaturation- and suspension density- dependent secondary nucleation was included in the model. The interaction between the operating conditions and their influence on the control target, i.e. the constant level of supersaturation, were studied with the aid of a numerical solution for the cooling model. Further, the batch cooling crystallization was simulated with the ideal mixing model and CFD model. The moment transformation of the population balance, together with the mass and heat balances, were solved numerically in the simulation. In order to clarify a relationship betweenthe operating conditions and product sizes, a system chart was developed for anideal mixing condition. The utilization of the system chart to determine the appropriate operating condition to meet a required product size was introduced. With CFD simulation, batch crystallization, operated following a specified coolingmode, was studied in the crystallizers having different geometries and scales. The introduced cooling model and simulation results were verified experimentallyfor potassium dihydrogen phosphate (KDP) and the novelties of the proposed control policies were demonstrated using potassium sulfate by comparing with the published results in the literature. The study on the batch-wise precipitation showed that immiscible additives could promote the agglomeration of a derivative of benzoic acid, which facilitated the filterability of the crystal product.