Zen Computer Support and Process Degradation Overview

Obsah pedmtu: Potaov podpora zen Te(r)orie a sestaven degrada n ho procesu P edm t : Po ta ov podpora zen K126 POPR Obor : E ZS, 2014, K126 EKO P edn ky/cvi en : Doc. Ing. P. Dlask, Ph.D. 10/2014 1

Obsah 1. Rekapitulace cvi en 2. Teorie pro modelov n procesu 3. C l lohy 4. P prava dat modelu 5. Sestaven modelu 6. Zkou kov ot zky 7. References 10/2014 2

Rekapitulace lohy v jedin m XLS(X)(M) Odstranit vazbu na data97.xls Nekop rovat zbyte n v ci z data97.xls Vysoko kolsk rove zpracov n Aplikace nov ch znalost p i zpracov n ovl dac prvky, procedury, makra, odkazy, navigace lohy Zkou kov benefit (Izrael, Burza) R zn aplikace pr tok eky, v kon elektr rny, v kony sportovc , v voj cen Chyb n kladov funkce (slo ka) 10/2014 3

Rekapitulace Pojmenov v n soubor (Liska01.xlsx, Liska01a.xlsx, ) Form tovat s ohledem na rozli en monitoru Navigace v souboru (posuny na grafy, kter jsou mimo desktop) e tina (spelling)! V ce text do text. pole (NE do bun k) Obsah bu ky lze vypsat do textov ho pole 10/2014 4

Rekapitulace Zkou kov benefit pr b n vystoupen v semestru pro z jemce 5-ti minutov rekapitulace Obsah P prava Popis e en Co se poda ilo? Co se nepoda ilo? Kde byl probl m? Co e il? ??? ??? Z v r 10/2014 5

Degradace stavebnho prvku len n technicko-ekonomick ch proces P N S P P , , Procesy kde P PProcesy P evidence odpracovan ch hodin), N mno ina re ln ch n vazn ch proces (nap . innosti prov d n v harmonogramu prac s definovan mi vz jemn mi vazbami), S mno ina pl nov ch proces (nap . sled innost prov d n ch na pracovn lince s prov d n m rozhodov n o kontrole kvality). souhrnn ozna en mno iny v ech proces , mno ina element rn ch proces (nap . v et materi lov ch skupin ve skladu, evidence pracovn k , dic procesy slou pro tvorbu dic ch z sah realizovan ch managementem. Zpracov vaj se na z klad dic ch model odvozen ch z popis re ln skute nosti . P eme 1. 2. Teorie pro modelov n procesu 3. C l lohy 4. 5. 6. Rekapitulace 10/2014 P prava dat modelu Sestaven modelu Zkou kov ot zky 6

Model strnut konstr. prvku 1. Sb r dat pro sestaven modelu 2. Sestaven modelu procesu 3. Navr en po adavk na chov n procesu 4. Navr en dic ch opat en 5. Aplikace zen 6. Ov en a lad n dic ch opat en 1. 2. 3. C l lohy 4. 5. 6. Rekapitulace Teorie pro modelov n procesu 10/2014 P prava dat modelu Sestaven modelu Zkou kov ot zky 7

1. 2. 3. 4.P prava dat modelu 5. Sestaven modelu 6. Zkou kov ot zky Rekapitulace Teorie pro modelov n procesu C l lohy 10/2014 8

Model strnut konstr. prvku 1. 2. 3. 4. P prava dat modelu 5. 6. Rekapitulace Teorie pro modelov n procesu C l lohy 10/2014 Sestaven modelu Zkou kov ot zky Source: Modelling in Excel https://www.youtube.com/watch?v=gNBg_rQQF5s

4 kinds of models Perhaps the simplest type of model to start with is the conceptual model. They are so simple and commonplace that I have already used them while writing this article. In turn, readers like yourself use conceptual models to understand what you read. Conceptual models basically convey meaning and can be pieced together to make sense of a bigger, trickier thing. Accordingly, every single word refers to a thing or an idea and words are joined into clauses to deliver a message. Electronic diagrams are also conceptual models, summarizing how current flows around the various bits of circuitry represented by standard symbols. 1. Conceptual Model 2. In Vivo Model 3. In Vitro Model 4. In Silico Model Beyond conceptual models there are in vivo models, from the Latin for 'live'. These are actual live organisms either in the field or in the laboratory sufficiently similar to real phenomena to be able to give clear results. Examples include the use of live mice to reflect aspects of the human immune system or to test the effects of nutrients or drugs. Despite their utility, in vivo models do have their drawbacks. Concern over their use, for instance regarding animal rights, means great care is now taken to ensure research is ethical. Modeling generally simplies the research process, but researchers using in vivo models take on a large burden of administration, monetary cost, care for organisms and, in some cases, risking their own safety at the hands of activists. Thankfully other types of model are available, so these difficulties can often be overcome. A third type of model is an in vitro model. In vitro is also from Latin, meaning 'in the glass', a phrase made popular by In-Vitro Fertilisation (IVF), where eggs are fertilised outside the body. In vitro models offer conditions outside of those of direct interest, but they are sufficiently similar that comparable processes will occur. An example of this kind of model would be a bionic eye that performs the same basic functions as a real eye, but is built from different materials. Another example would be any chemical reaction involving an isolated enzyme in a way that is far simpler than studying the entire biochemistry of a cell. Both in vivo and in vitro models are limited by the materials that are readily available for research and resources and labour to use them appropriately. Often it is not possible to conduct experiments in as many different systems as one would like and, even if these models are used, they can leave difficult questions unanswered. 10

4 kinds of models This brings us to the fourth and final kind of model. It is perhaps the hardest to comprehend, but has great power and versatility. In silico models refer to simulations using mathematical models in computers, thus relying on silicon chips. In silico models analyse and solve mathematical equations to give results under certain circumstances. These equations summarise relationships between things scientists study. To use these models, it is first necessary to describe the phenomena in question using numbers. Then quantitative relationships can be included in the equation and where these relationships are complex, a computer is necessary to solve them. These often involve some kind of mechanism that changes over time, like mimicking the changing price of a Mars bar from the 1970s to the present day. For this economic model many things need to be speciffied like in nation, supply and demand of sugar and coca etc. The results from this model may not be bang on the actual price of a Mars bar, but the model is useful in revealing what we do know (where the model works and the price is right) and what we don't (where the model fails and the price is wrong). In the same way, all models can fall down on some points, but these revelations are very useful in helping to advance scientific knowledge. 1. Conceptual Model 2. In Vivo Model 3. In Vitro Model 4. In Silico Model 10/2014 11

4 kinds of models - examples 1. Conceptual Model (scheme, chart, electronic diagrams, flow chart) 2. In Vivo Model (the human immune system, test the effects of nutrients or drugs, cell experiments) 3. In Vitro Model (bionic eye, chemical reaction, enzyme isolation, endoprosthetic, hip replacement) 4. In Silico Model (price model, prediction models, simulation model, transport model, population) 10/2014 12

What do we need? In Silico Model: - describe the phenomena in question using numbers, - describe quantitation relationships can be included in the equation, - these relationships are complex, - computer to solve them, - software to solve them, - mimicking the degradation process. revelations are very useful in helping to advance scientific knowledge. 1. 2. 3. 4. 5. Sestaven modelu 6. Zkou kov ot zky Rekapitulace Teorie pro modelov n procesu C l lohy P prava dat modelu 10/2014 13

XLSX model.

Model strnut konstr. prvku I. Bez dr by Bez obnovy Rozpad na 0% Parametry v po tu Popis prvku Technick parametry Po izovac n klady Doba ivotnosti Model st rnut 8000000 K 0 K Roky 0 6 8 10 12 Viz XLS 10/2014 15

Model strnut konstr. prvku II. Bez dr by Bez obnovy Rozpad na 25% 8000000 K 2000000 K 0 K Roky 0 8 10 12 10/2014 16

Model strnut konstr. prvku III. Bez dr by Obnova na max. Rozpad na 25% 8000000 K N klady 2000000 K 0 K Roky 0 8 10 12 10/2014 17

Model strnut konstr. prvku IV. S dr bou Bez obnovy Rozpad na 25% 8000000 K Pravideln dr ba 4000000 K 2000000 K 0 K Roky 0 10 10/2014 18

Model strnut konstr. prvku V. S dr bou S obnovou Rozpad na 25% 8000000 K Pravideln dr ba 4000000 K 2000000 K 0 K Roky 0 10 10/2014 19

Finann bilance drby/obnovy S dr bou S obnovou Rozpad na 25% 8000000 K Pravideln dr ba 4000000 K 2000000 K 0 K Roky 0 10/2014 20

Excel tipy (ExcelTipy.xlsm).

Literatura Beran, V., Dlask, P. Management udr iteln ho rozvoje region , s del a obc . Praha : Academia, 2005, s. 256. Beran, V. a kol. Dynamick harmonogram. Praha : Academia, 2002, s. 172. Dlask, P., Modelov n p i zen . Praha : Wolters Kluwer, 2011, s. 175. Griffiths, E., What is a model?, 2009. Kersten, G., Decision Support Systems for Sustainable Development, A Resource Book of Methods and Applications, Kluwer Academic Edition, 2002. Griffths, E., What is a model?, e.griffiths@shef.ac.uk 10/2014 22

Zvr Z v r Te(r)orie a sestaven degrada n ho procesu Doc. Ing. P. Dlask, Ph.D. 10/2014 23