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channels. Let S i denote a state (in the pattern instant T r k) where a work piece beingjust processed by some operation Op l according to a recipe j is waiting forprocessing by Op i . The interoperation states S i are used for modeling transportdelays between different locations where processing takes place.(a)(b)Figure 3.4 Model patterns: (a) a fragment of technological process “recipe”;(b) a fragment of a machining unit performing an operationThe root model M 0 can be simplified considerably by abstraction if generalresource and performance estimation problems must be solved (analysis of phaseP2). If the global performance or resource usage are of interest it is possible toabstract from recipe automata and introduce instead the so-called buffer (or storage)variables to T m models – a pair for each (observable in the model) machiningoperation. Since machining operations share their input and output buffers thevariables modeling buffers are joint for several operations. Thus, the machiningview can be constructed from initial T m patterns using the following rule: if tworecipe automata T r 1 and T r 2 include the same operation Op i , then there are buffervariables R i and R i+1 in the modified T m model such that for all operations precedingimmediately Op i in T m their common output buffer is modeled by the variable R i ,and for all operations of T r 1 and T r 2 following immediately Op i their input buffer ismodeled by variable R i+1 . Denoting the number of work-pieces needed for Op i by I iand the number of products or resources released after completing the operation byO i , the guards and assignments of transitions to and from the state Op i in T m* ( i.e.,t(.,i) and t(i,.)), are defined in the following way: G(t xi ) ≡ R i ≥ I i , Asg(t xi ) ≡ R i – I i ;G(t ix ) ≡ RR ≥ R i+1 + O i , Asg(t ix ) ≡ R i+1 + O i (see Fig. 3.4). The machining viewcompletely preserves the parallelism of machining units and can be used forplanning machine load and throughput.UppAal toolbox is one candidate for performing the model checking task(Rennik, 2005). However, it uses XML files which are not comparable withcorresponding database formats. Therefore in practice the XML output fromdatabase is transformed using Python software based model converter Finke,analysed by UppAal, and thereafter tranferred back by expert system Prolog. Thesuitable Java interface application has been elaborated at TUT (Mäe, 2006).In FMS situated at a laboratory of TUT (Fig. 3.5), several technological devicesare involved, including a Milling CNC machine (M8), Robot «Mentor» (M2),Robot «Serpent» (M7), Load module (M4), Height measurement device (M3),Diameter measurement device (M5), Conveyer 1 (M1), Conveyer 2 (M6), Indexedtable (M9), Operator.In Fig. 3.6 a scheme of FMS is presented, a data model (IDEF0) shown in Fig.3.7 (Karaulova, 2002, 2004) can be received after decomposition stages.38
Figure 3.5 FMS at TUTM9M8M4M1M2M7M5M3M6Figure 3.6 Scheme of FMS and modules decompositionC1 Objects specificationWork parts specificationC2I1Work partsCLADisplacement of theobject fromdispense partoutput to theconveyer 1A1M4Parts DespenserM1Conveyer1M2Robot "Mentor"Object at the onsetof the conveyer 2M3Height GaugeCLAMeasurement andclassifying of theobjectA2M6Conveyer2M5Width GaugeObject atthe end ofconveyer 2DdLdM8CNC MillCLAPlacing andmachining theobject in CNC Mill.Placing the objectonto IndexingTableA3M7Robot "Serpent"M9Indexed TableO1Machined andsorted partsModule 1 Module 2 Module 3Figure 3.7 First level decomposition of the diagram39
Page 1 and 2: THESIS ON MECHANICAL AND INSTRUMENT
Page 3 and 4: MASINA- JA APARAADIEHITUS E283
Page 5 and 6: PREFACEThe mankind of the 21 st cen
Page 7 and 8: Paper I............................
Page 9 and 10: XII. Riives, J., Papstel, J., Otto,
Page 11 and 12: 1. INTRODUCTION1.1. BackgroundManuf
Page 13 and 14: database by a query; c. Search of t
Page 15 and 16: Porter’s Diamond Model task an on
Page 17 and 18: Figure 2.1 Use of modelling in prod
Page 19 and 20: However, it should be noticed that
Page 21 and 22: Figure 2.6 Depth of field/magnifica
Page 23 and 24: 2.3. Prediction of machining accura
Page 25 and 26: uFy=ybsinptyOl 1ulFAϕFigure 2.10 C
Page 27 and 28: is2.5. Dynamical model with two deg
Page 29 and 30: According to de Moivre’s formulaw
Page 31 and 32: constant of the lathe. Figure 2.11
Page 33 and 34: Analogically, test results and resu
Page 35 and 36: Figure 3.1 Model checking in an ope
Page 37: Figure 3.3 A snapshot of Uppaal mod
Page 41 and 42: Turning and milling operations can
Page 43 and 44: 4. MODELS FOR MONITORING THE RESOUR
Page 45 and 46: As assumptions to solve the queries
Page 47 and 48: Regarding co-operation networks the
Page 49 and 50: • The system offers dynamic and u
Page 51 and 52: Figure 4.5 Associations in the Inno
Page 53 and 54: An enterprise-centred mapping and a
Page 55 and 56: Better efficiency and transparency
Page 57 and 58: institutions: in enterprises of div
Page 59 and 60: 1. Tehnoloogiaseadme tasemel on loo
Page 61 and 62: REFERENCESAltintas, Y. (2000). Manu
Page 63 and 64: Russo, M.F. (1999). Automating Scie
Page 65 and 66: Paper IIAryassov, G., Otto, T., Gro
Page 67 and 68: Paper IVOtto, T., Papstel, J., Riiv
Page 69 and 70: ELULOOKIRJELDUS (CV)1. IsikuandmedE
Page 71 and 72: CURRICULUM VITAE (CV)1. Personal da
Page 73 and 74: DISSERTATIONS DEFENDED ATTALLINN UN

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