Overview in PDF format - Tallinna TehnikaÃ¼likool

More documents

Recommendations

Info

• And last but not least, the most erroneous part of technological systems –human resource – should be made measurable, improving factor conditions ofPorter’s Competitive Diamond Model (Fig. 1).Figure 1.2 Porter’s Competitive Diamond Model: determinants of regional productivity(Porter 1990)The four attributes (1. Factor conditions, 2. Demand conditions, 3. Context forfirm strategy and rivalry, 4. Related and supporting industries) are self-reinforcingand catalyse the process of continuous innovations. The model focuses upon theconditions that support firm competitiveness at the national scale. In a study ofEstonia in transition Porter shows that the quality and efficiency of Estonianworkers was regarded by many as ahead of Finland, known for its hard-workingculture. However, Estonia was experiencing a shortage of highly qualified labor(Porter, 2006).To solve the tasks data flows are modelled for MU by using direct and indirectmeasuring techniques. Verification of models is investigated using UppAal modelchecking tool. Possibilities of model checking can be used for searching in webbasedinter-organizational resource and knowledge databases to find cost-effectivemanufacturing solutions for new products developing. In addition to locatingtechnical production and logistic capabilities such system can also includeknowledge requirement parameters based on database information. To solve the14
Porter’s Diamond Model task an online system of technological and humanresources is proposed. The most erroneous part of technological systems – humanresource – is analysed on the basis of competence, thus making it possible toelaborate a methodology for evaluation and development of the database model foradding innovation capacity of labour force and entrepreneurs of the metalengineering, machinery and apparatus sector.1.4. LimitationsThough the current solution is focused on the sector of metalworking, machineryand apparatus engineering the proposed methodology can be transferred also toother industrial sectors (wood processing, chemical industry, construction materialsindustry, etc).On the process level machining processes, especially metal turning and grinding,as examples, are discussed in more detail. Cutting process changes constantly dueto tool wear, and therefore cannot be considered time-invariable. Typical wearcriteria are the average wear land width and the maximum wear land width. Usingthese criteria it is possible to evaluate the average and maximum intensity of wearand implement these data in mathematical models predicting tool life. When itcomes to the analysis of tool wear, it is recognised that the flank wear is of primeconcern, so that all tool life testing has primarily considered this wear (Astakhov,1999). Knowledge of tool wear is used for modelling the process, validating themodel, and implementing it into the technological resources network.As to the human resource evaluation only most widely known engineeringprofessions of the machinery sector have been studied. A demo system module wasdeveloped in order to map different aspects of qualifications (general skills andknowledge, specific skills and knowledge, personal qualities, etc) and also tested inselected companies.The realisation of the Porter’s Competitive Diamond Model enhancement islimited to one branch – factor conditions.In building the application only freeware was used (Apache server, MySQLdatabase, UppAal toolbox). However, this realisation does not limit the applicabilityof the proposed model and can also be implemented with another piece of freewareor commercially available software (e.g. Oracle).15
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: database by a query; c. Search of t
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 and 38: Figure 3.3 A snapshot of Uppaal mod
Page 39 and 40: Figure 3.5 FMS at TUTM9M8M4M1M2M7M5
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
show all

Overview in PDF format - Tallinna TehnikaÃ¼likool

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?