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Tesi etd-08132012-093459


Thesis type
Tesi di laurea magistrale
Author
ROMEO, DANILO
URN
etd-08132012-093459
Title
Stock-Market Related Pricing Mechanisms for Tool and Mould Manufacturing Industries
Struttura
INGEGNERIA DELL'ENERGIA DEI PROCESSI E DEI SISTEMI
Corso di studi
INGEGNERIA GESTIONALE
Supervisors
tutor Nemeti, Andrea
relatore Prof. Dini, Gino
Parole chiave
  • tool
  • mould
  • pricing
  • costing
  • prediction market
Data inizio appello
26/09/2012;
Consultabilità
Parziale
Data di rilascio
26/09/2052
Riassunto analitico
Tools and industrial moulds are used by industries such as the metal stamping, die-casting and plastics moulding industries to give the final form to the products they manufacture. Manufacturing of tools and moulds influences the entire production of a large number of components, subassemblies and assemblies in many sectors, like motor vehicles, electronics, appliances, packaging. Short lead times, continuous changes in quantity and quality of orders and absence of correct work methods may cause fluctuations up to 40 percent between the pre and post calculation cost (and consequently variation of price). In the lapse of time between customer offer and mould production costs could vary up to 30 %; thus time dynamic costs, such as material cost and labor cost must be expected to reach a correct estimation of final price. A possible solution of the problem of miscalculation depending on disregarding time-dynamic costs is the integration of stock-market related pricing methods in the tool and mould manufacturing industry. Based on the described problems, the focus of this thesis is to establish a method to integrate time-dynamics costs, such as material costs or external labor, in the price estimation of the tool and mould manufacturing industries, to reduce price fluctuations. To forecast time-dynamic costs, furthermore, a method to integrate stock-market related pricing mechanisms in the tool and mould manufacturing industry will be developed. These objectives are based on the idea that the price estimation process could be optimized with the integration of time-dynamics costs and their prediction based on stock-market related mechanisms.
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