Multi-Criterion Assessment of Different Variants of Casts Manufacturing Processes

Open access

Abstract

The paper presents the issue of production processes improvement in foundries in the area of finishing treatment of iron casts manufactured on automated foundry lines with vertical or horizontal mould division. Due to numerous factors which influence the efficiency of the processes, multi-criterion assessment tools were proposed in order to select the optimal solution for the assumed criteria. After determining the criteria weight using the Saaty method, a simulation experiment was designed and carried out which presents possible scenarios of casts finishing treatment operations. Basing on experiment reports from a computer model, particular solutions were evaluated using the Yager's method. The evaluation of the experiment results was performed by experts who assessed different options according to each of the criteria adopted. After the establishment of the total standardized ratings by averaging the scores given by individual experts, the final decision was generated. Using the presented method, the best solution was chosen from among the analyzed scenarios.

[1] Knosala, R., Boratyńska-Sala, A., Jurczyk-Bunkowska, M., Moczała, A. (2014). Innovation management. Warszawa: Polish Economic Publishing House. (in Polish).

[2] Szymszal, J., Lis, T., Przondziono, J., Nowacki, K. & Kliś, J. (2013). Optimising a model of minimum stock level control and a model of standing order cycle in selected foundry plant. Archives of Foundry Engineering. 13(3), 97-100.

[3] Plinta, D., Kukla, S. (2004). Optimisation methods in the modelling and simulation of production systems. In 7th IFAC Symposium on Cost Oriented Automation, International Federation of Automatic Control. Canada, Quebec. (pp. 291-294).

[4] Whittington, R. (2014). CPAexcel Exam Review 2014 Study Guide, Business Environment and Concepts. New Jersey: John Wiley & Sons.

[5] Kukla, S. (2010). Production systems rationalisation on the example of iron foundry. Archives of Foundry Engineering. 10(2), 209-212.

[6] Panneerselvam, R. (2013). Engineering economics. Delhi: PHI Learning Pvt.

[7] Lanza, R.B. (2009). Cost recovery. New Jersey: John Wiley & Sons.

[8] Matuszek, J. & Kukla, S. (2009). Analysis of foundry production systems on the basis of modelling and simulation. Acta Mechanica Slovacia. 13(2), 106-111.

[9] Bangsow, S. (2012). Use Cases of Discrete Event Simulation: Appliance and Research. Berlin: Springer-Verlag.

[10] Maciąg, A., Piertroń, R., Kukla, S. (2013). Forecasting and simulation in enterprise. Warszawa: Polish Economic Publishing House. (in Polish).

[11] Zadeh, L., Kacprzyk, J. (1992). Fuzzy logic for the management of uncertainty. New York: John Wiley & Sons.

[12] Ciszak, O. (2012). Computer aided determination of the assembly sequence of machine parts and sets. Advances in Engineering Software. 48, 17-26.

[13] Massanet, S. & Torrens, J. (2012). On the characterization of Yager's implications. Information Sciences. 201, 1-18.

[14] Saaty, T. (1980). The Analytic hierarchy processes. New York: McGraw – Hill.

Archives of Foundry Engineering

The Journal of Polish Academy of Sciences

Journal Information


CiteScore 2016: 0.42

SCImago Journal Rank (SJR) 2016: 0.192
Source Normalized Impact per Paper (SNIP) 2016: 0.316

Cited By

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 146 144 7
PDF Downloads 43 42 3