A proposal for an operational methodology to assist the ranking-aggregation problem in manufacturing

Author:

Franceschini Fiorenzo1,Maisano Domenico A.1,Mastrogiacomo Luca1

Affiliation:

1. Politecnico di Torino

Abstract

Abstract Ranking aggregation is an ancient problem with some characteristic elements: a number of experts, who individually rank a set of objects according to a certain (subjective) attribute, and the need to aggregate the resulting expert rankings into a collective judgment. Although this problem is traditionally very popular in fields such as social choice, psychometrics, and economics, it can also have several interesting applications in manufacturing, e.g., for customer-oriented design, reliability engineering, production management, etc. Through a case study related to cobot-assisted manual (dis)assembly, the paper illustrates an operational methodology and various useful tools that assist in tackling the problem practically, effectively, and with a critical mind. The most relevant proposed tools assist in estimating the degree of concordanceamong experts, the collective judgment’s consistency and robustness. The paper is aimed at scientists and practitioners in manufacturing.

Publisher

Research Square Platform LLC

Reference37 articles.

1. Agresti, A. (2010). Analysis of Ordinal Categorical Data (2nd ed.), New York: John Wiley & Sons.

2. Arrow K.J. (2012). Social choice and individual values, 3rd edn. Yale University Press, New Haven.

3. Bana e Costa, C.A. (Ed.). (2012). Readings in multiple criteria decision aid. Springer Science & Business Media, Berlin Heidelberg.

4. Blais, A. (Ed.) (2008). To keep or to change first past the post?: the politics of electoral reform. Oxford University Press, Oxford.

5. Borda, J.C. (1781). Mémoire sur les élections au scrutin, Comptes Rendus de l’Académie des Sciences. Translated by Alfred de Grazia as Mathematical derivation of an election system, Isis, 44:42–51.

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