There are several manufacturing errors of different criticality, severity, and occurrence. Correcting all of them is difficult and costly. In this paper, we propose a new hybrid approach to classifying manufacturing errors in an automotive plant and, consequently, to selecting the portfolio of processes that require more attention from the management of the company. Our approach consists of two steps. Firstly, we classify the errors in terms of priority, based on a set of criteria agreed with the management, using the multi-criteria decision-aiding method AHPSort II. The errors belonging to the highest priority class are the most urgent and critical for the company. Secondly, we define a multi-objective portfolio problem, selecting a set of the most critical processes based on the number of errors in each of these processes and on their priority. We adopted an interactive method for finding the most preferred portfolio of processes according to the stakeholder preferences. We applied this approach to a case study of the largest automotive company in Italy, Fiat Chrysler Automobiles, showing how classical quality control tools can benefit from the integration of multi-criteria decision-aiding techniques.

A hybrid AHPSort II and multi-objective portfolio selection method to support quality control in the automotive industry

Gerarda Fattoruso
;
2022-01-01

Abstract

There are several manufacturing errors of different criticality, severity, and occurrence. Correcting all of them is difficult and costly. In this paper, we propose a new hybrid approach to classifying manufacturing errors in an automotive plant and, consequently, to selecting the portfolio of processes that require more attention from the management of the company. Our approach consists of two steps. Firstly, we classify the errors in terms of priority, based on a set of criteria agreed with the management, using the multi-criteria decision-aiding method AHPSort II. The errors belonging to the highest priority class are the most urgent and critical for the company. Secondly, we define a multi-objective portfolio problem, selecting a set of the most critical processes based on the number of errors in each of these processes and on their priority. We adopted an interactive method for finding the most preferred portfolio of processes according to the stakeholder preferences. We applied this approach to a case study of the largest automotive company in Italy, Fiat Chrysler Automobiles, showing how classical quality control tools can benefit from the integration of multi-criteria decision-aiding techniques.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/444429
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