Abstract
PurposeNowadays, companies are increasingly adopting additive manufacturing (AM) technologies due to their flexibility and product customization, combined with non-dramatic increases in per unit cost. Moreover, many companies deploy a plurality of distributed AM centers to enhance flexibility and customer proximity. Although AM centers are characterized by similar equipment and working methods, their production mix and volumes may be variable. The purpose of this paper is to propose a novel methodology to (1) monitor the quality of the production of individual AM centers and (2) perform a benchmarking of different AM centers.Design/methodology/approachThis paper analyzes the quality of the production output of AM centers in terms of compliance with specifications. Quality is assessed through a multivariate statistical analysis of measurement data concerning several geometric quality characteristics. A novel operational methodology is suggested to estimate the fraction nonconforming of each AM center at three different levels: (1) overall production, (2) individual product typologies in the production mix and (3) individual quality characteristics.FindingsThe proposed methodology allows performing a benchmark analysis on the quality performance of distributed AM centers during regular production, without requiring any ad hoc experimental test.Originality/valueThis research assesses the capability of distributed AM centers to meet crucial quality requirements. The results can guide production managers toward improving the quality of the production of AM centers, in order to meet customer expectations and enhance business performance.
Subject
Strategy and Management,General Business, Management and Accounting
Reference35 articles.
1. Evaluation of process capability in gamma regression profiles;Communications in Statistics-Simulation and Computation,2020
2. Capability measures for processes with multiple characteristics;Quality and Reliability Engineering International,2003
3. Exploratory case studies on manufacturing decision areas in the job production system;International Journal of Operations and Production Management,2012
4. A review of univariate and multivariate process capability indices;The International Journal of Advanced Manufacturing Technology,2017
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