TY  - JOUR
AB  - Learning behaviors related to quality improvement in manufacturing systems (i.e. reduction of defectiveness over production cycles) are widely investigated. Many different approaches have been introduced to describe the link between the learning mechanism and quality performance of a plant. In a previous study by the same authors, a set of learning “composition laws” for two basic structures were defined to provide a tool to forecast the behavior of complex manufacturing systems composed by a network of elementary processes. This paper presents an empirical investigation about these learning composition laws on a real case in the field of automotive exhaust‐systems manufacturing.
VL  - 15
IS  - 7
SN  - 1741-038X
DO  - 10.1108/17410380410555925
UR  - https://doi.org/10.1108/17410380410555925
AU  - Franceschini Fiorenzo
AU  - Galetto Maurizio
PY  - 2004
Y1  - 2004/01/01
TI  - An empirical investigation of learning curve composition laws for quality improvement in complex manufacturing plants
T2  - Journal of Manufacturing Technology Management
PB  - Emerald Group Publishing Limited
SP  - 687
EP  - 699
Y2  - 2024/04/25
ER  -