Augmenting measure sensitivity to detect essential, dispensable and highly incompatible features in mass customization
Autor: | Mauricio Alférez, Hector Perez-Morago, David Fernandez-Amoros, Ruben Heradio, Germán H. Alférez |
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Přispěvatelé: | Universidad Nacional de Educación a Distancia (UNED), Département Ingénierie Logiciels et Systèmes (DILS), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)) |
Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
Information Systems and Management
Computer aided manufacturing General Computer Science Computer science Distributed computing Mass customization Real-time computing Business competition 0211 other engineering and technologies Binary decision diagrams 02 engineering and technology Management Science and Operations Research Industrial and Manufacturing Engineering Service industries Supply and demand Competition (economics) Market demand [SPI]Engineering Sciences [physics] Variability model 0202 electrical engineering electronic engineering information engineering Feature (machine learning) [INFO]Computer Science [cs] Sensitivity (control systems) Tertiary sector of the economy Measure (data warehouse) 021103 operations research Competition business.industry Customer satisfaction 020207 software engineering Modeling and Simulation Product platforms business Lead time Algorithms |
Zdroj: | European Journal of Operational Research European Journal of Operational Research, Elsevier, 2016, 248 (3), pp.1066-1077. ⟨10.1016/j.ejor.2015.08.005⟩ European Journal of Operational Research, 2016, 248 (3), pp.1066-1077. ⟨10.1016/j.ejor.2015.08.005⟩ |
ISSN: | 0377-2217 1872-6860 |
Popis: | International audience; Mass customization is the new frontier in business competition for both manufacturing and service industries. To improve customer satisfaction, reduce lead-times and shorten costs, families of similar products are built jointly by combining reusable parts that implement the features demanded by the customers. To guarantee the validity of the products derived from mass customization processes, feature dependencies and incompatibilities are usually specified with a variability model. As market demand grows and evolves, variability models become increasingly complex. In such entangled models it is hard to identify which features are essential, dispensable, highly required by other features, or highly incompatible with the remaining features. This paper exposes the limitations of existing approaches to gather such knowledge and provides efficient algorithms to retrieve that information from variability models. |
Databáze: | OpenAIRE |
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