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
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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