LARG SCM

LARG SCM

LARG Supply Chain Management attempts to put together Lean, Agile, Resilient, and Green approaches in Supply Chain Management. Lean Supply Chain Managements aims are to maintain close to zero inventories and reduce work-in-process; Agile goes for quick responses to customer inquiries and market changes while controlling costs and quality; Resilience is about reacting quickly to disruptions impacting supply chain; and Green refers to sustainability in supply chain through low emissions to the environment and a recycling strategy for products.

History

The idea of LARG SCM was developed in the research unit of mechanical and industrial engineering (UNIDEMI) in the Faculty of Science and Technology at New University of Lisbon, Portugal. UNIDEMI is the main research center working on LARG SCM. UNINOVA and NECE are contributing partners.

Overview

A Lean company means nearly zero inventories; a Resilient company must have enough inventory to react to the effects of disruptions that may occur in a supply chain. These concepts seem to be contradictory . However, it would be ideal to have both systems working together in a company.[1] These facts advise for further research in production and supply chain management; Lean and Resilient concepts require to be modeled on a compatibility basis. LARG SCM develops a deep understanding of interrelationships (conflicts and trade-offs[2]) across lean, agile, resilient and green supply chain[3] paradigms. This understanding is believed to be vital to turn these concepts really compatible. This achievement will provide an important contribution for a competitive and sustainable environment; its justification will be based on better “lean, agile, resilient and green production systems” at the company level, with implications at the overall supply chain level and its agents. LARG SCM encompasses a variety of related topics such as methodology, characteristics,[4] organizational system, Performance measurement,[5][6][7] human factors,[8] information system, and management integration model.[9]

References

  1. ↑ Azevedo, Susana G; Carvalho, H; Cruz Machado, V (2010). "The influence of agile and resilient practices on supply chain performance: an innovative conceptual model proposal". HICL2010: Innovative Processes and Solutions in Logistics and SCM, Germany.
  2. ↑ Cruz-Machado, Virgilio; Duarte, S (2010). "Tradeoffs among paradigms in Supply Chain Management". Proceedings of the International Conference on Industrial Engineering and Operations Management, Bangladesh.
  3. ↑ Azevedo, Susana G; Carvalho, H; Cruz Machado, V (2010). "Green Supply Chain Management: A Case Study Analysis of the Automotive Industry". Proceedings of International Conference of Competitive and Sustainable Manufacturing, Products and Services, Italy.
  4. ↑ Carvalho, Helena; Cruz Machado, V (2009). "Lean, agile, resilient and green supply chain: a review". Proceedings of the Third International Conference on Management Science and Engineering Management, Thailand: 3–14.
  5. ↑ Maleki, Meysam; Cruz-Machado, V. (2013). "Supply chain performance monitoring using Bayesian network". International Journal of Business Performance and Supply Chain Modelling 5 (2): 177–197.
  6. ↑ Azevedo, Susana G; Carvalho, H.; Cruz Machado, V. (2011). "A proposal of LARGe Supply Chain Management Practices and a Performance Measurement System". International Journal of e-Education, e-Business, e-Management and e-Learning 1 (1).
  7. ↑ Duarte, Susana; Carvalho, H; Cruz Machado, V (2010). "Exploring relationships between supply chain performance measures". Proceedings of the Fourth International Conference on Management Science and Engineering Management (ICMSEM), China: 91–95.
  8. ↑ Correia, Natacha; Cruz Machado, V; Nunes, I.L (2010). "Strategy in human performance management in lean environment". Proceedings of the Fourth International Conference on Management Science and Engineering Management (ICMSEM), China: 554–557.
  9. ↑ Maleki, Meysam; Cruz Machado, V (2013). "Development of Supply Chain Integration model through application of analytic network process and Bayesian network". International Journal of Integrated Supply Management 8 (1/2/3): 67–89.
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