In the era of the fourth industrial revolution, connected smart factories are expected to efficiently produce a variety of personalized products with small lot size. Therefore, it is necessary to manage new supply chain based on connected smart factories differently from the existing supply chain for mass production. In the new environment, processing time may be not stable and different depending on the factory environment because it produces a small amount of product. In this paper, we propose a distributionally robust optimization model to construct and operate a smart supply chain for personalized production by sharing resources of smart factories within a given lead time at a minimum cost under processing time uncertainty. It overcomes the conservativeness issue of the traditional robust optimization model with box uncertainty set. Simulation experiments demonstrate the outperformance of the proposed model compared to a deterministic model and robust counterpart with box uncertainty set.
|Number of pages||11|
|Publication status||Published - 2018|
|Event||7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018 - Lyon, France|
Duration: 2018 Jul 8 → 2018 Jul 11
|Other||7th International Conference on Information Systems, Logistics and Supply Chain, ILS 2018|
|Period||18/7/8 → 18/7/11|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (NRF-2017R1C1B1008106).
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Hardware and Architecture
- Information Systems