A data-driven model with minimal information for bottleneck detection - application at Bosch thermotechnology-Reference-Cited by-同舟云学术

A data-driven model with minimal information for bottleneck detection - application at Bosch thermotechnology

Published:2022-10-11 Issue: Volume: Page:1-14
ISSN:1750-9653
Container-title:International Journal of Management Science and Engineering Management
language:en
Short-container-title:International Journal of Management Science and Engineering Management

Author:

Brochado A. F.¹,Rocha E. M.²³,Almeida D.⁴,de Sousa A.⁵,Moura A.¹⁶

Affiliation:

1. Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, Aveiro, Portugal

2. Department of Mathematics (Dmat), University of Aveiro, Aveiro, Portugal

3. Center for Research and Development in Mathematics and Applications (CIDMA), Aveiro, Portugal

4. Bosch Thermotechnology S.A, Cacia, Portugal

5. Department of Electronics, Telecommunications and Informatics (DETI), University of Aveiro, Aveiro, Portugal

6. Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Aveiro, Portugal

Publisher

Informa UK Limited

Subject

Information Systems and Management,Management Science and Operations Research,Strategy and Management,Mechanical Engineering,Engineering (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/17509653.2022.2116121

Reference56 articles.

1. Toward Industry 4.0 With IoT: Optimizing Business Processes in an Evolving Manufacturing Factory

2. Simulation-based multi-objective bottleneck improvement: Towards an automated toolset for industry

3. Detecting bottlenecks in serial production lines – a focus on interdeparture time variance

4. Bottlenecks in Bernoulli Serial Lines With Rework

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