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From digital to universal manufacturing

Kusiak, Andrew - In: International journal of production research 60 (2022) 1, pp. 349-360

Persistent link: https://www.econbiz.de/10012873145

Open manufacturing : a design-for-resilience approach

Kusiak, Andrew - In: International journal of production research 58 (2020) 15, pp. 4647-4658

Persistent link: https://www.econbiz.de/10012266078

Smart manufacturing

Kusiak, Andrew - In: International journal of production research 56 (2018) 1/2, pp. 508-517

Persistent link: https://www.econbiz.de/10011876611

Convolutional and generative adversarial neural networks in manufacturing

Kusiak, Andrew - In: International journal of production research 58 (2020) 5, pp. 1594-1604

Persistent link: https://www.econbiz.de/10012194100

Federated explainable artificial intelligence (fXAI) : a digital manufacturing perspective

Kusiak, Andrew - In: International journal of production research 62 (2024) 1/2, pp. 171-182

Persistent link: https://www.econbiz.de/10014454722

Predictive models in digital manufacturing : research, applications, and future outlook

Kusiak, Andrew - In: International journal of production research 61 (2023) 17, pp. 6052-6062

Persistent link: https://www.econbiz.de/10014382694

Universal manufacturing : enablers, properties, and models

Kusiak, Andrew - In: International journal of production research 60 (2022) 8, pp. 2497-2513

Persistent link: https://www.econbiz.de/10013375405

Forecasting technology success based on patent data

Altuntas, Serkan; Dereli, Türkay; Kusiak, Andrew - In: Technological forecasting & social change : an … 96 (2015), pp. 202-214

Persistent link: https://www.econbiz.de/10011532541

From data to big data in production research : the past and future trends

Kuo, Yong-Hong; Kusiak, Andrew - In: International journal of production research 57 (2019) 15/16, pp. 4828-4853

Persistent link: https://www.econbiz.de/10012193504

Modeling and optimization of a chiller plant

Wei, Xiupeng; Xu, Guanglin; Kusiak, Andrew - In: Energy 73 (2014) C, pp. 898-907

A data-driven approach is utilized to model a chiller plant that has four chillers, four cooling towers, and two chilled water storage tanks. The chillers have varying energy efficiency. Since the chiller plant model derived from data-driven approach is nonlinear and non-convex, it is not...

Persistent link: https://www.econbiz.de/10010906856