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Challenges in Implementing Industry 4 Laboratories and Learning Factories in Academia.

, , , , and . IEEM, page 506-510. IEEE, (2019)

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Development of a fuzzy-simulation Model of Scheduling robotic flexible assembly cells., , and . J. Comput. Sci., 9 (12): 1761-1768 (2013)A Novel Optimization Model for simultaneous Cost-Risk Reduction in Multi-suppliers Just-in-Time Systems., , and . J. Comput. Sci., 9 (12): 1778-1792 (2013)Application of a fuzzy-simulation Model of Scheduling robotic flexible assembly cells., , and . J. Comput. Sci., 9 (12): 1769-1777 (2013)Challenges in Implementing Industry 4 Laboratories and Learning Factories in Academia., , , , and . IEEM, page 506-510. IEEE, (2019)An integrated production scheduling model for multi-product orders in VCIM systems., , and . Int. J. Syst. Assur. Eng. Manag., 8 (1): 12-27 (2017)An improved structure of genetic algorithms for global optimisation., , and . Progress in AI, 5 (3): 155-163 (2016)A Genetic Algorithm Approach for Modelling and Optimisation of MAJSP- Part II: GA operators and results., , and . IEEM, page 1279-1283. IEEE, (2011)Assembly sequence planning and optimisation using genetic algorithms: Part I. Automatic generation of feasible assembly sequences., , and . Appl. Soft Comput., 2 (3): 223-253 (2003)An innovative framework for designing genetic algorithm structures., , and . Expert Syst. Appl., (2017)Optimisation of production scheduling for multi-product orders in VCIM systems using GA., , , and . Soft Comput., 23 (20): 10199-10224 (2019)