Simultaneous Balancing and Scheduling of Flexible Mixed Model Assembly Lines with Sequence-Dependent Setup Times
References (3)
Monolithic vs. hierarchical balancing and scheduling of a flexible assembly line
European Journal of Operational Research
(2002)
Cited by (17)
Empowering and engaging industrial workers with Operator 4.0 solutions
2020, Computers and Industrial EngineeringCitation Excerpt :Techniques/tools such as gesture recognition, video analysis and augmented reality could be used to monitor the realization of these tasks as well as to recommend operations/tools to the worker in order to complete their job. Similar to this task, determining the optimal ordering of assembly operations assigned to a worker in terms of total walking distance between assembly unit and the tool magazine for tool changing is another point that can be improved (Öztürk, Tunali, Hnich & Örnek, 2010a), along with finding the most ergonomic and time-efficient way of ordering tasks in terms of task time increments due to positioning of the assembly unit (Öztürk, Tunali, Hnich & Örnek, 2010b). Last but not least, communication channels between workers and with their environment need to be enhanced in order to accommodate knowledge sharing.
Combinatorial Benders cuts for assembly line balancing problems with setups
2017, European Journal of Operational ResearchCitation Excerpt :This sequence-dependent scheduling problem is typically solved on a day-to-day or shift-by-shift basis, to find the best production sequence of a given number of models (Boysen, Fliedner, & Scholl, 2009). The long term line design problem and the short term sequence-dependent scheduling problem can be simultaneously solved in an integrated way (Ozturk, Tunali, Hnich, & Ornek, 2010). In this paper, however, we concerned ourselves with the tactical design problem of designing a mixed-model assembly line that is able to produce different models in any intermixed sequence.
Operational extended model formulations for Advanced Planning and Scheduling systems
2014, Applied Mathematical ModellingCitation Excerpt :Interested readers can refer to the references for more detail. There are also heuristic approaches to create capacity feasible schedules that take into account realistic constraints, such as sequence and machine dependent setups, parallel machines and multiple objectives [12,9,13]. These algorithms try to develop production schedules to balance demand with the resources of the factory.
Integrated decision making in flow line balancing
2013, IFAC Proceedings Volumes (IFAC-PapersOnline)A constraint programming model for balancing and scheduling of flexible mixed model assembly lines with parallel stations
2012, IFAC Proceedings Volumes (IFAC-PapersOnline)A genetic algorithm approach for balancing two-sided assembly lines with setups
2019, Assembly Automation