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Heijunka, Planning and Scheduling, Sequencing Activities, Load Balancing
Published in Charles Protzman, Fred Whiton, Joyce Kerpchar, Christopher R. Lewandowski, Steve Stenberg, Patrick Grounds, James Bond, The Lean Practitioner’s Field Book, 2018
Charles Protzman, Fred Whiton, Joyce Kerpchar, Christopher R. Lewandowski, Steve Stenberg, Patrick Grounds, James Bond
In manufacturing, this concept is utilized to level out production of various or “mixed” models. This concept allows Toyota to run multiple car types down the same line one model after another. This can be accomplished only with flexibility built into the layout, equipment, utilities, and people. The idea behind this concept is to schedule your products evenly so as not to create batches of products coming in at one time. In some areas of companies, this is easy to do, and in some areas, it may be nearly impossible to do.
Lean Quality Management
Published in Jong S. Lim, Quality Management in Engineering, 2019
The primary motivation of JIT is to respect the market demands. Customers make a purchasing order, which is the initiation of the pulling system. Production should follow the pulling by producing the products in sequence. In other words, instead of producing batches of the same model, mixed models are produced on the same production line according to the market demand of the customer. We can increase customer satisfaction by demand-based sequence production.
Modeling, analysis and optimization of carousel-based flexible manufacturing system
Published in Journal of Industrial and Production Engineering, 2022
Hafiz Zahid Nabi, Tauseef Aized, Fahid Riaz
The complete FMS carousel-based layout configuration, which has been taken into consideration, is demonstrated in Figure 1. The system has five manufacturing cells and two assembly cells around a carousel layout configuration to accomplish two key activities: manufacturing and assembly of mixed-model multiple products. A mixed-model manufacturing system has become the need of the hour to deliver larger variety to customers and sustainability in a competitive market of any firm. Conventional manufacturing systems are not capable to respond quickly to the diverse nature of products as compared to computer integrated flexible manufacturing systems, which use different control algorithms. In the addressed flexible manufacturing system, primary material handling system consisting of a conveyor is responsible for moving parts from buffer storage as per process requirement either for manufacturing or assembly processes between different cells, while the secondary material handling system consists of a robot to transfer parts within each cell.
Anarchic manufacturing: implementing fully distributed control and planning in assembly
Published in Production & Manufacturing Research, 2021
Andrew Ma, Aydin Nassehi, Chris Snider
Due to demands for more flexible and versatile production, assembly lines have changed from fixed lines of a single model to mixed-model assembly lines, producing variants of the same product family (Battini et al., 2009). Mixed-model assembly lines use flexible workers and machinery to reduce setup times and costs, so that different products can be jointly manufactured in an intermixed product sequence on the same line (Boysen et al., 2009). Many issues arise from mixed-model facilities having greater task duration variation and drift from the cycle time and a lack of buffers used in industry (Battini et al., 2009). Flexible manufacturing and assembly systems are one of the most fundamental solutions to efficiently react to disturbances (ElMaraghy et al., 2013). For mixed-model production lines, the production processes of manufactured goods require a minimum level of homogeneity, therefore a common base product, or platform, is typically used which is customisable through a bounded number of and predetermined optional features (Boysen et al., 2009).
How IJPR has addressed ‘lean’: a literature review using bibliometric tools
Published in International Journal of Production Research, 2019
Maria Pia Ciano, Rossella Pozzi, Tommaso Rossi, Fernanda Strozzi
Notwithstanding the very large amount of literature on the scheduling of just-in-time production systems, the topic still attracts the interest of production researchers, due to the continuously increasing market demand for product variety, which forces manufacturers to design mixed-model assembly lines (Moradi, Zandieh, and Mahdavi 2011). Moreover, by levelling the production sequence, mixed-model production systems running under the just-in-time philosophy are implemented to efficiently meet customer demands for a variety of products. In this context, the production smoothing problem aims at finding level schedules in which the products are processed over the time horizon as uniformly as possible (Yavuz and Tufekci 2007). On the other hand, minimising the cumulative lead time of the production schedule, i.e. the makespan, is the objective of the scheduling of parts within most manufacturing systems, as demonstrated by the algorithms and models developed by researchers (e.g. Venkataramanaiah 2008; Abedi et al. 2015). Both production smoothing and just-in-time scheduling are in some cases NP-hard problems, and this issue is tackled by researchers. Moradi, Zandieh, and Mahdavi (2011) develop a genetic algorithm to deal with the NP-hard sequencing problem when two objectives are considered simultaneously. Yavuz and Tufekci (2007) develop a parametric heuristic procedure for dealing with an NP-hard sequencing.