Production scheduling and nesting in additive manufacturing

Chergui, Akram; Hadj-Hamou, Khaled; Vignat, Frédéric

doi:10.1016/j.cie.2018.09.048

Cited by 112 publications

(45 citation statements)

References 15 publications

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“…The planning problem for a case in which orders from different distributed customers were satisfied by due dates was studied by Chergui et al (2018). A mathematical formulation of the problem was presented and a heuristic was also proposed to solve it.…”

Section: Production Scheduling and Nesting Problemsmentioning

confidence: 99%

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Production planning in 3D printing factories

Antón

Senovilla

González

et al. 2020

Int. J. Prod. Manag. Eng.

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<p>Production planning in 3D printing factories brings new challenges among which the scheduling of parts to be produced stands out. A main issue is to increase the efficiency of the plant and 3D printers productivity. Planning, scheduling, and nesting in 3D printing are recurrent problems in the search for new techniques to promote the development of this technology. In this work, we address the problem for the suppliers that have to schedule their daily production. This problem is part of the LONJA3D model, a managed 3D printing market where the parts ordered by the customers are reorganized into new batches so that suppliers can optimize their production capacity. In this paper, we propose a method derived from the design of combinatorial auctions to solve the nesting problem in 3D printing. First, we propose the use of a heuristic to create potential manufacturing batches. Then, we compute the expected return for each batch. The selected batch should generate the highest income. Several experiments have been tested to validate the process. This method is a first approach to the planning problem in 3D printing and further research is proposed to improve the procedure.</p>

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Section: Production Scheduling and Nesting Problemsmentioning

confidence: 99%

“…Moving on to powder-bed laser processes (e.g. Selective Laser Sintering, Selective Laser Melting, Direct Metal Laser Sintering), Chergui et al (2018) presented a model that considered delivery times in which the utilization of the manufacturing area was subordinated to the on-time service of the parts produced.…”

Section: Nesting Problem Approachmentioning

confidence: 99%

Production planning in 3D printing factories

Antón

Senovilla

González

et al. 2020

Int. J. Prod. Manag. Eng.

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show abstract

“…Inspired by our research, several studies have been reported recently. The production planning and scheduling of identical parallel AM machines to fulfil the different orders by due dates and to minimize the total tardiness was studied by Akram et al [40], where the mathematical formulation of the problem and a heuristic procedure were proposed. The problem was formulated as two subproblems-part/job assignment through part clustering based on due dates and job scheduling based on tardiness of the jobs.…”

Section: Related Workmentioning

confidence: 99%

A dynamic order acceptance and scheduling approach for additive manufacturing on-demand production

Qiang

Zhang

Wang

et al. 2019

Int J Adv Manuf Technol

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Additive manufacturing (AM), also known as 3D printing, has been called a disruptive technology as it enables the direct production of physical objects from digital designs and allows private and industrial users to design and produce their own goods enhancing the idea of the rise of the "prosumer". It has been predicted that, by 2030, a significant number of small and medium enterprises will share industry-specific AM production resources to achieve higher machine utilization. The decision-making on the order acceptance and scheduling (OAS) in AM production, particularly with powder bed fusion (PBF) systems, will play a crucial role in dealing with on-demand production orders. This paper introduces the dynamic OAS problem in on-demand production with PBF systems and aims to provide an approach for manufacturers to make decisions simultaneously on the acceptance and scheduling of dynamic incoming orders to maximize the average profit-per-unit-time during the whole makespan. This problem is strongly NP hard and extremely complicated where multiple interactional subproblems, including bin packing, batch processing, dynamic scheduling, and decision-making, need to be taken into account simultaneously. Therefore, a strategy-based metaheuristic decisionmaking approach is proposed to solve the problem and the performance of different strategy sets is investigated through a comprehensive experimental study. The experimental results indicated that it is practicable to obtain promising profitability with the proposed metaheuristic approach by applying a properly designed decision-making strategy.

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“…Such links in the timetable shall be included in the area of production planning. They consist in manufacturing a given element on several machines in a process line [5,19]. This chain is more flexible (easy to reorganise) and there are no such restrictions as in rail transport.…”

Section: Dependent Operationsmentioning

confidence: 99%

“…Tego typu powiązania w harmonogramie uwzględnia się w obszarze planowania produkcji. Polegają one na wytwarzaniu danego elementu na kilku maszynach w ciągu technologicznym [5,19]. Łańcuch ten cechuje się większą elastycznością (łatwością reorganizacji) i nie występują tam takie ograniczenia jak w transporcie kolejowym.…”

Section: Działania Zależneunclassified

Evaluation of Train Crews Schedule in Terms of Robustness

Wolniewicz

2019

Journal of KONBiN

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The evaluation of team work schedules in complex rail transport conditions is related to the robustness of individual solutions. In rail systems there are many aims that are important for users. One of the most important aims is to find a feasible solution. It is characterized by the non-conflicting schedule with another train, minimizing the travel time of the trainset and taking into account the priority of train. The problem of responding to delays in terms of reorganisation of work, prevention of delay propagation and real-time schedule changes is important. Schedules are built in a way that ensures the best use of work time. This has a negative impact on critical situations. The study analysed the changes of the conductor’s team to another train depending on the buffer time provided in work plan, real time needed for change and train delays.

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Production scheduling and nesting in additive manufacturing

Cited by 112 publications

References 15 publications

Production planning in 3D printing factories

Production planning in 3D printing factories

A dynamic order acceptance and scheduling approach for additive manufacturing on-demand production

Evaluation of Train Crews Schedule in Terms of Robustness

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