Berg, Simon Vestergaard

Bodilsen, Morten Svangren

Nielsen, Mette Busk

Sarivan, Ioan-Matei

Schou, Casper

English

In the sheet metal industry, companies rely on nesting procedures to organise the cut patterns of sheet metal. Most of the current nesting algorithms and methods focus solely on laying out the cutting patterns only to reduce material usage. However, in dynamic manufacturing environments, such as engineer to order (ETO) companies, efficient nesting has to be addressed together with effective production scheduling. Therefore, reducing the trade-off between high material utilisation (to lower production cost) and effective production planning (to honour tight delivery deadlines) is essential. This paper presents a novel scheduled nesting approach for ETO companies. The framework is built on the existing ”scheduled nesting” model, where material utilisation and variables implied from different operations around the nesting process are considered together. The proposed artifact, called Scheduled Nesting System (SNS), is based on a constrained optimisation objective function to be minimised and considers a wide range of variables, which are either directly or indirectly connected with nesting. These variables are material usage, operation of cutting machine cost, cost of changing metal sheets, cost of cutting orders to stock, and order due date, to name a few. The dynamic nature of the ETO operations is as such included by adapting pending nests based on incoming orders. Based on these variables, the framework finds a nest, which has a minimal cost. The study focuses on ETO companies’ sheet metal nesting process, and test results show the SNS’s potential for lead-time and production cost reduction

Automated Scheduled Nesting for Flexible Manufacturing

https://vbn.aau.dk/files/474994838/1_s2.0_S2212827122004516_main.pdf

Automated Scheduled Nesting for Flexible Manufacturing

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