An integrated process planning approach for CNC machine tools

Aktürk, M. Seli̇m; Avci, Selcuk

doi:10.1007/bf01351201

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Yeo (1995) developed a multi-pass optimisation method for a CNC lathe, in which near-optimal solutions were obtained. Akturk and Avci (1996) presented a hierarchical method for a CNC machine tool. In their method, the mathematical models on system characterisation were established to minimise the total production cost.…”

Section: Related Workmentioning

confidence: 99%

A big data analytics based machining optimisation approach

Yin

Wang

2018

J Intell Manuf

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Currently, machine tool selection, cutting tool selection and machining conditions determination are not usually performed at the same time but progressively, which may lead to suboptimal or trade-off solutions. Targeting this issue, this paper proposes a big data analytics based optimisation method for enriched Distributed Process Planning by considering machine tool selection, cutting tool selection and machining conditions determination simultaneously. Within the context, the machining resources are represented by data attributes, i.e. workpiece, machining requirement, machine tool, cutting tool, machine conditions, machining process and machining result. Consequently, the problem of machining optimisation can be treated as a statistic problem and solved by a hybrid algorithm. Regarding the algorithm, artificial neural networks based models are trained by machining data and used as optimisation objectives, whereas analytical hierarchy process is adopted to decide the weights of the multi-objective optimisation; and evolutionary algorithm or swarm intelligence is proposed to perform the optimisation. Finally, the results of a simplified proof-of-concept case study are reported to validate the proposed approach, where a Deep Belief Network model was trained by a set of hypothetic data and used to calculate the fitness of a genetic algorithm.

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Section: Related Workmentioning

confidence: 99%

A big data analytics based machining optimisation approach

Yin

Wang

2018

J Intell Manuf

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“…The major development of Industry 3.0 was the use of computer numerical control (CNC) machines which enabled processing of materials in many different sizes and numbers. A CNC equipment is basically a computer controlled sculptor, which produces 3D objects by removing parts from a solid block, performing a subtractive manufacturing with top-down approach [ 23 ]. During the cutting and shaping of very complex structures with CNC, there may be a loss of detail in the product due to the limited 3D movement of the cutting tip [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Novel additive manufacturing applications for communicable disease prevention and control: focus on recent COVID-19 pandemic

et al. 2021

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COVID-19 disease caused by the SARS-CoV-2 virus has had serious adverse effects globally in 2020 which are foreseen to extend in 2021, as well. The most important of these effects was exceeding the capacity of the healthcare infrastructures, and the related inability to meet the need for various medical equipment especially within the first months of the crisis following the emergence and rapid spreading of the virus. Urgent global demand for the previously unavailable personal protective equipment, sterile disposable medical supplies as well as the active molecules including vaccines and drugs fueled the need for the coordinated efforts of the scientific community. Amid all this confusion, the rapid prototyping technology, 3D printing, has demonstrated its competitive advantage by repositioning its capabilities to respond to the urgent need. Individual and corporate, amateur and professional all makers around the world with 3D printing capacity became united in effort to fill the gap in the supply chain until mass production is available especially for personal protective equipment and other medical supplies. Due to the unexpected, everchanging nature of the COVID-19 pandemic-like all other potential communicable diseases-the need for rapid design and 3D production of parts and pieces as well as sterile disposable medical equipment and consumables is likely to continue to keep its importance in the upcoming years. This review article summarizes how additive manufacturing technology can contribute to such cases with special focus on the recent COVID-19 pandemic.

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Big Data Analytics for Scheduling and Machining

Wang

2017

Cloud-Based Cyber-Physical Systems in Manufacturing

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An integrated process planning approach for CNC machine tools

Cited by 6 publications

References 10 publications

A big data analytics based machining optimisation approach

A big data analytics based machining optimisation approach

Novel additive manufacturing applications for communicable disease prevention and control: focus on recent COVID-19 pandemic

Big Data Analytics for Scheduling and Machining

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