Generation of identifiable CNC reference runs with high information content for machine learning and analytic approaches to parameter identification

Gönnheimer, Philipp; Ströbel, Robin; Netzer, Markus; Fleischer, Jürgen

doi:10.1016/j.procir.2022.05.054

Cited by 6 publications

(1 citation statement)

References 1 publication

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“…To get a first impression of the correlation between axis-specific velocity, acceleration and power, existing data sets were analyzed. The recordings were made on the three-axis milling machine CMX 600V from DMG Mori using the reference runs described in [39] and a sampling rate of 500 Hz. The block change was performed at 80% of the braking ramp.…”

Section: Prediction Of the Axis Specific Energy Consumptionmentioning

confidence: 99%

Software-Defined Workpiece Positioning for Resource-Optimized Machine Tool Utilization

Ströbel¹,

Probst²,

Hutt³

et al. 2023

Journal of Machine Engineering

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Advancing climate change, tense world markets, and political pressure steadily increase the demand for resourceoptimized production solutions. Herby, the positioning of the raw material in the machine tool is an important factor that has received little attention. Traditionally, this is done centrally on the machine table, which leads to locally increased wear of the feed axis. Furthermore, positioning directly influences energy consumption during machining. Consequently, the longest possible component utilization through optimum wear and energy optimization creates a direct conflict of objectives. To solve this conflict, this paper presents an automated approach for software-defined workpiece positioning and NC-Code optimization regarding the axis-specific energy consumption and the spindle condition of ball screws. An approach for mapping the energy consumption and the directly measured spindle condition is presented. Both represent input variables of the cost function. Approaches for the optimization of the position as well as for the practical implementation are proposed.

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Section: Prediction Of the Axis Specific Energy Consumptionmentioning

confidence: 99%

Software-Defined Workpiece Positioning for Resource-Optimized Machine Tool Utilization

Ströbel¹,

Probst²,

Hutt³

et al. 2023

Journal of Machine Engineering

View full text Add to dashboard Cite

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Analytical Approach for Parameter Identification in Machine Tools Based on Identifiable CNC Reference Runs

Gönnheimer

Ströbel

Fleischer

2023

Lecture Notes in Production Engineering

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Software-Defined Manufacturing for the Entire Life Cycle at Different Levels of Production

et al. 2023

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Increasingly volatile markets, higher numbers of product variants and more sophisticated customer demands lead to a soaring complexity of productions themselves and their operations. An enabling technology that allows to cope with this increased complexity is digitization, as it enables data capturing and data driven analysis in production. Software-defined manufacturing (SDM) empowers to fully use the potential of digitization by decoupling physical production hardware and the associated control software. This enables an increase in the versatility of existing resources through automated generation of software for instantiations and interventions in production control. With the aim of enlarging the abstraction and decoupling capabilities of SDM, this paper presents a concept to use SDM at different abstraction levels of the production over the whole life cycle. The different abstraction levels, i.e. machine, production system and production network, are decoupled based on a service-oriented approach that defines interactions between these abstraction levels. The requirements to implement this approach are determined for the different levels where special notice is given to changing requirements over the life cycle of the production. With respect to the requirements, recommendations are given considering the integration of the concept in existing productions. Finally, potential benefits of this concept are discussed.

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Generation of identifiable CNC reference runs with high information content for machine learning and analytic approaches to parameter identification

Cited by 6 publications

References 1 publication

Software-Defined Workpiece Positioning for Resource-Optimized Machine Tool Utilization

Software-Defined Workpiece Positioning for Resource-Optimized Machine Tool Utilization

Analytical Approach for Parameter Identification in Machine Tools Based on Identifiable CNC Reference Runs

Software-Defined Manufacturing for the Entire Life Cycle at Different Levels of Production

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