Enriched machining feature-based reasoning for generic machining process sequencing

Wang, Lihui; Cai, Ningxu; Feng, Hsi-Yung; Liu, Z.

doi:10.1080/00207540500354119

Cited by 50 publications

(10 citation statements)

References 33 publications

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“…Consequently, the proposed DPP separates generic and machine-specific information of process plans by assigning operation planning tasks to open-architecture CNC controllers. In order to realise the concept of DPP, Wang et al (2006) propose a reasoning approach to generic machining process sequencing, based on enriched machining features (EMFs). An EMF is represented by combining its machining volume with surface, geometric and volume features, as well as other technological information needed to machine the feature.…”

Section: Overview Of Related Research Workmentioning

confidence: 99%

“…The application of feature-based process planning has gained ground recently in supporting the efficient CAD and CAM integration (Gao et al 2004;Zhou et al 2007). Features are assumed inherently as a main factor in such an integration effort because of the association of various design, engineering and manufacturing data used by CAPP (Liu and Wang 2007;Tanaka and Kishinami 1998;Wang et al 2006). Proper sequencing of machining features still remains a challenging issue in CAPP due to its complexity and adherence to the class of nondeterministic polynomial-time problems (Mokhtar and Xu 2011).…”

Section: Introductionmentioning

confidence: 99%

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Feature-based generation of machining process plans for optimised parts manufacture

Deja

Siemiątkowski

2012

J Intell Manuf

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Efficacious integration of such CAx technologies as CAD, CAM and CAPP still remains a problem in engineering practice which constantly attracts research attention. Design by feature model is assumed as a main factor in the integration effort in various engineering and manufacturing domains. It refers principally to feature clustering and consequently operation sequencing in elaborated process plan designs. The focus of this paper is on CAPP for parts manufacture in systems of definite processing capabilities, involving multi-axis machining centres. A methodical approach is proposed to optimally solve for process planning problems, which consists in the identification of process alternatives and sequencing adequate working steps. The approach involves the use of the branch and bound concept from the field of artificial intelligence. A conceptual scheme for generation of alternative process plans in the form of a network is developed. It is based on part design data modelling in terms of machining features. A relevant algorithm is proposed for creating such a network and searching for the optimal process plan solution from the viewpoint of its operational performance, under formulated process constraints. The feasibility of the approach and the algorithm are illustrated by a numerical case with regard to a real application and diverse machine tools with relevant tooling. Generated process alternatives for complex machining with given systems, are studied using models programmed in the environment of Matlab software.

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Section: Overview Of Related Research Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Feature-based generation of machining process plans for optimised parts manufacture

Deja

Siemiątkowski

2012

J Intell Manuf

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“…In [12], a system was reported for setup planning in machining operations using Java and Web technologies, where XML was used to transfer data and information between various manufacturing systems. Wang et al, recently proposed to use enriched machining features and function blocks to handle the uncertainty [13] [14]. The goal is to generate detailed and adaptive operation plans at runtime by CNC controllers to best utilize the capability of the available machines.…”

Section: State Of the Artmentioning

confidence: 99%

Machine Availability Monitoring for Adaptive Holistic Scheduling: A Conceptual Framework for Mass Customization

et al. 2014

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Although the market started expressing the need for high product variety three decades ago, manufacturing systems have not kept the pace with these social and economic developments. Modern industrial shop-floors are highly affected by the ever-increasing product variety and volatile market demands introduced by the currently established mass customization paradigm. The increasing complexity and high unpredictability in manufacturing activities require immediate reactions to emerging disturbances, such us reducing bottlenecks, and avoiding brake-downs and idleness of critical equipment in order to increase productivity and therefore, the company's competitiveness. The framework proposed in this research work includes machine monitoring techniques for the near real-time identification of machine status, in order to allow a predictive maintenance engine to diminish machine tool failures. Moreover, an adaptive short-term scheduling mechanism is employed, using monitoring data for the refinement of production schedules based on the current and future conditions of the shop-floor. Data acquired from a multisensory pilot installation together with information directly retrieved from the machine tool's controller are fused and comprise the input to subsequent software modules. The monitoring module is described, which analyses sensory data during the machine operation, as well as the Adaptive Scheduling Engine that dispatches schedules and refines future schedules based on awareness regarding machine availability. The software architecture and hardware setups are described and comprise the roadmap for the framework development. A possible application of the framework is described in the context of a European SME manufacturer.

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“…9 consists of 14 machining features. After applying the five geometry-reasoning rules [29], the 14 machining features are grouped into two setups and a critical machining sequence is generated for each setup, which mainly considers datum references and manufacturing constraints at this stage. The non-critical machining features remain in parallel (e.g.…”

Section: Case Studymentioning

confidence: 99%

A review of function blocks for process planning and control of manufacturing equipment

Wang

Adamson

Holm

et al. 2012

Journal of Manufacturing Systems

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Enriched machining feature-based reasoning for generic machining process sequencing

Cited by 50 publications

References 33 publications

Feature-based generation of machining process plans for optimised parts manufacture

Feature-based generation of machining process plans for optimised parts manufacture

Machine Availability Monitoring for Adaptive Holistic Scheduling: A Conceptual Framework for Mass Customization

A review of function blocks for process planning and control of manufacturing equipment

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