Extracting the manufacturing information of machining features for computer-aided process planning systems

Manafi, D.; Nategh, Mohammad Javad; Parvaz, Hadi

doi:10.1177/0954405415623487

Cited by 25 publications

(13 citation statements)

References 21 publications

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“…Computer-aided design (CAD), computer-aided manufacturing (CAM), computer-aided technology (CAx) and so on are tools that allow to design, analyze and facilitate the design and production. 86 Therefore, these CAx tools are included in the IT-based production management cluster as well.…”

Section: Characteristics Clustersmentioning

confidence: 99%

“…Computer-aided design (CAD), computer-aided manufacturing (CAM), computeraided technology (CAx) and so on are tools that allow to design, analyze and facilitate the design and production. 86 Therefore, these CAx tools are included in the IT-based production management cluster as well. Interfaces and high-level frameworks such as Supply Chain Operations Research (SCOR), 87 Design Chain Operations Reference (DCOR), 88 Manufacturing Enterprise Solutions Association (MESA) and ISA 95/88 89 consider the various levels of business processes and provide a computer-based package support.…”

Section: Technology Clustersmentioning

confidence: 99%

See 1 more Smart Citation

Smart manufacturing: Characteristics, technologies and enabling factors

Mittal

Khan

Romero

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part B:

384

261

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The purpose of this article is to collect and structure the various characteristics, technologies and enabling factors available in the current body of knowledge that are associated with smart manufacturing. Eventually, it is expected that this selection of characteristics, technologies and enabling factors will help compare and distinguish other initiatives such as Industry 4.0, cyber-physical production systems, smart factory, intelligent manufacturing and advanced manufacturing, which are frequently used synonymously with smart manufacturing. The result of this article is a comprehensive list of such characteristics, technologies and enabling factors that are regularly associated with smart manufacturing. This article also considers principles of ''semantic similarity'' to establish the basis for a future smart manufacturing ontology, since it was found that many of the listed items show varying overlaps; therefore, certain characteristics and technologies are merged and/or clustered. This results in a set of five defining characteristics, 11 technologies and three enabling factors that are considered relevant for the smart manufacturing scope. This article then evaluates the derived structure by matching the characteristics and technology clusters of smart manufacturing with the design principles of Industry 4.0 and cyber-physical systems. The authors aim to provide a solid basis to start a broad and interdisciplinary discussion within the research and industrial community about the defining characteristics, technologies and enabling factors of smart manufacturing.

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Section: Characteristics Clustersmentioning

confidence: 99%

Section: Technology Clustersmentioning

confidence: 99%

Smart manufacturing: Characteristics, technologies and enabling factors

Mittal

Khan

Romero

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part B:

384

261

View full text Add to dashboard Cite

show abstract

“…In this article, the approach proposed by Manafi et al 24 is employed to specify the TAD. The machining features are identified using the graph-based method.…”

Section: Manufacturing Information For Fms and Setup Determinationmentioning

confidence: 99%

Reducing search space of optimization algorithms for determination of machining sequences by consolidating decisive agents

Manafi

Nategh

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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One of the main objectives of computer-aided process planning is to determine the optimum machining sequences and setups. Among the different methods to implement this task, it can be named the constrained optimization algorithms. The immediate drawback of these algorithms is usually a large space needed to be searched for the solution. This can easily hinder the convergence of the solution and increase the possibility of getting trapped in the local minima. A novel approach has been developed in this work with the objective of reducing the search space. It is based on consolidating the decisive factors influencing the consecutive features. This helps prevent creation of sequences which need the change of setup, machine tool, and cutting tool. The proposed method has been applied to three different optimization methods, including genetic, particle swarm, and simulated annealing algorithms. It is shown that these algorithms with reduced search spaces outperform those reported in the literature, with respect to the convergence rate. The best results are found in the genetic algorithm from the viewpoint of the obtained solution and the convergence rate. The worst results belong to the particle swarm algorithm in connection with the strategy of generating new solutions.

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“…One of the major PLM-related functionalities which is a challenge for most PLM/PDM software is openness related to D-I-K and is studied in detail to develop criteria for industrial internet platform selection from the perspective of effective facilitation of D-I-K within and between PLM lifecycle phases. [15][16][17][18][19] The remainder of this article is organized in a manner that we discuss the PLM challenges, industrial internet platforms and related selection criteria. Then we analyze the selected platforms based on industrial internet functionalities.…”

Section: Introductionmentioning

confidence: 99%

Industrial internet platforms: A conceptual evaluation from a product lifecycle management perspective

Menon

Kärkkäinen

Wuest

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part B:

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Industrial Internet platforms have the ability to access, manage and control product-related data, information and knowledge across all the lifecycle phases (beginning of life, middle of life and end of life). Traditional product lifecycle management/product data management software have many limitations when it comes to solving product lifecycle management challenges, like interoperability for instance. Industrial Internet platforms can provide real-time management of data and information along all the phases of a product’s lifecycle. Platform openness in combination with the above-mentioned industrial internet platform characteristics helps solve the product lifecycle management challenges. This article describes the product lifecycle management challenges in detail from the existing literature and presents solutions using industrial internet platform openness and related dimensions as well as sub-dimensions. A wide pool of platforms is narrowed down to specific platforms that can solve the documented product lifecycle management challenges and allow the manufacturing companies to collaborate as well as enhance their business. We also present in detail managerial implications toward long-term and sustainable selection of industrial internet platform.

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Extracting the manufacturing information of machining features for computer-aided process planning systems

Cited by 25 publications

References 21 publications

Smart manufacturing: Characteristics, technologies and enabling factors

Smart manufacturing: Characteristics, technologies and enabling factors

Reducing search space of optimization algorithms for determination of machining sequences by consolidating decisive agents

Industrial internet platforms: A conceptual evaluation from a product lifecycle management perspective

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