Intelligent machining: a review of trends, achievements and current progress

Imad, Mohamd; Hopkins, Connor; Hosseini, Ali; Yussefian, N.Z.; Kishawy, Hossam A.

doi:10.1080/0951192x.2021.1891573

Cited by 20 publications

(5 citation statements)

References 100 publications

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“…The small craft industry in West Java is gradually embracing technological innovation to improve efficiency and meet consumer expectations while preserving traditional craftsmanship [1], [13]. Traditional production methods that emphasized manual craftsmanship are being integrated with technology to enhance production capabilities [14]. The use of parametric technology and digital transformation in bamboo weaving, for example, has provided new design methods and ideas for the development of bamboo weaving products [15].…”

Section: Technological Innovation In Small Craft Industrymentioning

confidence: 99%

Increasing Production Efficiency in Handicraft Small Industries in West Java Through the Utilization of Technological Innovation

Putra,

Wibowo

2023

WSJEE

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This study looks at the dynamics of technical innovation adoption and how it affects the productivity of small-scale craft businesses in West Java, Indonesia. A quantitative approach was used to collect data from 110 small craft businesses, including statistical analysis and quantitative surveys. The workforce had high skill levels, moderate levels of technology adoption, and perceived problems such as resistance to change and financial restrictions. These findings were supported by descriptive statistics. Technology use, worker skills, and production efficiency were found to be significantly positively correlated, as evidenced by multiple regression analysis. Differences in adoption patterns between rural and urban industries were revealed through cross tabulation. The results of this study highlight the need for a customized approach, resource distribution and information exchange to enhance technical innovation in the heterogeneous craft industry in West Java.

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Section: Technological Innovation In Small Craft Industrymentioning

confidence: 99%

Increasing Production Efficiency in Handicraft Small Industries in West Java Through the Utilization of Technological Innovation

Putra,

Wibowo

2023

WSJEE

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“…Classification of metal forming processes [2] For high-volume manufacturing, deep drawing is considered a promising and valuable process. The most important advantage of this process is its potential to manufacture components with exceptional repeatability and accuracy while reducing the manufacturing cost compared to other manufacturing methods, such as turned and machined components [3]. The process of deep drawing is a significant method in sheet metal forming.…”

Section: Introductionmentioning

confidence: 99%

Lubricating materials as a novel approach to reduce defects of micro-deep drawing forming process

Khalil,

Shaker,

Yaseen

et al. 2024

J Appl Eng Science

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The deep drawing forming process, classified under sheet metal working, is a promising and essential metal forming process that has attracted much interest due to its wide application in micro-production. The process parameters, such as the cross-head speed of the machine, have a significant influence on the quality of the product. The impact of two essential parameters was investigated to minimize or eliminate the product's production defects, such as thinning, tearing, and scratching. The first one was the impact of using two types of lubricating oil (grease and wax), and the products were compared with the dry condition (without using a lubricating oil). The second is the impact of changing the cross-head speed of the machine from 5 to 15 mm/min. This work aims to determine the optimum operating condition that prevents any defect in the product. The results showed that using lubricating oil resulted in better product shape, and the wax is better than grease in eliminating product defects. In addition, the results showed that the lower machine speed is preferred for eliminating production defects, where the final product has no obvious thinning, tearing, or scratching. The final product shape was evaluated visually because eye observation is the only way to judge the product shape.

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“…Zhou and Xue [10], Mohanraj et al [34] and Pimenov et al [35] have summarized TCM in milling, including chatter detection. Sensor types were reviewed by Rizal et al and Dhobale et al [36,37], Lauro et al [38] outlined the signal processing techniques, Kuntoğlu et al and Wong et al [39,40] discussed data acquisition and processing, Imad et al [41] described advances in machining monitoring, while Zhu et al and Peng et al [42,43] reviewed wavelet-based methods. The use of digital image processing was revised by Dutta et al [44], and vision-based techniques were outlined by Liu et al [45].…”

Section: Introductionmentioning

confidence: 99%

Chatter detection in milling processes—a review on signal processing and condition classification

Navarro-Devia

Chen

Dao

et al. 2023

Int J Adv Manuf Technol

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Among the diverse challenges in machining processes, chatter has a significant detrimental effect on surface quality and tool life, and it is a major limitation factor in achieving higher material removal rate. Early detection of chatter occurrence is considered a key element in the milling process automation. Online detection of chatter onset has been continually investigated over several decades, along with the development of new signal processing and machining condition classification approaches. This paper presents a review of the literature on chatter detection in milling, providing a comprehensive analysis of the reported methods for sensing and testing parameter design, signal processing and various features proposed as chatter indicators. It discusses data-driven approaches, including the use of different techniques in the time–frequency domain, feature extraction, and machining condition classification. The review outlines the potential of using multiple sensors and information fusion with machine learning. To conclude, research trends, challenges and future perspectives are presented, with the recommendation to study the tool wear effects, and chatter detection at dissimilar milling conditions, while utilization of considerable large datasets—Big Data—under the Industry 4.0 framework and the development of machining Digital Twin capable of real-time chatter detection are considered as key enabling technologies for intelligent manufacturing.

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Intelligent machining: a review of trends, achievements and current progress

Cited by 20 publications

References 100 publications

Increasing Production Efficiency in Handicraft Small Industries in West Java Through the Utilization of Technological Innovation

Increasing Production Efficiency in Handicraft Small Industries in West Java Through the Utilization of Technological Innovation

Lubricating materials as a novel approach to reduce defects of micro-deep drawing forming process

Chatter detection in milling processes—a review on signal processing and condition classification

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