Analysis on critical success factors for agile manufacturing evaluation in original equipment manufacturing industry-an AHP approach

Dev, C. Ajay Guru; Kumar, V.S. Senthil

doi:10.3901/cjme.2016.0608.071

Cited by 21 publications

(2 citation statements)

References 16 publications

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“…The industry’s industrial structure is perfect. Due to the country promoting the EMI development, the industry, relying on abundant capital and talent base, constantly improves its innovation ability to improve the LoI [ 63 ]. The instrument industry is the smallest subsector in the EMI because the instrument products in the long term have a trade deficit.…”

Section: Resultsmentioning

confidence: 99%

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta

Zhou,

Xiang,

Tang

et al. 2024

PLoS ONE

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The Yangtze River Delta (YRD) bears the vital task of driving the growth of China’s equipment manufacturing industry (EMI) intelligence as an advanced region. Fostering the transformation and upgrading of the EMI in the YRD and constructing a modern production mode is vital to developing and reforming China’s manufacturing industry. This paper uses industrial robot data to assess the level of intelligence (LoI) in the EMI from 2016 to 2019. The OLS (ordinary least squares) model is used for the measurements, and the MQ (the modified contribution index) is used to estimate the degree of contribution from a host of variables. It is identified that the LoI is on the rise. However, excluding railways, aerospace, shipbuilding, and other transportation equipment manufacturing, the LoI is significantly higher than in other subsectors. It is also identified that technological innovation ability, human capital density, and enterprise cost pressure govern the industry’s LoI. Moreover, while there is a difference in the main influencing factors in LoI within different industries, R&D investment, technological innovation ability, and enterprise cost pressure have the most significant impact across most equipment manufacturing sub-industries.

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Section: Resultsmentioning

confidence: 99%

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta

Zhou,

Xiang,

Tang

et al. 2024

PLoS ONE

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“…Selection results of manufacturing enterprise innovation projects for customers' green preferences. The methods of Analytic Hierarchy Process (AHP) [48] and information entropy [49] were respectively applied to select innovative projects, and the ranking results are shown in Table 5. Table 5.…”

Section: Resultsmentioning

confidence: 99%

Selection of Manufacturing Enterprise Innovation Design Project Based on Consumer’s Green Preferences

Jie

Song

2019

Sustainability

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For enterprise, how to quickly realize the selection of green innovative design projects has become a key issue for improving innovation performance. Based on an analysis of enterprise product innovation and customer green preferences, an indicator set for innovation performance in enterprise was established. Considering the fuzziness of the correlation between indicators for innovation performance in enterprise and consumer’s green preferences, a fuzzy clustering method was used to identify the internal relations among the indicators for innovation performance with green preferences of customers. Then a wavelet neural network was used to select the innovation design project for various green preferences of customers. Finally, a case study was proposed to verify the feasibility and effectiveness of the method. This work can help the enterprise to develop green design, products, and serve uniformly, which can effectively shorten green product development cycles, reduce cost, and improve enterprise innovation performance greatly.

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Enablers for Lean Six Sigma and Agile Implementation: An Interpretive Structural Modeling Approach

Mundra

Mishra

2020

Lecture Notes in Mechanical Engineering

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Analysis on critical success factors for agile manufacturing evaluation in original equipment manufacturing industry-an AHP approach

Cited by 21 publications

References 16 publications

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta

Selection of Manufacturing Enterprise Innovation Design Project Based on Consumer’s Green Preferences

Enablers for Lean Six Sigma and Agile Implementation: An Interpretive Structural Modeling Approach

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