scholarly journals Optimization of Lead Time through Genetic Algorithm: A Case Study of Equipment Manufacturing Industry

2021 ◽  
Vol 9 ◽  
Author(s):  
Qasim Rehman Siddiqui ◽  
◽  
Muhammad Shafiq ◽  
Keyword(s):  
Genetic Algorithm ◽  
Lead Time ◽  
Manufacturing Industry ◽  
Sensitivity Analyses ◽  
Proposed Model ◽  
Timely Completion ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry ◽  
The Impact

This study aims at optimizing lead time through effective management of resources in an equipment manufacturing industry to ensure timely completion of the projects. The concept of “project crashing” was implemented to identify potential activities at production line of conventional two-roller machines. The developed model is optimized using modified Genetic Algorithm (GA). The results showed that the proposed model enabled to deliver products as per schedule without increasing planned cost. Sensitivity analyses were also conducted to find out the impact of various process parameters. From analyses, it was found that the proposed model facilitate the manufacturer in delivering the products at specified time with increasing the planned cost.

scholarly journals Clique Structure and Enterprise Innovation: an Empirical Research on China's High-end Equipment Manufacturing Industry

2018 ◽  
Vol 11 (3) ◽  
pp. 21
Author(s):  
Xiangjie Zheng
Keyword(s):  
Manufacturing Industry ◽  
Negative Binomial ◽  
Moderating Effect ◽  
Innovation Performance ◽  
Innovation Network ◽  
Innovation Capability ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry ◽  
Enterprise Innovation ◽  
The Impact

Clique problem has been fully researched in the social relations network of sociology，But the cliques in inter-enterprise networks have attracted people's attention in recent years. Based on the alliance data of the high-end equipment manufacturing industry in China in 2000-2013, we construct innovation network，and use negative binomial regression models to analyze the impact of the clique structure on enterprise innovation. The results show that the more the clique numbers in the alliance innovation network, the stronger the enterprise innovation capability. Whether the enterprises listed have a negative moderating effect on the impact of clique numbers on enterprise innovation performance. That is, for the listed enterprises, more clique numbers cannot significantly promote enterprise innovation, but for non-listed enterprises, more clique numbers are conducive to enterprise innovation. Innovation accumulation has no significant positive moderating effect on the impact of clique numbers on enterprise innovation performance. The impact of the coreness values on the enterprise innovative output in an inverted-U curvilinear way, and the coreness values also moderates the effect of innovation accumulation on enterprise innovation capability in an inverted-U curvilinear way. The conclusions of the research can provide the basis for the enterprise to embed the network cliques and for the relevant government departments to formulate the alliance policy.

scholarly journals Impact of Embedded Global Value Chain on Technical Complexity of Industry Export—An Empirical Study Based on China’s Equipment Manufacturing Industry Panel

2020 ◽  
Vol 12 (7) ◽  
pp. 2694
Author(s):  
Yan Li ◽  
Haiyan Zhang ◽  
Yihui Liu ◽  
Qingbo Huang
Keyword(s):  
Value Chain ◽  
Manufacturing Industry ◽  
Global Value Chain ◽  
Industry Research ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry ◽  
Instrumental Variable Method ◽  
The Impact ◽  
D Investment ◽  
Embedding Methods

This study uses the World Input–Output Database (WIOD) to construct an export technical complexity index based on the effective elimination of imported foreign technology. The panel data of China’s equipment manufacturing industry from 2000 to 2014 are used as a sample, and the instrumental variable method is used to test the impact of the embedded global value chain on the technical complexity of industry exports. The impacts of different embedding time periods and different embedding methods on the technical complexity of industry exports are also explored with a view to providing reference recommendations to improve the technical complexity of China’s equipment manufacturing exports. The study finds that embedding a global value chain (GVC) can promote the export technical complexity of the equipment manufacturing industry, and with the improvement of domestic openness and industry research and development (R&D) investment conditions, the promotion effect will become increasingly potent. In addition, the backward and forward embedded global value chain (GVC) can promote the export technical complexity of the industry, and the effect of the promotion of backward embedding is even greater.

scholarly journals An Empirical Study on the Impact of Knowledge Intensive Business Service on Technology Innovation of Equipment Manufacturing Industry

2021 ◽  
Vol 257 ◽  
pp. 02032
Author(s):  
Xiaonan Fan ◽  
Jialun Li
Keyword(s):  
Technological Innovation ◽  
Manufacturing Industry ◽  
Liaoning Province ◽  
Business Service ◽  
Diffusion Of Knowledge ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry ◽  
Knowledge Intensive ◽  
Knowledge Intensive Business Service ◽  
The Impact

The knowledge intensive business service has obvious technological innovation effects. It can promote the technological innovation of the equipment manufacturing industry and enhance the innovation capability of the equipment manufacturing industry through the integration and diffusion of knowledge, technology, human resources and other resources. Taking the equipment manufacturing industry and knowledge intensive business service in Liaoning Province of China as the research objects, this paper analyzes the mechanism of knowledge intensive business service in promoting equipment manufacturing innovation, and constructs a model of the impact of knowledge intensive business service on the innovation of equipment manufacturing industry.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

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