The influence of Flexible Manufacturing Technology adoption on productivity of Malaysian manufacturing industry

2010 ◽  
Vol 27 (1) ◽  
pp. 395-403 ◽  
Author(s):  
D.A.R. Dolage ◽  
Abu Bakar Sade ◽  
Elsadig Musa Ahmed
2021 ◽  
pp. 1-13
Author(s):  
Yang GAO ◽  
Xiang GAO

With knowledge perspective of industrial technology, in this paper we propose fast ranking score decision making model based on Fuzzy integrated TOPSIS approach to determine economic growth rate of manufacturing industry in China. This research focuses on driving effects of China’s productive service industry on manufacturing technology innovation. The research results show that the manufacturer service industry takes a high level of information diffusion for the manufacturing industry. It transmits a large amount of diverse information through the unconstrained relationship with the manufacturing industry, thereby forming the economic network with proposed Fuzzy integrated TOPSIS economy ranking (FITER) model and improve the development level of the manufacturing industry. We evaluate the performance of proposed FITER model by comparing ranking score of different manufacturing industry with different existing decision making mode and demonstrate that proposed model represent best ranking score in comparison to existing approach. Result from data analysis motivates driving effect of production services on the technological innovation of manufacturing and sub-sectors. It is found that the innovation and technological advancement in the production industry of services takes drive the overall expansion level of the business industry, as well as make the manufacturing industry the strongest.


2013 ◽  
Vol 465-466 ◽  
pp. 682-687
Author(s):  
Fairul Azni Jafar ◽  
Nurhidayu Abdullah ◽  
Noraidah Blar ◽  
M.N. Muhammad ◽  
Anuar Mohamed Kassim

In order for humans and robots to interact in an effective and instinctive manner, robots must obtain information about the human emotional state in response to the robots actions. This is important as the presence of robot in manufacturing industry is very wide and robot plays a big role in the emerging of automation manufacturing technology. Consequently, we believed that it is necessary to investigate how human feel about this situation and if robot can understand those human emotions, collaboration with human can be much better. In order to investigate the human emotions, we applied akanseisurvey method based on akanseiengineering technology. We request a number of participants to take part in our experiment where they will be in the same environment of where a robot is working on some tasks. The participants will answer those questions in the survey based on what they feel about working together with moving robot. The overall goal is, in fact, to predict in which area in the vicinity of the robot that the human is heading to, especially in term of humans feeling, so that by understanding how human feels of working together with robots, perhaps we can create a better working environment. This paper describes the results of our findings about how human feel when collaborating with robot (s).


1990 ◽  
Vol 26 (1-4) ◽  
pp. 351-375 ◽  
Author(s):  
Jonathan P. Caulkins ◽  
Charles H. Fine

2018 ◽  
Vol 9 (2) ◽  
pp. 54-69 ◽  
Author(s):  
Gregory W. Ulferts ◽  
Terry L. Howard ◽  
Nicholas J. Cannon

This article describes how U.S. manufacturing was stricken when companies embraced outsourcing beginning in the 1990s as a strategy for taking advantage of lower labor costs in developing countries. The U.S. textile and apparel industries lost 76.5% of its workforce, or 1.2 million jobs, between 1990 and 2012. The catalyst which has renewed the interest in manufacturing textiles and apparel in the United States is the narrowing gap between the U.S. and Asian labor costs. The sector changed in response to technology and the global market, and both the number and type of employees demanded turned as well. The advanced technology currently drives the domestic textile industry. Despite a positive outlook on growth, it is unlikely that textile manufacturing will create the large number of jobs that it did in the past. Furthermore, it is only viable because of the technological improvements to its factories. The current production is designed to employ fewer workers in order be more productive and less dependent on labor costs. Nevertheless, the high demand for specialized and unique textiles in the U.S. and Europe will likely continue to drive improved manufacturing technology and performance. China's transition from a manufacturing economy to a service economy will increase its manufacturing operational costs, while probably growing demand for the sorts of specialized textiles on which American textile manufacturers tend to focus. If such manufacturers can increase their market shares in China and other Asian countries, while maintaining such markets in the U.S. and Europe, the American textile manufacturing industry will likely grow at a moderately high rate.


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