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Thus, simulation may also be effective in helping achieve better line balancing, even predicting problems before production starts. Results derived from the simulation hypothesise that by considering the operators’ efficiencies the production line could be changed generating higher productivity and lower work in process (WIP). An optimization solution is suggested that may be one route to improving production line performance. The data collected by the researcher from a dress assembly line in factory in China is used to build a simulation using ProModel software.

This paper will develop a simulation technique that can be applied to production lines, balancing the data derived and offering clear measurements of operators’ efficiencies. Simultaneously, differences in operators’ efficiency make this difficulty far greater. However, on the shop floor, it is difficult to achieve line balancing due to the different pitch time of each workstation. This speeds the response to those rapid changes occurring in the apparel industry. The need for high product variety, smaller batch size, shorter delivery time and higher quality has encouraged apparel companies to concentrate on the development of digitization and information management. The target audience includes professors and students in engineering schools, and researchers and engineers in industries. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks in industrial and control engineering areas.

Parts continue with applications in materials science and industry such as material identification, and estimation of material property and state, food industry such as meat, electric and power industry such as batteries and power systems, mechanical engineering such as engines and machines, and control and robotic engineering such as system control and identification, fault diagnosis systems, and robot manipulation. Particular applications in textile industries follow. The book begins with a review of applications of artificial neural networks in textile industries. The purpose of this book is to provide recent advances of artificial neural networks in industrial and control engineering applications. Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications.