Application issues of industrial soft computing systems

An overview of the key technical, organizational, and political issues that need to be resolved for successful application of soft computing systems in industry is given in the paper. An integrated methodology with neural networks, support vector machines, and genetic programming is recommended. Several examples of successful soft computing applications in the chemical industry are given. The key explored application areas are inferential sensors, automated operating discipline, process emulators, accelerated new product development, and complex process optimization.