Implementation of fuzzy logic systems and neural networks in industry

Industrial applications of type-2 fuzzy sets and systems: A concise review

“…Since the ability of the FSs indicated robust and valid results, they have been used in a wide range of applications in many diverse fields of manufacturing. The type-1 FSs have been successfully implemented in several industrial areas, such as automobile speed control, robot arm control, water quality control, and automatic train operation systems [18]. The fundamental superiority of type-2, over type-1 models has been its ability to capture membership of relevant membership values where the uncertainty is handled more accurately.…”

A review of soft computing applications in supply chain management

“…Fuzzy systems are very useful not only in situations involving highly complex systems but also in situations where an approximate solution is warranted (Ross, 2004). To deal with qualitative, inexact, uncertain and complicated processes, the fuzzy logic system can be well-adopted since it exhibits a human-like thinking process (Du and Wolfe, 1997).…”

AI and OR in management of operations: history and trends

“…Ming and Mak (2001) use a hybrid GA/NN approach to study tolerance allocation and manufacturing operations selection in process planning. Du and Wolfe (1997) present details of the implementation of NN/FL systems in industry including inventory. In supply chain management, a hybrid CBR/NN approach has been used for benchmarking suppliers in outsource manufacturing (Choy et al 2002) and for supplier-relationship management (Choy et al 2003) Examples of multiple hybrid systems include the use of KBS/FL and NNs in control of communication systems (Guyot et al 2004) and aquaculture (Lee 2000), and the use of FL/NN/GA in automation and control of reverse osmosis plants (Zilouchian and Jafar 2001) and cryogenic cooling plant (Linkens et al 2000).…”