Many evolutionary artificial intelligence (AI) technologies have been applied to assist with
job scheduling in manufacturing. One of the main approaches is genetic algorithms (GAs) …

Complex and uncertain decision-making environment increasingly requires the
collaborations of participants, the exchange and interaction of knowledge of different actors …

Explainable artificial intelligence (XAI) tools are used to enhance the applications of existing
artificial intelligence (AI) technologies by explaining their execution processes and results. In …

Recently, many methods based on artificial neural networks (ANNs) or deep neural
networks (DNNs) have been proposed to accurately predict the cycle time of a job. However …

Artificial intelligence (AI) applications based on deep learning for diagnosing type-II diabetes
are sometimes difficult to understand and communicate even as patients are eager to …

This chapter begins by defining explainable artificial intelligence (XAI). A procedure for
implementing XAI was also established. Then, through literature analysis, the application of …

Several artificial intelligence (AI) technologies have been applied to assist in the selection of
suitable three-dimensional (3D) printing facilities in ubiquitous manufacturing (UM) …

Assessing and comparing the overall performances of robotic applications amid the COVID-
19 pandemic is a key task for local governments and relevant stakeholders, but has yet to be …

There is a localization wave in the semiconductor industry for pushing wafer foundries to
transfer their production capacity to where chip designers are located. The main reasons for …

This chapter discusses an important topic in factory management, that of improving the
understandability of AI applications for group multi-criteria decision making in manufacturing …