Published in eight issues per year, the Journal of Intelligent Manufacturing provides a unique international forum for developers of intelligent manufacturing systems. By publishing quality refereed papers on the application of artificial intelligence in manufacturing, the Journal provides a vital link between the research community and practitioners in industry. In addition to research papers, the Journal of Intelligent Manufacturing features articles on new methodologies and developments, case studies, surveys, and tutorials on topics related to product design, manufacturing, and service systems. Papers in emerging areas such as biomanufacturing, nanotechnology, and energy are welcome. Periodically special issues on topics of interest to the readership are published. Officially cited as: J Intell Manuf
Journal of Intelligent Manufacturing
Description
Identifiers
ISSN | 0956-5515 |
e-ISSN | 1572-8145 |
DOI | 10.1007/10845.1572-8145 |
Publisher
Springer US
Additional information
Data set: Springer
Articles
Journal of Intelligent Manufacturing > 2019 > 30 > 8 > 2789-2803
This paper focuses on modelling the enterprise level risks from the perspective of an original equipment manufacturer. We intend to converge on an overall risk measure that is representative of the cumulative effect of risks emanating from considerations pertaining to respective functional divisions within the enterprise. Further, due to multitude of interplays between the core objectives of various...
Journal of Intelligent Manufacturing > 2019 > 30 > 8 > 2965-2979
The aim of this paper is to process modelling of AWJM process on machining of green composites using fuzzy logic (FL). An integrated expert system comprising of Takagi–Sugeno–Kang (TSK) fuzzy model with subtractive clustering (SC) has been developed for prediction surface roughness in green AWJM. Initially, the data base is generated by performing the experiments on AWJM process using Taguchi $$(\hbox...
Journal of Intelligent Manufacturing > 2019 > 30 > 8 > 2945-2964
In this study, a satisfaction index estimation model is proposed integrating structural equation modeling and mathematical programming methods with fuzzy customer data. Firstly, a deep literature survey is conducted in this field of study. Then, a new model is proposed by taking into consideration gaps in the literature. The estimation model is composed of five stages and first stage is building conceptual...