Risk Management and Product Development based on Hybrid Soft Computing Techniques
1Government College Women University, Sialkot, Pakistan
2Division of Science & Technology, University of Education, Lahore, Lahore, Pakistan
3Shahid Bahonar University of Kerman, Kerman, Iran
Risk Management and Product Development based on Hybrid Soft Computing Techniques
Description
Risk management is a widespread mechanism to recognize and eliminate possible errors, problems, and failures in design, process, and systems. The principal focus of risk assessment is to deliver services and products to clients without any defects. The detection of failures and their effects has been proved a powerful strategy widely used for reliability and safety analysis of systems, processes, and products in numerous industries, for instance, space engineering, nuclear industry, and automotive production. It is additionally a good approach to provide relevant information for risk assessment decisions. Numerous designers and architects are likewise inspired by FMEA because of its capability of stimulating the use of continuous improvement in the phase of product design. It helps engineers to clearly know and understand the potential causes and risks influencing their production reliability.
Design concept production and assessment are essential for identifying an optimal concept in the early design phase of the new product development. Design concept evolution in product development, in which designers evaluate several design concept ideas generated at an early stage of product design, and then decide on which one of the available ideas should be selected for further improvement. It is so important for product design that lots of researchers provided various numerical evaluation methods which can be perceived as a problem of multiattribute group decision-making. Hybrid soft computing techniques integrated with risk management and product development approaches deal with the uncertainty arising in experts’ judgements without much prior information and additional suppositions such that all vagueness of decision information can be collected based on initial data. The integrated soft computing models are powerful artificial intelligence techniques that can handle vague assessment information under uncertain decision environments.
This Special Issue calls for original and high-quality research papers that report the emerging applications of hybrid soft computing methods in risk management and new product development. We also want to emphasize on the mathematical approaches with strong theoretical backgrounds. Original research as well as review articles are welcome.
Potential topics include but are not limited to the following:
- Rough numbers and their integrated forms
- Cloud model theory and its integration with soft computing techniques
- Grey relational analysis
- Utility theory integrated with fuzzy numbers, rough numbers, and their extensions
- Extension of fuzzy numbers integrated with approximation theory
- Hybrid type-2 soft models
- Expert sets and their extensions