Single-Valued Trapezoidal Neutrosophic Preference Relations for Evaluating Design Quality in Mechanical Automation Production Control Systems within Intelligent Manufacturing Frameworks

Abstract

 Design quality in mechanical automation control systems must be reevaluated due to 
the quick integration of intelligent manufacturing technologies into industrial automation. The 
goal of this research is to provide a thorough assessment methodology that will evaluate these 
systems' efficacy, flexibility, and technical resilience in the context of Industry 4.0. The 
performance of various control system options used in intelligent manufacturing environments 
is examined using eight important criteria, such as system stability, reaction time, energy 
efficiency, and real-time data processing capabilities. Neutrosophic numbers tools are 
incorporated into the process to guarantee systematic and objective comparison. We use Single
Valued Trapezoidal Neutrosophic Preference Relations to evaluate the criteria and alternatives 
and overcome uncertainty information. The results emphasize how important fault tolerance, 
maintainability, and integration compatibility are in determining the overall sustainability and 
performance of a system. Manufacturing companies looking to optimize control system design 
in accordance with digital transformation objectives may find this evaluation methodology to be 
a useful tool.

DOI: 10.5281/zenodo.16118267