Papers
15
Total Citations
137
H-Index
6
About
Khalid Abd is a researcher specializing in intelligent manufacturing systems, with a particular focus on scheduling optimization within robotic flexible assembly cells (RFACs). His body of work sits at the intersection of artificial intelligence, fuzzy logic, and flexible manufacturing, addressing one of the most pressing challenges in modern industry: how to dynamically and efficiently schedule complex robotic assembly systems in the face of competing objectives and real-world uncertainty. Abd's most significant contributions include the development of the Fuzzy Sequencing Rule (FSR), an innovative scheduling approach that integrates processing time, due dates, batch size, and assembly requirements into a coherent decision-making framework. His most-cited work (2016, 26 citations) applies fuzzy-based Taguchi methods to multi-objective dynamic scheduling, demonstrating measurable improvements in makespan, tardiness, and system utilization. Complementing this, his simulation-based studies and multi-criteria decision-making (MCDM) frameworks — incorporating techniques such as AHP, TOPSIS, and ELECTRE — provide robust tools for selecting optimal scheduling rules under uncertainty. Collectively accumulating over 120 citations, Abd's research has meaningfully advanced the field of intelligent manufacturing scheduling. His work is particularly valuable for students and engineers seeking practical, AI-driven solutions to real-world production planning challenges in flexible and robotic manufacturing environments.
Research Focus
Key Achievements
Top Papers
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- 4A Scheduling Framework for Robotic Flexible Assembly Cells18 citations · 2013
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