Kazem Abhary
Papers
11
Total Citations
121
H-Index
6
About
Kazem Abhary is a specialist in intelligent manufacturing systems, with a sustained research focus on the scheduling and optimization of robotic flexible assembly cells (RFACs). His work addresses one of modern manufacturing's most pressing challenges: enabling flexible production systems to efficiently handle diverse product mixes, dynamic workloads, and competing performance objectives in increasingly competitive global markets. Abhary's most significant contributions lie in developing novel scheduling methodologies that harness fuzzy logic, simulation modeling, and multi-criteria decision-making (MCDM) frameworks. His fuzzy sequencing rule (FSR), introduced in 2012, represented a meaningful advance by integrating multiple scheduling variables — including processing time, due dates, and batch size — into a single intelligent decision rule. Building on this, he applied Taguchi optimization methods to both single- and multi-objective scheduling problems, producing robust, computationally efficient solutions. His 2016 multi-objective optimization study and 2013 simulation-based analysis remain his most cited works, with 26 and 23 citations respectively, reflecting their methodological influence. Across more than a dozen publications spanning 2011 to 2017, Abhary has consistently bridged artificial intelligence techniques with practical manufacturing engineering problems, offering researchers and industry practitioners actionable frameworks for smarter, more adaptive robotic assembly systems.
Research Focus
Key Achievements
Top Papers
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- 4A Scheduling Framework for Robotic Flexible Assembly Cells18 citations · 2013
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- 9Intelligent Model of Scheduling Rfacs - Part I: Methodology and Strategy4 citations · 2013
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