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Fuzzy-based multi-objective scheduling for human-robot manufacturing systems.

Yijun Deng1, Binrong Huang1, Shouliang Lai2

  • 1College of Packaging Design and Art, Hunan University of Technology, Zhuzhou, 412000, Hunan, China.

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Summary

This study optimizes human-robot collaboration in manufacturing using fuzzy programming. It balances production, inventory, and task allocation to maximize value and minimize delays, even with uncertain demand.

Keywords:
Fuzzy programmingHuman–robot interactionMulti-objective optimizationProduction planningScheduling

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Area of Science:

  • Manufacturing Engineering
  • Operations Research
  • Fuzzy Systems

Background:

  • Modern manufacturing faces challenges with fluctuating demand and human-robot interaction.
  • Optimizing production planning and scheduling is crucial for efficiency and profitability.

Purpose of the Study:

  • To develop a fuzzy programming model for simultaneous optimization of production, inventory, human-robot task allocation, and job sequencing.
  • To address uncertainties in demand and processing times within a multi-period, multi-product manufacturing environment.

Main Methods:

  • A pessimistic (credibility-constrained) fuzzy programming approach was employed to handle uncertainties.
  • The epsilon-constraint method was used for small-scale problems, while metaheuristic algorithms (NSGA-II, MOPSO, MOWOA) were applied to larger instances.
  • Sensitivity analyses were conducted to evaluate the impact of various parameters on objective functions.

Main Results:

  • Reducing completion times increases costs and lowers net present value.
  • Higher uncertainty rates lead to increased production times and shortages, decreasing net present value.
  • A 4% increase in bank interest rate significantly reduces net present value by 15.68%.

Conclusions:

  • The MOWOA algorithm shows superior performance for large-scale problems in generating efficient solutions for human-robot collaboration.
  • The study provides practical insights for optimizing integrated production planning and scheduling in fuzzy manufacturing environments.
  • Effective management of uncertainty and financial parameters is critical for maximizing manufacturing value.