Scheduling in cloud manufacturing systems: Recent systematic literature review.

Area of Science:

• Manufacturing Engineering
• Operations Research
• Computer Science

Background:

• Cloud Manufacturing (CMFg) leverages cloud computing for interconnected manufacturing systems.
• Virtual platforms in CMFg enable direct customer-supplier linkages, expanding market access.
• CMFg introduces complex challenges in production planning and scheduling.

Purpose of the Study:

• To conduct a systematic literature review on scheduling in Cloud Manufacturing environments.
• To analyze optimization methods and problem-solving strategies for CMFg scheduling.
• To identify future research directions in CMFg scheduling.

Main Methods:

• Systematic literature review, starting from a seminal 2019 study.
• Analysis of optimization techniques and problem-solving strategies.
• Categorization and evaluation of existing research on CMFg scheduling.

Main Results:

• Cloud Manufacturing scheduling is a rapidly growing field of scientific interest.
• Bio-inspired metaheuristics dominate CMFg scheduling research, accounting for over 50% of studies.
• Existing methods show effectiveness but highlight areas for advancement.

Conclusions:

• CMFg scheduling is a dynamic research area with significant potential.
• Multi-objective optimization approaches are crucial due to conflicting objectives in CMFg.
• Decentralized methods, such as game theory, present promising avenues for future research.