在智能制造中优先考虑机器人使用 q-rung orthopair 模糊决策方法和未知重量信息
Ming Sheng1, Hui Zhu1, Yu He1
1College of Engineering, Shandong Xiehe University, Jinan, China.
PloS one
|August 29, 2025
概括
这项研究对智能制造机器人进行了排名, 该研究使用先进的模糊逻辑和决策方法来优化机器人技术投资以提高生产力和安全性.
科学领域:
- 智能制造系统
- 机器人的整合
- 决策支持系统
背景情况:
- 智能制造需要先进的机器人来提高生产力,精度和适应性.
- 机器人对于组装和检查等操作至关重要,
- 加强决策对于机器人技术的战略投资至关重要.
研究的目的:
- 对智能制造系统的不同类型机器人进行评估和排名.
- 开发一个整合的决策框架,包括不确定性.
- 为优化机器人技术整合和投资提供可操作的见解.
主要方法:
- 使用q-rung整形模糊集 (qROFS) 来处理不确定的专家评估.
- 使用和相似度来确定专家的重量.
- 使用FUCOM (主观) 和CRITIC (客观) 方法推导的标准权重.
- 通过"理想解决方案的联合妥协" (CoCoFISo) 方法建立了机器人排名.
主要成果:
- 机器人被认为是最有影响力的.
- 然后是检查,组装,接和材料处理/包装机器人.
- 建议的框架有效地处理了专家在评估中的不确定性.
结论:
- 这项研究为机器人在不确定性下做出决策提供了方法论上的进步.
- 这些发现支持机器人技术在智能制造中的战略整合.
- 这项研究有助于优化生产和投资决策.
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