Abstract The competitive global scenario faces the corresponding impacts such as difficulties in scheduling and loading, high tooling and equipment investment, enormous scrap availability, complex to control the quality, and extensive setup time. So, a higher level of connectivity is required in between the design and manufacturing activities to raise the profitability of the firms and enrich the product support design. In any manufacturing firm, poor reliability causes failure availability in all stages, namely, design, construction, planning, and maintenance, etc. In this research work, RAM is analyzed from the Weibull distribution based Mean time to repair (MTTR) and mean time to failure rates (MTTF) for the ten different industries. The measured RAM performances are optimized by the Imperialist competitive algorithm (ICA) by the application of the rank order clustering (ROC) method. The failure rates are clustered and ranked by using the rank order clustering method. Besides, the cost and RAM performance values are predicted by ICA and hybrid ROC method, and such a proposed algorithm is mathematically modeled in the Mat Lab platform. Hence from the evaluation, the proposed method scores better industrial performances than the actual and other implemented methods

中文翻译：

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基于不同工业部门的成本和 RAM 分析的排序聚类和帝国主义竞争优化

摘要 竞争激烈的全球情景面临着相应的影响，例如调度和装载困难、工装和设备投资高、废品率高、质量控制复杂、准备时间长。因此，设计和制造活动之间需要更高水平的连接，以提高公司的盈利能力并丰富产品支持设计。在任何制造企业中，可靠性差会导致设计、施工、规划和维护等各个阶段的故障可用性。 本研究工作从基于威布尔分布的平均修复时间 (MTTR) 和平均时间分析 RAM十个不同行业的故障率 (MTTF)。测量的 RAM 性能由帝国主义竞争算法 (ICA) 通过应用秩序聚类 (ROC) 方法进行优化。故障率通过使用排序聚类方法进行聚类和排序。此外，成本和 RAM 性能值是通过 ICA 和混合 ROC 方法预测的，并且这种算法在 Mat Lab 平台上进行了数学建模。因此，从评估来看，所提出的方法比实际和其他实施的方法具有更好的工业性能