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DSF 核心：用于工业设备寿命延长策略优化调度的综合决策支持。

DSF Core: Integrated Decision Support for Optimal Scheduling of Lifetime Extension Strategies for Industrial Equipment.

机构信息

Centre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece.

出版信息

Sensors (Basel). 2023 Jan 25;23(3):1332. doi: 10.3390/s23031332.

DOI:10.3390/s23031332
PMID:36772372
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9920745/
Abstract

This paper proposes a generic algorithm for industries with degrading and/or failing equipment with significant consequences. Based on the specifications and the real-time status of the production line, the algorithm provides decision support to machinery operators and manufacturers about the appropriate lifetime extension strategies to apply, the optimal time-frame for the implementation of each and the relevant machine components. The relevant recommendations of the algorithm are selected by comparing smartly chosen alternatives after simulation-based life cycle evaluation of Key Performance Indicators (KPIs), considering the short-term and long-term impact of decisions on these economic and environmental KPIs. This algorithm requires various inputs, some of which may be calculated by third-party algorithms, so it may be viewed as the ultimate algorithm of an overall Decision Support Framework (DSF). Thus, it is called "DSF Core". The algorithm was applied successfully to three heterogeneous industrial pilots. The results indicate that compared to the lightest possible corrective strategy application policy, following the optimal preventive strategy application policy proposed by this algorithm can reduce the KPI penalties due to stops (i.e., failures and strategies) and production inefficiency by 30-40%.

摘要

本文提出了一种适用于设备退化和/或故障且后果严重的行业的通用算法。该算法基于生产线的规格和实时状态，为机械操作人员和制造商提供决策支持，包括应采用的适当寿命延长策略、每种策略的最佳实施时间框架以及相关机器部件。该算法通过在考虑对这些经济和环境关键绩效指标 (KPI) 的短期和长期决策影响后，对经过模拟的生命周期评估后的关键绩效指标 (KPI) 进行明智选择的替代方案进行比较，选择相关建议。该算法需要各种输入，其中一些可能由第三方算法计算，因此它可以被视为整体决策支持框架 (DSF) 的最终算法。因此，它被称为“DSF 核心”。该算法已成功应用于三个异构工业试点。结果表明，与尽可能轻的纠正策略应用政策相比，遵循该算法提出的最佳预防策略应用政策可以将因停机（即故障和策略）和生产效率低下而导致的 KPI 罚款降低 30-40%。

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