使用预测分析降低企业资产管理的维护成本
公司规模
Large Corporate
地区
- Europe
国家
- Switzerland
产品
- IBM Maximo Asset Management
- IBM Maximo Everyplace
技术栈
- Predictive Analytics
- Mobile Technology
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 功能应用 - 企业资产管理系统 (EAM)
- 分析与建模 - 预测分析
适用行业
- 零售
适用功能
- 维护
用例
- 预测性维护
- 资产健康管理 (AHM)
服务
- 系统集成
- 数据科学服务
关于客户
Migros Zurich (GMZ) 是瑞士一家大型零售商，经营着 97 家商店、26 家专业市场和 47 家食品店。该公司服务于约 150 万客户，年收入约为 24.7 亿瑞士法郎（25 亿美元）。GMZ 拥有约 8,800 名员工。该公司的声誉取决于其能够以合理的价格和精准的效率提供高质量的商品和服务。然而，该公司的维护实践成本高昂，这导致人们认识到需要采取主动策略来优化企业资产的性能、可靠性和使用寿命。
挑战
Migros Zurich (GMZ) 经营着庞大的商店、专业市场和食品店网络，为大约 150 万客户提供服务。该公司的声誉取决于其能够以合理的价格和精准的效率提供高质量的商品和服务。然而，该公司的维护人员需要一种方法来汇总、整合和分析来自资产清单、服务请求、工作订单、维护记录、设备服务合同、保修、服务水平协议以及服务和技术文档的信息，其中大部分信息以物理形式存档在公司的中央办公室。这些记录包含数千个数据点，需要这些数据点来全面了解其资源的当前状况，并将其维护实践从被动转变为主动。此外，为了提高现场效率，该公司需要一个移动解决方案，使现场技术人员能够随时随地实时访问公司的资产管理系统。
解决方案
为了转变资产管理业务，Migros Zurich 与 IBM 和 IBM 业务合作伙伴 Ascom Solutions 合作，实施基于 IBM® Maximo® Asset Management 和 IBM Maximo Everyplace® 软件的分析解决方案，该解决方案可提供公司资产的全面视图。Ascom Solutions 在部署期间提供了出色的咨询和实施服务。GMZ 现在使用预测分析来评估多年的维护数据并准确确定资产生命周期。维护分析师可以评估整个公司的设施、系统和设备健康状况，以更好地预测系统何时需要维护、维修或更换。凭借这些见解，Migros Zürich 可以确定维护任务的优先级并安排维护任务，以延长单个资产的使用寿命并优化维护这些资产所需的人员分配。该解决方案集成了服务合同、保修、SLA 和历史服务记录，而这些记录以前是现场维护团队无法访问的。现在，技术人员可以使用移动设备（例如智能手机和平板电脑）从服务呼叫现场远程访问这些内容以及技术手册和图表，从而无需花费时间前往办公室查阅纸质文档。
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