下载PDF
Bosch rapidly scales automation with Catalytic
技术
- 应用基础设施与中间件 - 数据交换与集成
- 平台即服务 (PaaS) - 连接平台
适用功能
- 离散制造
- 采购
用例
- 工厂可见化与智能化
- 预测性维护
服务
- 云规划/设计/实施服务
- 系统集成
挑战
博世是一家全球制造公司，需要一家强大的协作自动化技术合作伙伴来加速其数字化转型。该公司正在寻找一种解决方案，帮助他们评估运营、设计和实施自动化流程，并找到扩大其工作规模的方法。挑战在于找到一家能够满足博世严格的云安全需求的技术合作伙伴，这对于博世这样规模和全球影响力的公司来说至关重要。此外，该公司还在使用 RPA 工具，因此新的技术合作伙伴需要紧密集成，以从博世的技术堆栈中释放更多价值。
关于客户
博世是一家全球制造公司，拥有超过 410,000 名员工。该公司在 31 个国家/地区开展业务，业务范围广泛，从汽车零部件到家用电器。博世以其对创新和质量的承诺而闻名，在制造业享有盛誉。该公司一直在进行数字化转型，寻找自动化任务和提高整个运营效率的方法。博世的利益相关者对自动化技术的潜力有着强烈的愿景，并将其视为整个组织变革的催化剂。
解决方案
博世与自动化技术提供商 Catalytic 合作，加速数字化转型。Catalytic 帮助博世评估其运营情况，设计和实施自动化流程，并发现扩大其工作规模的方法。借助 Catalytic 轻松构建自动化，博世能够在整个公司范围内快速扩展自动化并实现价值。Catalytic 能够协调包括人类参与的流程，这意味着最终可以实现更多流程的自动化。Catalytic 的平台满足了博世严格的云安全需求，并且与 RPA 工具的紧密集成为博世的技术堆栈释放了更多价值。在短短 18 个月内，博世对 Catalytic 的使用从试点自动化流程发展到每年在 31 个国家/地区执行 500 万个自动化任务。
运营影响
数量效益
相关案例.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Asset Management and Predictive Maintenance
The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.
