Maintenance Engineer-Intelligent Maintenance_PS_RBCD

Job description

Job Summary Takes responsibility for maintenance of defined MAE Focused on the maintenance and repair of machines related to fuel cell business Ensuring the efficient operation of equipment, promptly addressing technical issues, and participating in equipment optimization and improvement. In addition, actively explores and drives the transition from traditional to intelligent maintenance by leveraging PLC software, equipment interconnectivity, and digital tools to achieve predictive and proactive maintenance. Roles and Responsibilities Main maintenance KPI of responsible machines Malfunction regular review Leading problem solving of key malfunction, utilizing PLC software for deep-level fault diagnosis and program optimization. KPI PDCA L3/L4 preparation Activities for machine performance stabilization and continuous improvements, including data-driven analysis and digitalization initiatives. Spare parts preparation Defining spare parts Tracking spare parts abnormal usage. Working at alternative solution if spare parts not available. Support spare parts localization project Organizing repaired key spare parts try-out Maintenance competence development for responsible machines Record and analyze equipment failure data, providing improvement recommendations. (Explore data pattern for predictive maintenance) Following the competence development plan Attending know-how exchanging activities in IPN Train and guide other team members to enhance equipment maintenance skills. (Promote digital and intelligent maintenance awareness within the team) Collaborate with suppliers and internal teams to ensure timely repairs and technical support. Performing at TPM activity from maintenance Regular review and update of PM items Key malfunction (long breakdown or repeated problem) summary (PSS) and defining standard reaction plan for same problem (error search plan), preferably digitizing these plans into system-based decision trees. Joining TPM activities, taking a main role in TPM review meeting, supporting to improve TPM maturity Supporting planning and releasing of new investment machines Supporting technical specification defines for the new investment machine. (Ensure new machines meet interconnectivity and data acquisition standards for intelligent maintenance) Reviewing and summarizing historical machine problem and machine concept failure and related improvements; Evaluating the MAE potential improvements MAE releasing and MAE A/B/C classification according the standard check list. Supporting MAE commissioning Technical preparation for machine overhauling Preparing the evaluation check list for machine overhauling Preparing the overhauling proposal Coordinating the overhauling project Contributing to cross-functional improvements, Eg.CO2 reduction, System CIP projects, Shop floor CIP projects, etc. [Preferred] Explore and pilot emerging technologies (e.g., AI algorithms, machine learning) in equipment condition monitoring and predictive maintenance to adapt to rapid technological iterations. Education degree: Bachelor or Master degree in Mechanical Engineering, Electrical Engineering, Computer Science or a related field. Total working experience > 5 year Maintenance related working experience >3 years Strong fault analysis and resolution skills. Solid foundation and hands-on experience in PLC software for troubleshooting and logic optimization. Good teamwork and communication abilities. Fluent English both in speaking and writing Interest and foundational knowledge in equipment interconnectivity (IoT), data acquisition, and digital/intelligent maintenance systems. Highly curious, open to trying new things, and embraces challenges to adapt to rapid technological changes. (Preferred) Basic knowledge or strong passion for Artificial Intelligence (AI), machine learning, or data analytics, with a willingness to apply them in industrial maintenance scenarios. Candidates with relevant hands-on experience or self-driven AI learners will be given priority. 博世集团网上招聘数据处理同意声明 个人信息及目的：你的如下个人信息将被处理并用于招聘：姓名、电子邮箱、电话号码、所在地区、经验和教育信息、简历等应聘者自主提交的附件信息、证件号、职位、部门、计划入职日期、劳动合同持续时间、工作地点、月薪、年薪、浮动奖金比例、餐贴、车贴。 博世将依据相关的数据保护法规，在全球范围内对您的数据进行保密。招聘流程中，您的个人信息只有在必须时才会被提供给博世以外的第三方机构(如代理机构)。博世精心挑选了第三方机构并与之签订了保密合同。博世采取了种种保密措施以保护您的数据，确保其不会遭受操纵、丢失、破坏、未经授权的访问或泄漏。我们的安全措施将随着新技术的应用而不断升级。您的本地浏览器和我们的人才招募系统之间的数据传输通过https加密。 特定职位申请：申请博世集团的职位就意味着您将自己的个人信息提供给博世集团旗下相应的法律实体（具体请见博世集团法人清单）。请注意，若有任何文件或资料变更，请在所有申请书里一并变更。人力资源部门的员工可能与您联系，询问您是否同意将您的求职申请转向博世集团内部另一合适职位。如果您申请了特定职位，那么只有在您同意的情况下，博世才会将您的求职申请转向另一职位。 您可以随时撤回求职申请，博世将根据相关法律删除您的个人信息。与您的申请相关的所有资料将被保留至24个月。您的权利：若您希望停止向博世提供您的个人信息，可联系我们或通过博世网上招聘数据隐私声明中的BKMS系统提出申请。您可以在SmartRecruiters平台查阅和修改您的简历。您对您的个人信息的处理享有知情权、决定权，您有权限制或者拒绝我们对您的个人信息进行处理。您还可以更正、补充您的个人信息。 跨境传输：为了实现前述目的，我们所收集的您的个人信息可能会在多个国家或地区间进行跨境转移，例如德国、新加坡。 德国：罗伯特-博世有限公司（德国格宁根市罗伯特博世广场1号（Robert-Bosch-Platz 1, Gerlingen-Schillerhohe, Germany，邮编：70839），用于集团统一招聘管理（博世中国与数据接收方均基于该目的开展数据出境活动； 英国：SmartRecruiters（英国伯克郡温莎亚瑟路圣斯蒂芬大厦 邮政区码: SL4 1RU），用于招聘、后期交流联系及分享职位/活动信息、潜在人才社区邀请。 您可通过上述联系方式依法向境外接收方行使您在个人信息处理活动中的权利。 存储您的个人信息：我们将仅在为实现目的必要的范围内以及法律法规要求的时间内保留您的个人信息。 雇佣：被雇佣后，您提供的数据将被从当前招聘系统转移至职位所属公司的人力资源管理系统。联系方式： 请通过访问博世中国官方主页：博世在中国＞加入博世＞工作机会，在网上招聘数据隐私声明中“9.联系方式” 博世集团法人清单： 请通过访问博世中国官方主页：博世在中国＞加入博世＞工作机会，在网上招聘数据隐私声明中获取现阶段使用网上招聘系统的博世集团法人（第五页） Bosch Powertrain Systems Co., Ltd. (RBCD), the joint venture of Robert Bosch GmbH and Weifu High Technology Group Co., Ltd., is a high tech enterprise specializing in the development, production and sales of common rail systems, exhaust gas after treatment systems, fuel cell stacks and key components. The company, based on its local R&D and project management competence, with innovative technologies, can support customers to continuously improve internal combustion engines efficiency, to reduce emission, and to accelerate the market launch of new energy products. The garget of the company is to provide the Chinese market and customers with diversified advanced powertrain products.