Job Description
You will be part of a global Asset Management CoE (Center of Excellence) team to:
- Design and implement Asset Operations Management (AOM) systems to deliver diagnostic, prognostic, and predictive insights for a variety of industrial assets, including rotating, static, and electrical equipment.
- Engage in data analysis and reliability-centered maintenance studies, applying mechanical, mathematical, and statistical analyses to synthesize IT and OT data into predictive maintenance models for our clients.
- Employ a range of predictive technologies such as vibration analysis, ultrasound analysis, motor circuit analysis, oil analysis, and infrared thermography. The objective is to pre-empt asset failure and unplanned outages, enhance maintenance strategies, reduce risks and operational costs, and prolong the lifespan of assets.
- Lead Digital Asset Management Maturity Assessments (DAMMA) sessions with clients. Collaborate with AOM Solution Architects and Data Scientists to craft AOM solutions that leverage Industry 4.0 technologies like IIoT, AI/ML, and digital twins to drive value.
- Develop and define key metrics and KPIs for asset condition, health, and performance monitoring.
- Below duties by default due to ISMS requirements:
- Maintain confidentiality of the Information received, either in writing or verbally, whether technical, business, legal, organizational, personal or any other information that could result in damage to Yokogawa in case of disclosure to unauthorized persons, regardless of whether the information is classified as confidential or not.
- Take all reasonable, necessary, and appropriate steps to safeguard confidentiality, integrity, and availability of the Yokogawa’s assets and information.
Requirements
- Bachelor’s degree in mechanical, engineering, or a related discipline
- Master’s degree in computer science, data analytics or a related field preferred
- 3-5 years of experience in implementing Predictive Maintenance within an industrial context.
- Demonstrated expertise in designing, developing, testing, and deploying anomaly detection models.
- Proficient in MATLAB, Jupyter Notebook, and Python programming
- Comprehensive knowledge of industrial systems, including IoT devices, PLCs, SCADA, DCS, Historians, and CMMS
- Deep understanding of vibration analysis with the capability to develop rules and algorithms
- Proven ability to independently drive results in a fast-paced environment and collaborate across different regions and countries
- Excellent communication skills with the ability to convey complex technical concepts clearly to varied audiences.
Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job.)
- Predictive Maintenance Techniques
- Reliability Engineering
- MATLAB and Jupyter Notebook
Personal Attributes (Special personal characteristics/ interpersonal skills)
- Demonstration of high quality of technical ability/competence/productivity
- Passionate about converting technologies into industrial solutions
- Communication and interpersonal skills
- A quick learner and a team player
By responding to Yokogawa’s advertisement, consent is considered given to Yokogawa to collect the required personal data for the purpose of recruitment with expectation that Yokogawa will protect personal data with security safeguards that are reasonable and appropriate to the sensitivity of the personal data, to protect it from unauthorized access, use or disclosure and complies with applicable regulatory requirements with respect to the retention of personal data.
