Asset Predictive Analytics

4 days ago

Bengaluru, Karnataka, India Artificial Intelligence Global Company Full time

Responsibilities

  • Implement Asset Predictive Analytics (APA) (Utilizing software packages such as AVEVA or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics).
  • Conduct Data Collection and Analysis including:
  • Gathering data from various sources, including sensors, maintenance logs, and operational data,
  • Cleaning, validating, and preparing data for analysis,
  • Developing and implementing data quality control processes,
  • Analyzing data to identify trends, patterns, and anomalies related to equipment performance and potential failures.
  • Conduct Predictive Modeling including:
  • Developing and implementing predictive models using machine learning algorithms to forecast potential equipment failures,
  • Evaluating the performance of predictive models and refining them over time,
  • Integrating predictive models into existing systems and workflows.
  • Conduct Maintenance Optimization including:
  • Using predictive insights to optimize maintenance schedules and prevent unplanned downtime,
  • Recommending maintenance strategies based on predicted failure risks,
  • Collaborating with maintenance teams to implement optimized maintenance plans.

Qualifications

  • B.E/B.Tech (Mechanical/Chemical Engineering) or equivalent degree from recognized university.
  • Minimum 5+ plus years' experience in APA in industrial sectors (preferred oil & gas).

Required Skills

  • Knowledge of reliability principles, tools, and methodologies (e.g., FMEA, RCFA, RCM, PMO).
  • Rich Experience in AVEVA Predictive Analytics or similar solutions.
  • Strong understanding of mechanical systems and equipment.
  • Proficiency in data analysis and statistical modeling, including statistical modeling, machine learning algorithms, and data visualization.
  • Proficiency in programming languages such as Python, R, or others commonly used for data analysis and machine learning.
  • Experience developing and implementing predictive models using machine learning algorithms, such as regression, classification, and time series analysis.
  • Ability to effectively communicate technical information to both technical and non-technical audiences.
  • Experience with CMMS (Computerized Maintenance Management System), SCADA (Supervisory Control and Data Acquisition), and other relevant software and tools.
  • Rotating machinery Fault Analysis.
  • Static equipment Fault analysis.
  • Ability to engage with client/team stakeholders at a senior level.

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