Analyze key equipment comprehensive utilization rates (time and performance availability), identify inefficient equipment and bottleneck workstations, and analyze the composition and root causes of non-production time to provide data support for reducing equipment waiting and downtime
Job Summary
Analyze key equipment comprehensive utilization rates (time and performance availability), identify inefficient equipment and bottleneck workstations, and analyze the composition and root causes of non-production time to provide data support for reducing equipment waiting and downtime.
Establish per-piece product consumables consumption standards, monitor actual consumables usage differences, locate abnormal consumption points, and analyze the correlation between consumables lifespan and replacement cycles to optimize replacement frequency and balance consumables costs with equipment stability.
Participate in production digitalization projects, IIoT data platform construction, CMMS/EAM system optimization, and propose data and analysis requirements.
Matching Summary
Analyze key equipment comprehensive utilization rates (time and performance availability), identify inefficient equipment and bottleneck workstations, and analyze the composition and root causes of non-production time to provide data support for reducing equipment waiting and downtime.
Skills & Requirements
Must-have
equipment utilization analysis
consumables usage efficiency analysis
personnel time and utilization analysis
production process and cycle analysis
SQL for data extraction
Python (Pandas, Numpy, Scikit-learn, Matplotlib)
Power BI/Tableau visualization
Nice-to-have
cross-departmental collaboration
process optimization
data-driven decision making
digitalization projects
Key Requirements
Master's degree in Statistics, Applied Statistics, Data Science, or Data Science and Big Data