- Lead collection of data through connection to PLC, sensors and IT/IS systems (ERP, MES...) for Plastic Omnium–Intelligent Exterior Systems’ core process & machines: plastic injection, painting and assembly technology (bonding, welding, clipping, screwing…)
- Ensure quality of data through relevant checking tools and proper storage in appropriate databases to run proper analytics for Predictive Quality and Predictive Maintenance
On his/her perimeter of responsibility:
- Lead data collection & acquisition through connection to machines PLC, sensors & IT/IS systems for core PO-IES process & ensure quality and security of data.
- Understand PO-IES core process: plastic injection, painting and assembly
- Contribute to assess & define data needed with Process Experts, plants & data analysts to achieve the productivity & efficiency goals
- Study & define ways of acquiring the data on machines PLC, sensors (IOT box or device) & IT/IS systems as well as computing data if needed (edge computing)
- Source & put in place with plant automation technician & suppliers the equipments needed for DAQ ( Data Acquisition) & data computing if needed ( edge servers)
- Study & define with IT department the best network for data flow (wired LAN, Wireless network...) in terms of flow, reliability and security
- Study & define with IT department the best repository / database system to store data for further analytics
- Check data consistency & accuracy through relevant software & quality check protocols
- Ensure delivery or right data to database with Data Analysts : quality parameter outputs and process parameter inputs
- Contribute to predictive model by applying close loop control when possible or needed
- Teach process engineers in central department and plants basis of data acquisition & treatment
- Active awareness & benchmark on connection (IOT) and Data Acquisition and treatment / computing
- Measure progress & results to improve
- Ensure adhesion of future plant teams & departments to the technologies implemented by identifying the skills and competence needed and elaborating the proper training modules.
Educational background: Master’s degree in Automation, Data Science, Engineering, or Manufacturing
Proficient in English language
Skills: Automation, connection to PLC, sensors, data acquisition experience, Team player and project management skills.
New technologies & digitalization affinity
Result, productivity, continuous improvement & lean manufacturing oriented
Capacity to explain and teach on Data Acquisition topics
Previous Experience: In automation, PLC, data acquisition in production.