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.