Project Objectives :
Expansion of the assembly and packaging lines to implement the global concept of Automatic Reason Code Assignment (ARCA) and integration of the data into an eOEE system
Creation of a consistent data model, ensuring the streamability of production data, and implementation of ARCA for the automated and standardized recording of downtime and alarm causes
Creating transparency (alarm error) through translation matrices
Implementation of the data pipeline : Alarm data Streaming engine Server
Integration into the data landscape (Snowflake, OPC-Kepware, Power BI)
Pilot solution for one manufacturer cell with subsequent adaptation to other manufacturers.
Job Description :
Data analysis and preparation : Familiarization with the existing data from the production facilities and development of a comprehensive understanding of the current data structures
Inventory of the data structure (>
700 alarms per plant; high alarm and stop frequencies)
Assignment of alarms to units in the OEE tool (Power BI) via translation matrices (alarm unit ARC code)
Data migration planning : Preparation and structuring of plant data for transfer to a standardized data infrastructure
Development of a linking tool between OPC and Data Lake interfaces
Programming in the Plant Connectivity (PCo) agent
Export of raw data (CSV, PDF) server streaming to Snowflake; Direct query / import to Power BI
Test runs, error analysis, and optimization of the mapping logic
Performance optimization : Identification of potential improvements in plant performance through data-driven analyses
Problem solving : Development of creative solutions for complex data challenges, especially when conventional methods fail, e.g. B. : Reverse engineering of the existing solution for a Mikron assembly machine and evaluation of its transferability to AL5
Stakeholder communication : Proactive communication with plant manufacturers and internal departments to gather information
Project management : Independent planning, prioritization, and execution of work steps
Visualization and presentation of results (Power BI, management updates)
Qualifications and requirements
Experience :
Sound knowledge of industrial and technical systems
Experience with data migration projects and data harmonization
Proven experience in the performance optimization of production plants
Experience with assembly and packaging systems for autoinjectors and injection pens is an advantage
Prior experience with systems from Körber, Krones, Schubert, Mikron, Harro Höfliger (advantageous / desirable)
Prior experience in the pharmaceutical / medtech sector (advantageous / desirable)
Technical skills :
Expertise in data analysis and preparation
Understanding of industrial Automation systems and plant engineering
Experience with data standards and norms
Knowledge of performance monitoring and analysis of production plants
OPC UA, Kepware, OSIsoft PI, streaming engines (e.g., Kafka / MQTT), Snowflake, Power BI
SAP MII / PCo, data lake architectures, eOEE interfaces
Network / OT security, middleware integration, audit trails, hash codes
Programming languages :
Java (SAP PCo custom agents, SAP MII logic)
XML (configuration files for PCo / MII)
SQL (Snowflake / databases)
Python or C# (data integration, parsing machine-readable alarms)
Structured Text (IEC 61131-3) and ladder logic (PLC)
JavaScript (frontend logic in MII / BI environments)
Und • Frankfurt (Oder), Germany