Machine Data Analytics: Identification of equipment data relevant for production performance
Company: Bayer, Consumer Health, Product Supply
Contact person: Kathrin Kleefuss/ Lynn Würth
Location: GP Grenzach Produktions GmbH, Grenzach, DE
Study Program: IE
ESCF Community: Data2Move
Start date: September 2020
Housing arranged by company: No
Internship compensation: 1694.- € per month
The purpose of Bayer Consumer Health Product Supply is to build the products our consumers love and that transform their lives. Product Supply provides about 9,400 products to Bayer Consumer Health. Our 5,100 employees at 12 Bayer-owned production sites, as well as more than 200 external contract manufacturers, produce and ensure a steady and flexible supply of these products to our customers and consumers.
Consumer Health Product Supply´s vision is to continuously advance our trusted daily health solutions with passion, competence and innovation. One of our strategic enablers is the digitalization of our network.
In this context we are now offering following internship at our supply center Grenzach, Germany, in the south-west of the country close to the Swiss and French borders and center of excellence for Bayer`s ointment and cream production.
Accessing all relevant production data and analyzing this data is an important foundation for digitalization initiatives within the supply centers of Bayer Consumer Health. The project offered in this internship involves collection, filtering and first analysis of production data with the help of common data analysis methods. A technical understanding of the considered production equipment and its associated data should be developed in order to prioritize the performance-relevant production data and reflect the results together with production experts. The focus will be on the analysis of alarms and parameters of filling and packaging production lines.
The results should be collected in a user-friendly form such that they can be shared in a knowledge base and used for future digitalization activities.
Goals of the project
The goal of the project is to analyze production data, identify relevant parameters for production improvement (e.g. equipment downtime reduction) and contribute towards an equipment-specific knowledge base.
Identified set of important equipment data relevant for production performance.
Essential student knowledge
Engineering (e.g. mechanical / electrical) background with German language skills, preferably with first data analytical and programming experience.