Future of sharing schedule information in automotive industry supply chains using advanced data analytics
Research Project, 2018
– 2021
The project’s point of departure is generally low forecast/delivery schedule accuracies, with negative impact on tied-up capital, transport costs, volume flexibility and environment in automotive industry supply chains. The aim is to generate a best practice description of how planning information is shared and used in the supply chains, and develop and field test new methods and models for measuring, visualizing and predicting delivery schedule variations in supply chains.
The new methods and models will generate improved demand visibility and allow for new ways of planning (e.g. conducting proactive scenario-based planning). As such the project intends to contribute to companies’ production and supply chain planning systems' abilities to compensate for and manage uncertainties, variations, and disturbances in supply chains.
The project is organized in six work packages. The first is a survey study of information usage in automotive supply chains. The second conducts data analytics of a large amount of delivery schedule data in order to identify common variations and patterns. The third conducts case studies to explain causes and consequences. The fourth develops new machine learning-based solutions/models for visualization and prediction. The fifth studies implementation and the sixth conducts dissemination.
Participants
Patrik Jonsson (contact)
Chalmers, Technology Management and Economics, Supply and Operations Management
Robin Hanson
Chalmers, Technology Management and Economics, Supply and Operations Management
Magnus Kjellberg
Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd
Paulina Myrelid
Chalmers, Technology Management and Economics, Supply and Operations Management
Muhammad Azam Sheikh
Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd
Hafez Shurrab
Chalmers, Technology Management and Economics, Supply and Operations Management
Collaborations
Automotive Components Floby AB
Floby, Sweden
Bulten AB
Göteborg, Sweden
Heléns Rör AB
Halmstad, Sweden
Meridion AB
Göteborg, Sweden
Northern LEAD
Gothenburg, Sweden
Odette Sweden AB
Stockholm, Sweden
Plastal Sverige AB
Göteborg, Sweden
Scania CV AB
Södertälje, Sweden
Veoneer
Stockholm, Sweden
Volvo Cars
Göteborg, Sweden
Volvo Group
Gothenburg, Sweden
Funding
FFI - Strategic Vehicle Research and Innovation
Project ID: 2018-02695
Funding Chalmers participation during 2018–2021
VINNOVA
Project ID: 2018-02695
Funding Chalmers participation during 2018–2021
Related Areas of Advance and Infrastructure
Information and Communication Technology
Areas of Advance
Transport
Areas of Advance
Production
Areas of Advance