The complexity of production and logistics systems is often caused by frequent changes and dependencies among the many interacting systems. As a consequence and despite the systematic work for increasing process stability, manufacturing industry faces deviations from production plan and the “normal situation” which is the set standard within lean. This project will support the management of deviation handling and the re-scheduling of tasks by implementing automation solutions of relevant information flows and processes.
The expected impact of implementing relevant automated solutions is faster reaction and flexibility to deviations such as disturbances, changes and other events interfering with the production plans, as well as reduced propagated effects. Furthermore, increased automation will give access to relevant information and increase knowledge of events and appropriate actions. This will result in a measurable improved overall competitiveness of a manufacturing company.
This project will develop a model framework that identifies and describes the needs for support, information, and automation. This is based on case studies carried out within industrial partner companies and a methodology that guides companies to specify such need, to be used for subsequent investments to employ such technological solutions to better manage frequent production re-scheduling, deriving as a consequence of occurring deviations. The intention is to enhance the state-of-art and provide important solutions and experiences for increased digitalization and automation in industry. A crucial part of the project is the dissemination of solutions to Swedish industry, especially SMEs
Professor vid Chalmers, Technology Management and Economics, Supply and Operations Management
Tekniklektor vid Chalmers, Technology Management and Economics, Supply and Operations Management
Docent vid Chalmers, Technology Management and Economics, Supply and Operations Management
Funding Chalmers participation during 2018–2020
Areas of Advance
Areas of Advance