Event-based modelling of distributed sensor networks in battery manufacturing

Abstract

Battery manufacturing systems are characterised by their complex dynamics subject to constant changes caused by technology insertion, engineering modifications, as well as disruption events. To support daily operation, distributed sensors are used to provide real-time data describing the status of each process. Despite the big potential in improving productivity, the advantages of distributed sensor networks are not fully realised for overall system efficiency due to a lack of system-level modelling. Motivated by this need, we develop an event-based modelling (EBM) approach to quantify the systematic impacts of stations and supporting activities with an index called permanent production loss. EBM instantaneously captures the system dynamics using distributed sensor information and provides a severity ranking of stations and supporting activities. We also study the system dynamics of serial production lines with multiple slowest stations and quantify the impacts of disruption events to the production system. A case study is conducted to demonstrate the application of EBM in a battery production system and its ability to facilitate decision-making at plant floor on resources and budget allocation.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 22 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.