Colloquium aankondiging

Faculteit Engineering Technology

Afdeling Design, Production and Management
Master opleiding Mechanical Engineering

In het kader van zijn/haar doctoraalopdracht zal

Grip, R. (Ramon)

een voordracht houden getiteld:

Master Thesis Defence R. Grip

Datum28-01-2026
Tijd10:00
ZaalHT700B + HT307

Samenvatting

Lithium-ion battery packs are increasingly required to support both scalable manufacturing and future circular strategies, such as repair and recycling. Manufacturing-oriented design choices that favor short cycle times and automation can conflict with requirements for accessibility and reversibility during disassembly. This creates a need for structured decision-making approaches that enable manufacturing improvements while accounting for life-cycle considerations. This thesis presents a structured methodology for the analysis and optimization of lithium-ion battery pack manufacturing processes. The methodology integrates product architecture analysis, manufacturing process mapping, task and time analysis, and lead-time evaluation to support the systematic identification of manufacturing improvement opportunities. Automation- and disassembly-oriented objectives are translated into measurable criteria to enable transparent prioritization of improvement directions. The methodology is demonstrated through a case study on the manual assembly of a 240-cell battery pack for an electric motorcycle. A detailed task and time analysis reveals a total assembly time of 6 hours and 27 minutes per pack, with joining operations representing the dominant contribution. To evaluate process optimization at the operation level, a full factorial Design of Experiments is conducted on the spot-welding process to assess the influence of key parameters on connection success, electrical resistance, visual quality, and tensile strength. Based on experimentally identified parameter settings and representative automated welding rates, a scenario-based estimate indicates that automation of the joining operation could reduce the total assembly time to approximately 4 hours and 49 minutes, corresponding to a reduction of about 25%. The results demonstrate how the proposed methodology supports data-driven manufacturing process optimization and provides a structured basis for further automation-oriented and circularity-aware battery pack development.