From Bottlenecks to Efficiency : Investigating Barriers to Increase Production Capacity at Hitachi Energy

This thesis investigated how the cylinder production at Hitachi Energy Öjebyn could be improved to meet a projected 60% increase in demand by autumn 2025. The study focused on identifying inefficiencies in the current production flow, with the goal of increasing the output from 25 to 40 cylinders per day. The study was conducted as a case study using the DMAIC methodology. Data was collected through Gemba walks, interviews, ERP data analysis, and manual time measurements. Both qualitative and quantitative data were used. In the Define phase, problems such as reactive planning, lack of coordination between departments, and unclear responsibilities were identified. In the Measure phase, data was collected to analyze delivery history using ABC-classification and to map bottlenecks using value stream mapping. The analysis showed large variations in lead times, low value-added time, uneven shift structures, and high scrap rates, especially for non-varnished products. The inspection station and one of the hardening ovens were identified as physical bottlenecks, as well as the NC station, if not planned consciously. Improvement proposals were developed to increase output. Inventory for three levels: semi-semi-finished shafts, semi-finished products, and finished products, was proposed based on adjusted demand, service levels, and lead times. The fixture storage at the NC station was proposed to be organized using 5S to reduce setup times. A unified four-shift model was suggested for several stations to balance the flow. A second inspection station was recommended to reduce queues. Visual control and daily improvement meetings were proposed to support operator involvement in continuous improvement efforts. In the Control phase, an action plan was developed for each improvement proposal, including assigned responsibilities, KPIs, and milestones. Examples of KPIs include scrap rate, lead time, and inventory turnover. In summary, the study shows that both organizational and physical constraints affect capacity. By improving planning, inventory management, and work routines, production can become more stable and scalable.