Exploring Automation Potential: A Case Study of Volvo Penta’s Warehouse Operations

Abstract

This thesis investigates the feasibility and strategic implications of automating order picking operations at Volvo Penta’s Distribution Centre (VPDC) in Vara, Sweden, within the scope of the company’s VPDC 2.0 development initiative. The focus lies on evaluating four candidate automation technologies, vertical lift modules (VLM), vertical Carousels, horizontal Carousels, and mini-load systems, against the current manual picking solution. These options are assessed across seven performance aspects: throughput, cost, quality, space utilisation, scalability, flexibility, and ergonomics. To support the evaluation, a multi-method research approach was adopted. This included a literature review, time studies, site visits, historical order data analysis, and unstructured interviews with different stakeholders at various levels within Volvo Penta. The Analytical Hierarchy Process (AHP) was employed to rank the importance of each performance aspect and to compare the suitability of each order picking system based on those performance aspects. Interview insights played a central role in defining criteria relevance. In addition, an association and cluster analysis of historical order data was performed to identify co-picked stock keeping units (SKU) clusters, supporting a data-driven approach to warehouse layout optimisation. The results reveal that flexibility is the most valued performance aspect at VPDC, followed by quality, scalability, and cost. Although the VLM solution ranked marginally higher overall than the current manual operations, each system excelled in different areas. The findings suggest that a hybrid setup, integrating VLMs for selected high-runner SKU clusters while retaining manual operations for irregular items, may offer the optimal balance of efficiency and adaptability. Key success factors include staged implementation, clear project ownership, super-user training, and risk mitigation through pilot testing and temporary safety stock. Overall, the study demonstrates that automation, when aligned with data insights and operational context, can significantly enhance warehouse performance.