Automatisering vid högintensivt styckplock på lager – En fallstudie på Lyko Group AB

Sammanfattning: The amount of products sold online is increasing at record speed, which has meant a mixed blessing for e-commerce companies. Continuously increasing demand and a customer base that is discerning, disloyal and expects increasingly shorter lead times impose high logistics demands. One of the major differences between logistics within e-commerce and traditional store replenishment, which has a major impact on logistical requirements, is that e-commerce orders are more labour intensive. This is because e-commerce orders often consists of a few orderliness containing only a few pieces per line, which means that e-commerce companies has to pick, pack and ship thousands of orders in small packages of piece picked products. The increased demand and high logistical requirements within the e-commerce industry has resulted in that many of the warehouses that previously have managed well with manual labour feel the need to invest in warehouse automation to ensure capacity for continued growth. However, the decision to automate can be very complicated since automation often requires a high capital investment and it can therefore take a long time before the investment becomes profitable.  A calculation, that may be difficult to perform due to the many different financial factors that need to be taken into account, has to be performed before a decision can be made. There are also qualitative factors, that can be difficult to motivate economically but which can be crucial to consider in an automation decision. Lyko Group AB, one of Scandinavia’s largest actors within beauty and haircare, has for many years been heavily growing and forecasts to continuously do so during the upcoming years. Lyko Group AB has identified a need to invest in automation solutions in their warehouse to ensure that they have capacity to meet demand. In order to facilitate the automation decision, this study presents a model aims at comparing and generation decision making support on the profitability of various alternative automation solutions for high-intensity piece picking at a warehouse. A theoretical model, consisting of capacity requirements, qualitative- and quantative factors, was created based on a literature study. The model was tested through an application on Lyko Group AB and later modified based on the experience gained during the application, resulting in a reality-based model. The resulting model is iterative and enables multi-step feedback to the suppliers by identifing in which areas the performance of the different solutions differ.