Miljömässiga besparingar i lagerverksamheter : Framtagning av en modell för besparandet av koldioxidekvivalenter i kunders lagerverksamhet för Consafe Logistics

Sammanfattning: Companies are having to adhere to higher demands regarding their environmental emissions, this also stands true for the companies warehousing. In warehouses, both picking and moving goods is done using forklifts which leads to energy use and thereby environmental emissions for these activities. Two ways of reducing these emissions are to plan routes for the forklifts that minimize travel distance, or placing the goods such that it reduces the total travel distance. One company that offers IT solutions which make optimizations like this possible is Consafe Logistics. Situated in Lund, Sweden, Consafe Logistics serves over 250 customers worldwide. The company’s main product is Astro WMS, a Warehouse Managing System with different optional modules that, for example, can reduce forklift driving using the methods described above. In this study three of these modules are studied; Slotting, Goods Move Optimization, and Pick Route Optimization. Slotting and Pick Route Optimization aim to optimize picking of goods while Goods Move Optimization aims to optimize moving of goods. Consafe Logistics have knowledge regarding how the implementations of the modules reduce travel distance and travel time, but they do not know what environmental effects these reductions have. Because Consafe Logistics customers differ in their warehousing it also becomes relevant to study how the environmental effects of the modules vary depending on which customer that implements the modules. Therefore, the aim of this study is “To create a model for reduction of carbon dioxide equivalents (CO2e) in warehousing for different customer segments when using Astro WMS modules to optimize the warehouse.” To study how the environmental effects, differ depending on which customer is regarded, the customers needed to be separated. This was done by identifying the customers’ differing characteristics. For characteristics, physical aspects, conditions, circumstances, and/or strategic differences, was regarded. Determining the characteristics was done using seven interviews with customers. The interviewees all had responsibilities for managing and developing activities in the warehouse. The customers were interviewed regarding what parts of warehousing affect how much forklift driving that was needed in the warehouse. The customers then ranked the characteristics and an aggregated list of what customers regarded as most important. In parallel to a literature study about compartmentalizing customer warehouses, the list was presented to the commissioner who determined what characteristics to study. From the chosen characteristics, area of the warehouse, number of orders handled, and carbon dioxide intensity (gCO2e per generated kWh as customer segment). For each segment there was multiple subdivisions, for example the big area of the warehouse (>20 000 m2). Carbon dioxide intensity was used to highlight that some warehouses give rise to more or less environmental effect depending on how much carbon dioxide that is emitted when generating the used electricity. The customer segments and subdivisions were then used to categorize the customers into different segments for each studied module. The effect on potential kgCO2e savings from different segments was then studied together with the effects of the different modules. From the results, a correlation was observed between a bigger warehouse area and more orders, and potentially saved carbon dioxide equivalents. This was true independently of what module was being studied. The highest observed yearly reduction was 1620 kgCO2e when using Goods Move Optimization and electricity with high carbon dioxide intensity.