• Environmental Factors
• Human Factors
• Logistics
• Team Behaviours
• Wearable Sensors

The aim of this thesis is to identify environmental and human factors that affect productivity and performance of operators in material handling activities, regarding the internal logistics field. The study was carried out in a semi-automated warehouse and the data collection related to human factors has been conducted using an innovative approach, i.e. equipping each operator with a wearable sensor. Notably consisting of a smartwatch and a specific software, designed by the MIT Center for Collective Intelligence of Boston, that is able to detect human-related variables such as heart rate and interactions. The main contribution of the applied methodology is the measurement of both environmental and human factors, in order to carry out analyses that can explain what the major factors are impacting on operators’ productivity. The statistical analysis of data collected has led to a model that describes the most relevant variables which can be used by management for the improvement of productivity and the well-being of operators.