Learning Curves of Temporary Workers in Manual Order Picking Activities

Person-to-stock order picking is highly flexible and requires minimal investment costs in comparison to automated picking solutions. For these reasons, tradi-tional picking is widespread in distribution and production logistics. Due to its typically large proportion of manual activities, picking causes the highest operative personnel costs of all intralogistics process. The required personnel capacity in picking varies short- and mid-term due to capacity requirement fluctuations. These dynamics are often balanced by employing minimal permanent staff and using seasonal help when needed. The resulting high personnel fluctuation necessitates the frequent training of new pickers, which, in combination with in-creasingly complex work contents, highlights the im-portance of learning processes in picking. In industrial settings, learning is often quantified based on diminishing processing time and cost requirements with increasing experience. The best-known industrial learning curve models include those from Wright, de Jong, Baloff and Crossman, which are typically applied to the learning effects of an entire work crew rather than of individuals. These models have been validated in largely static work environments with homogeneous work contents. Little is known of learning effects in picking systems. Here, work contents are heterogeneous and individual work strategies vary among employees. A mix of temporary and steady employees with varying degrees of experience necessitates the observation of individual learning curves. In this paper, the individual picking performance development of temporary employees is analyzed and compared to that of steady employees in the same working environment.

Exploring Urban Environments Using Virtual and Augmented Reality

In this paper, we propose the use of specific system architecture, based on mobile device, for navigation in urban environments. The aim of this work is to assess how virtual and augmented reality interface paradigms can provide enhanced location based services using real-time techniques in the context of these two different technologies. The virtual reality interface is based on faithful graphical representation of the localities of interest, coupled with sensory information on the location and orientation of the user, while the augmented reality interface uses computer vision techniques to capture patterns from the real environment and overlay additional way-finding information, aligned with real imagery, in real-time. The knowledge obtained from the evaluation of the virtual reality navigational experience has been used to inform the design of the augmented reality interface. Initial results of the user testing of the experimental augmented reality system for navigation are presented.

E-Learning Systems, Environments and Approaches

The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Part III), Collaborative and student-centered e-Learning design (Part IV). E-Learning has been, since its initial stages, a synonym for flexibility. While this dynamic nature has mainly been associated with time and space it is safe to argue that currently it embraces other aspects such as the learners’ profile, the scope of subjects that can be taught electronically and the technology it employs. New technologies also widen the range of activities and skills developed in e-Learning. Electronic learning environments have evolved past the exclusive delivery of knowledge. Technology has endowed e-Learning with the possibility of remotely fomenting problem solving skills, critical thinking and team work, by investing in information exchange, collaboration, personalisation and community building.