Analytics

The term “low carbon” has become a buzzword in recent years and has presented new challenges for the industry. For the manufacturing companies the first step to reach the “low carbon” goal is “low carbon manufacturing”, wherein the possibilities to reduce the CO2 emissions could be utilized during the manufacturing stage. So far, there is a lack of a holistic concept to determine and assess the production processes in consideration of CO2 emissions. This paper focuses on the emissions, which emit due to the use of energy, material and capital goods in the production. Here, the indirect emissions from suppliers are also being considered. Afterwards, a hybrid approach to determine the emissions is presented. With this approach the paper investigates the possibility of a comprehensive production optimization with respect to efficient resource usage and emission reduction at the planning stage.

The demand for more sophisticated logistics services has brought about a diversification of services, specialization and mainly a more intensive use of ICT (Information and Communication Technologies) by the 3PL providers. To characterize logistics services offered in Brazil, a third-party logistics provider typology is suggested based on statistics and data mining analysis. Considering the presence of technological solutions through Yes/No categorical statements, the results identified 3PL homogeneous clusters in the Brazilian market which correspond to main sector categories that are described in this paper. These results are equivalent to those models that make use of quantitative variables, usually associated with unreliability and difficult acquisition.

In the planning phase of cyclically interlinked production lines neural networks are used to learn and forecast the characteristics of these systems. To increase the results of learning and to accelerate the training this paper presents a method, based on genetic algorithms, that reduces the attributes to describe the behaviour of the production lines.

The analysis of maintenance tasks in shipbuilding by using virtual reality (VR) technologies offers significant capabilities of minimizing the maintenance costs. In order to reach these capabilities, it is necessary to develop a data model to support the required variant construction in VR. Additionally the efficient integration of the VR software components into a typical IT environment has to be taken into account.

adhesive bonding technology, fit analysis, optical measurement, offline programming, data management

Investments in knowledge management systems have increased significantly in the past. However, various implementations have failed due to human, organizational and technological barriers. Since various knowledge management approaches consider these barriers isolated, we focus on a holistic, process-oriented approach to identify, structure, and tackle those barriers. Specifically, we emphasize the process of knowledge distribution, e.g., knowledge sharing. Based upon this analysis, we provide recommendations for management instruments and concepts to overcome knowledge management barriers.