Vertical integration of production systems for resource efficiency determination

The current trend of digitalising processes as well as the manufacturing environment in general within the context of Industry 4.0 offers a wide range of opportunities such as increase of productivity and performance, individualisation or quality but entails challenges as well. These include especially for small and medium enterprises (SME) the proper selection and introduction of production systems, selection of entities to be digitalized as well as setting up the suitable Industry 4.0 environment. Besides the mentioned aspects, digitalisation by means of vertical integration of production systems offers the opportunity of increasing the transparency of processes, e.g. regarding resource consumptions which founds the basis for improvements in resource efficiency. This aspect is worth being considered due to the constantly increasing prices of production factors caused by resource scarcity and cost-intensive labor. To use Industry 4.0 as a driver for productivity in manufacturing and increase transparency, literature suggests the vertical integration of production systems. The integration of data within production systems such as enterprise resource planning (ERP), manufacturing execution systems (MES) and sensors enable to develop meaningful key performance indicator (KPI) about the manufacturing processes performance. This concept includes the use of gathered process data and their aggregation to knowledge about the most relevant resources. Together with the intelligent selection of necessary datasets within e.g. ERP or MES, an intelligent interconnection leads to the meaningful calculation of resource consumptions. For a useful preparation of companies for the presented Industry 4.0 transformation process, this paper strives to (1) select the most relevant activities in the main corresponding research areas, (2) identify the major industrial requirements, (3) evaluate existing approaches regarding those and (4) finally derive further research demand about this vertical integration approachs development as well as its implementation into an existing manufacturing environment

Pre-selection of Suitable Regression Methods for the Determination of Interactions and Forecasts in Global Production Networks

The locations of many manufacturing companies are distributed globally. This has led to the development of historically grown global production networks whose structure is often very complex, not transparent and influenced by many factors. The high number, as well as the volatility of the influencing factors and dependencies in the network additionally, complicate the network configuration. As a result, adaptation needs and optimization possibilities are recognized too late or not at all. In order to enable early recognition of saving potentials, active monitoring and analysis of changes and dependencies of the influencing factors on the production network is needed. The necessary consideration of a multitude of influencing factors requires further tools to be manageable by the network planner. Therefore, databased methods can be used as support for the forecast and the determination of dependencies of influencing factors. In other research fields, regression analysis is an established method for a databased analysis. This paper focuses on the use of regression analysis in global production networks. It is essential for an accurate analysis, to choose the right regression method out of the many different types in existence. A systematic literature review is conducted to establish an overview of regression methods used in other research fields. A search strategy is developed and implemented and the key findings of the literature review are derived and evaluated. In the second step, a new approach for the pre-selection of suitable regression methods for the determination of interactions and forecasts in global production networks is proposed