Systematic combination of Lean Management with digitalization to improve production systems on the example of Jidoka 4.0

© The Author(s) 2020. Lean Management builds the basis for efficient production systems for many industrial companies. However, lots of potentials of Lean Management have been lifted and information and communication technologies in the context of digitalization and cyber-physical production systems (CPPS) offer new possibilities to enhance the performance of companies. Even though surveys indicate that companies recognize these potentials, especially small and medium-sized companies still face challenges in selection and implementation of suitable solutions. Thus, the research project GaProSys 4.0 aims at supporting companies with a systematic approach to combine existing structures of Lean Management with potentials of digitalization in development of a new set of methods to enhance production systems. This paper presents the approach of the research project to develop a structured set of methods and provides an example to illustrate the potentials

Different populations and sources of human mesenchymal stem cells (MSC): A comparison of adult and neonatal tissue-derived MSC

The mesenchymal stroma harbors an important population of cells that possess stem cell-like characteristics including self renewal and differentiation capacities and can be derived from a variety of different sources. These multipotent mesenchymal stem cells (MSC) can be found in nearly all tissues and are mostly located in perivascular niches. MSC have migratory abilities and can secrete protective factors and act as a primary matrix for tissue regeneration during inflammation, tissue injuries and certain cancers

Lung allocation score: The Eurotransplant model versus the revised US model - a cross-sectional study

Both Eurotransplant (ET) and the US use the lung allocation score (LAS) to allocate donor lungs. In 2015, the US implemented a new algorithm for calculating the score while ET has fine-tuned the original model using business rules. A comparison of both models in a contemporary patient cohort was performed. The rank positions and the correlation between both scores were calculated for all patients on the active waiting list in ET. On February 6th 2017, 581 patients were actively listed on the lung transplant waiting list. The median LAS values were 32.56 and 32.70 in ET and the US, respectively. The overall correlation coefficient between both scores was 0.71. Forty-three per cent of the patients had a < 2 point change in their LAS. US LAS was more than two points lower for 41% and more than two points higher for 16% of the patients. Median ranks and the 90th percentiles for all diagnosis groups did not differ between both scores. Implementing the 2015 US LAS model would not significantly alter the current waiting list in ET

Active Role-Based Database System for Factory Planning

Part 6: Industry 4.0 - Smart FactoryInternational audienceThe globalization of markets and the paradigm shift to mass customization lead to a turbulent planning environment. For companies, this results in an increased planning frequency and an increased volume of planning data in the factory planning process. Solutions are the concepts of the Digital Factory and the Digital Shadow. In the context of these two concepts, database systems must be integrated into systematic planning tools in order to make continuous and active use of factory planning knowledge and to reduce the amount of data to the required. Against this background, the paper proposes a concept for the development of an active role-based database system that converts information from various sources into manageable restrictions and filters them by assigning them to the relevant planning phase and to the responsible employee in the company. To validate the concept, the database system is integrated in a factory planning table. A use case shows, that in combination with the planning table, the database system reduces the planning time of factories and at the same time improves planning quality by integrating stored planning knowledge