Open Source

In the connected world, digital twins open up completely new possibilities: they virtually replicate physical systems, processes, or products. However, key challenges remain, including the collection of current product data. This issue of Industry 4.0 Science covers a wide range of topics, from the basic concept of the digital twin to its benefits in procurement and its use in supply chain management.

The success of technologies depends not only on their innovative strength and acceptance, but also on their management. Decision-makers evaluate factors like technical framework conditions and organizational requirements, with the demand for flexibility adding to the complexity. Industry 4.0 addresses this with networking, transparency and decentralized decisions. Digital twins, which can be implemented with open source software, play a key role.

Learning factories promote digital transformation through an interdisciplinary approach between lean management, Industry 4.0, energy efficiency, training center or research farm. SME centers are characterized by the on-site integration of small and medium-sized companies. Such a regional strategy, combined with learning factories, promotes a goal-oriented dialog between science and practice where students can put their theoretical knowledge to the test.

Facility managers for industrial properties are faced with the challenge of optimizing the energy efficiency of their facilities in the face of ever-increasing energy demand and rising energy costs. Digital processes that enable the comprehensive monitoring, analysis and control of energy demand offer an effective way to reduce costs, increase energy efficiency and make optimal use of resources. Based on IoT technologies and open-source software, a cost-effective, wireless and flexible retrofit solution for real-time energy data collection has been developed.

Intensified networking and digitalization of systems affect an increasing number of sectors. At the same time a great variety of different concepts, ideas, expectations as well as fears have emerged around Industry 4.0. A look into the newspapers is enough to understand that the profound connection of critical structures does also hold profound dangers. For the future it is crucial to consider a way of using the new mass of data and information to protect these structures. Evaluating big data and transforming it into smart data with support of Artificial Intelligence will be a significant security factor in the future.

The difference between Open and Closed Innovation is that external partners can get actively involved in all stages of the value added process and are not limited to being mere idea generators. Whilst finding solutions for their own problems and needs, creative individuals or groups of individuals can play an active role in the development of innovative products featuring new functional and design elements. In addition, Open Innovation provides further benefits in the field of image building and innovation marketing.

There are many commercial software applications to support business processes. More and more companies, however, rely on open source alternatives, because there is now a wide range of sophisticated applications for classical business functions. But how good is the royalty-free alternative, for whom is it appropriate and what to look for? The following article provides a glimpse into the world of open source and introduces some tools and applications.

Standard software should be chosen based on the value created through it’s introduction within the firm. Business process improvements that are achieved after the software has been introduced create value for the company. Due to the vast amount of software companies and their products it is recommend to follow a structured approach when selecting standard software, assuring that a high degree of functional coverage and profitability surging through the introduction of the software are present. This approach is briefly introduced in this article.

The Autonomous Logistic Engineering Methodology (ALEM), which is developed within the Collaborative Research Center 637, provides several tools for creating models of autonomously controlled logistic systems. To evaluate such models, the ALEM framework is extended to include a simulation component. As the ALEM Models cannot run directly within simulation software, they are transformed using principles of the Model Driven Architecture. To enable the transformation several open source tools can be applied. This article evaluates a selection of such tools with the aim of integrating them into ALEM.

Due to increased market turbulence, firms not only are faced with the decision to use open source software, but also consider releasing their proprietary software under an open source license. Beside the appropriateness as an open source product this raises the question of how to profit from giving something away which then is available for free. This article contributes to this discussion by addressing possible open source business models with regard to the type of software.