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The interworking of Manufacturing Execution Systems (MES) and operating resources is a prerequisite for the flexible and versatile production in Smart Factories of Industry 4.0. This article describes a qualitative and quantitative analysis of an MES integration based on an industrial laser assistance system for worker guidance. It analyzes the situation and requirements from a user perspective with special consideration of implemented systems, interfaces, protocols as well as Plug & Produce. The study uses qualitative analysis results from opinion makers and quantitative analysis results from leading manufacturing companies among others from the automotive and aerospace industry. Thus, the study supports decision making for MES investments in Industry 4.0.

The performance of assistance systems, especially in the automotive sector, has become an unique selling point. The trend toward Autonomous driving represents the expected impact of innovation resulting from the exploitation of the latest technologies. Besides autonomous driving, other areas of application for autonomous systems could trigger social change - the prime example being industrial production. The following article presents a planning approach tailored to the complex engineering task of planning and designing autonomous systems for industrial applications.

Existing factories face multiple problems due to their hierarchical structure of decision making and control. Cyber-physical systems principally allow to increase the degree of autonomy to new heights. But which degree of autonomy is really useful and beneficiary? This paper differentiates diverse definitions of autonomy and approaches to determine them. Some experimental findings in a lab environment help to answer the question raised in this paper.

Cyber-Physical Systems (CPS) are an example of the close connection between the digital and the real world. This connection makes the development of the systems more complex. Methods of Artificial Intelligence (AI) such as machine learning help companies to use these systems for new application scenarios. Image and speech recognition capabilities enable new, closer forms of cooperation between humans and CPS that previously did not work for occupational safety reasons. At the same time, machine learning enhances the cognitive abilities of CPS. They can work independently in situations which are difficult to plan.

Why Lean-Management is the solid basis for the fourth industrial revolution: The fourth industrial revolution seems to be the current issue number one. Apart from that well-known consultancies determine a not satisfactory level of implementation concerning Lean methods. The question rises to what extent the implementation of Lean Methods is useful for the introduction of industry 4.0 or if these methods can even be seen as a precondition. Therefore, all common Lean principles and methods were contrasted with the principles and technologies of the industry 4.0. In conclusion, Lean Management is a solid basis for the successful implementation of the fourth industrial revolution for the production of the future. Lean Management can finally be seen as the essential precondition.

The economic and environmental impacts of globalization are forcing companies to form their supply chain more efficient. Vendor Managed Inventory (VMI) is a widely used concept that is primarily implemented because of its cost savings. Based on a comprehensive survey in the logistics industry in Germany, this study provides sustainable and ecological recommendations for companies planning or already working daily with VMI.

In transport logistics the utilization of transports is often unknown. As a consequence it is not possible to use this information during the transport planning phase and it cannot be used for operational transport control. This report describes technologies which can measure the utilization of shipping spaces. Due to the lack of market-ready systems, a new system was developed that uses ultrasonic sensors to determine the transport utilization. The system was built on a trailer and was tested during live operation. It was shown that the system fulfills the given requirements and it is suggested to expand the tests.

As a result of digitization, logistics objects and systems are increasingly being equipped with information and communication technologies, which is accompanied by new functionalities. Such smart objects enable a high-resolution representation of processes within a supply chain and support their control. At the same time, the variations in the technical design and integration are increasing. For the handling of complexity, an approach for a systematic structuring of objects in logistics with regard to function, structure and dependencies is presented.

Methods for monitoring and controlling material flows in a production or logistics system should support objectives like costs and throughput-time. Lean focuses on decentral, demand-driven steering of activities. Advanced manufacturing concepts for Smart Factories rely on innovative digital technologies. Which method is the best fit for steering the material flow? The Crossroads-Model explains different approaches and supports the selection of a suitable method for corporate practice.

Implementing Industry 4.0 as the digital Agenda in all manufacturing industries and thereby increasing the competitiveness is a matter of course and clearly also applicable for the food and beverage industry. With altering customer behaviours, legal requirements as well as the increasing specialization, the industrial sectors are facing continuous challenge. Even though the automation of facilities in many cases is already put into practice, the structured integration into a holistic data concept is often missing. Through the digital networking of all processes, innovative solutions are on offer. What does Industry 4.0 mean for the food and beverage industry, where the opportunities lie and which specific implementation measures are available is subject to this article.