Internet of Things

Mixed global economic signs hardly allow for reliable long-term forecasts. While the traditionally export-oriented production sector in Germany is benefitting from the economic recovery in the U.S., Asian demand has started to dwindle. At the same time the third industrial revolution offers new opportunities and challenges through the development of intelligent production systems and manufacturing processes. In order to obtain an advantageous position in a changing technological and economic environment, companies must preserve efficiency and innovation in production processes. The deployment of modern technology and machinery equipment is therefore crucial. Flexible financing solutions help industrial enterprises make investments and maintain flexibility and competitive advantage.

Dynamic routing is a major research topic for logistics service providers and based on satellite navigation systems. The major challenge in operational business practice applications is the dynamic high-performance analysis of GPS data with individual depots and vehicles in logistics - and the acceptance and use by logistics employees in administration and truck driver roles. Therefore this contribution outlines a basic design of a software and process system for these application areas in order to evaluate the first estimates regarding the overall business value of GPS-based dynamic routing in logistics.

Cyber-Physical Systems and the internet of things change the way we see management, production and even logistics processes. The research project “Smart Logistic Grids” uses a decentralized cloud-based management concept to reduce the risk of disruptions in logistics networks.

Value Stream Mapping has been applied successfully in production and logistics scenarios. With the rise of Cyber-Physical Systems (CPS) in the context of Industry 4.0, the value-contribution of information itself is gaining importance. Therefore, the concept of Value Stream Mapping is extended to the field of information logistics. Key-processes and design variables are defined.

Industry 4.0 is part of the high-tech strategy of the German government. It promotes the computerization of established industrial areas like  manufacturing. The Smart Factory, characterized by resource efficiency, consistency of processes, a common technological base and the usage of the “Internet of Things” is the strategic objective. Prof. Herkommer prefers to call this process “evolution” instead of “revolution”.

The fourth industrial revolution promises a further automation of process control by cyber-physical systems. The individual products gain the ability for controlling their production and logistics themselves. By coordinating themselves they can jointly achieve business objectives. This logical decomposition reduces the complexity of cross-company process control significantly. Thus, even exceptions on short notice can be dealt with in real-time. In operation, the required artificial intelligence will usually not be implemented on the active objects. Instead, adequate software platforms for the so-called Industry 4.0 are required. This article investigates the requirements for such platforms and describes how they can be implemented.

Today’s systems of internal material flow must cope with high demands: an in-creasing variety and shorter innovation and product life cycles lead to difficulties in predicting order loads and structures. The order-based production is becoming increasingly important. Against this background, material handling systems have to be dynamically adjustable and thereby cause the lowest possible cost. Approaches of modularization and decentralization both in the field of control software and in the design of conveyor systems promise great potential in terms of flexibility, robustness and reusability. Technological developments in the areas of sensors, data processing and storage, communication, locating and identification support this trend and enable new, innovative solutions for transportation tasks in logistic systems - including swarm-like conveyor systems.

The vision of the “Internet of Things” describes networked, interactive objects which are capable of autonomous decision-taking. The potentials of this vision for logistics in the automotive and food sector go from tracking and tracing throughout the supply-chain, via quality assurance and monitoring through to new service models and consequently completely novel sources of revenue. Key elements of the “Internet of Things” such as auto-identification technology or sensors are already mature and ready to be used in logistics. On the basis of a series of industry case studies, this article describes the current situation in industry with regards to these technologies and identifies future potential. To facilitate the analysis, it presents an instrument by which the level of implementation of the technologies of the “Internet of Things” can be measured.

Due to growing demands on logistic processes, increasing transportation costs and a crowded, highly competitive market, margins in this service sector are shrinking. In order to survive, logistics providers will have to reduce internal costs, for example by means of logistic optimization (e.g., scheduling of pickup and delivery). Equally important, they also need to offer their customers additional value-added services, such as tracking and tracing (e.g., temperature logging within the cold chain). These requirements can be seamlessly supported across multiple industries by the event-driven EPCglobal Network.

The international exchange of goods and products is growing steadily. Information technologies now in use are unable to sufficiently organize the flows of goods both more securely and more reliably: Losses from misdirected containers, pallets and luggage run in the tens and hundreds of millions. Modern solutions not only have to provide the capability to positively identify mobile objects of different kinds and in changing environmental conditions but also to localize them, communicate with them, navigate them and control them.