A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting

The paper discusses manufacturing enterprises’ compelling challenges that are directly stemming from generic conflicts between competition and cooperation, local autonomy and global behavior, design and emergence, planning and reactivity, uncertainty and a plethora of information. Responses in product and service design, organization of production networks, planning and management of operations, as well as production control are surveyed. As illustrated through industrial case studies, production engineering should integrate a rich body of interdisciplinary results together with contemporary information and communication technologies in order to facilitate cooperation and responsiveness that are vital in competitive, sustainable manufacturing.

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Cooperative and responsive manufacturing enterprises

Today's manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products, and changing market volumes. To manage these dynamics, several production concepts (e.g., flexible, reconfigurable, changeable or autonomous manufacturing and assembly systems) were proposed and partly realized in the past years. This paper presents the general principles of autonomy and the proposed concepts, methods and technologies to realize cognitive planning, cognitive control and cognitive operation of production systems. Starting with an introduction on the historical context of different paradigms of production (e.g., evolution of production and planning systems), different approaches for the design, planning, and operation of production systems are lined out and future trends towards fully autonomous components of an production system as well as autonomous parts and products are discussed. In flexible production systems with manual and automatic assembly tasks, human-robot cooperation is an opportunity for an ergonomic and economic manufacturing system especially for low lot sizes. The state-of-the-art and a cognitive approach in this area are outlined. Furthermore, introducing self-optimizing and self-learning control systems is a crucial factor for cognitive systems. This principles are demonstrated by a quality assurance and process control in laser welding that is used to perform improved quality monitoring. Finally, as the integration of human workers into the workflow of a production system is of the highest priority for an efficient production, worker guidance systems for manual assembly with environmentally and situationally dependent triggered paths on state-based graphs are described in this paper.

/pdf/artificial-cognition-in-production-systems-3xn9mwrv8l.pdf

Artificial Cognition in Production Systems

This paper presents a concept of a smart working environment designed to allow true joint-actions of humans and industrial robots. The proposed system perceives its environment with multiple sensor modalities and acts in it with an industrial robot manipulator to assemble capital goods together with a human worker. In combination with the reactive behavior of the robot, safe collaboration between the human and the robot is possible. Furthermore, the system anticipates human behavior, based on knowledge databases and decision processes, ensuring an effective collaboration between the human and robot. As a proof of concept, we introduce a use case where an arm is assembled and mounted on a robotpsilas body.

/pdf/joint-action-for-humans-and-industrial-robots-for-assembly-1u20yvhrb2.pdf

Joint-action for humans and industrial robots for assembly tasks

https://research.chalmers.se/publication/510875/file/510875_Fulltext.pdf

A framework for operative and social sustainability functionalities in Human-Centric Cyber-Physical Production Systems

https://isiarticles.com/bundles/Article/pre/pdf/16193.pdf

A holistic approach for the cognitive control of production systems

Towards the Cognitive Factory

Increasing requirements in regard to reactivity, adaptability and traceability in production and by extension in the supply chain can be observed among products, processes and clients all over the product lifecycle. In order to cope with these challenges, new methods for an accurate and reliable production planning and control are necessary. The integration of modern sensor technologies presents a promising approach to enhance information management on the shop floor. Hence, current states of both resources and individual products can be captured. The paper presents the framework of a multi-agent-supported, product-based production control, in which the individual product acts as an additional element of control in the production system. Thus, a significant contribution to adaptive and closed-loop production systems can be achieved that are able to transfer current information to the respective planning and control levels.

A multi-agent-supported, product-based production control

In order to stay competitive, producing companies have to meet the constantly rising customer’s individual requirements. One central element is the demand for customized products at short delivery times and reasonable costs In this context, the field of production planning and shop floor is of utmost importance. A promising approach for the realization of a high degree of flexibility and, at the same time, a high productivity is the implementation of artificial cognitive capabilities. The paper outlines the paradigm of the “Cognitive Factory” that combines the advantages of automated systems with the flexibility, adaptability and reactivity of human workshops. As an example, the adaptive job control is elucidated in detail. Here, so-called smart products have, on the one hand, a “backpack” with knowledge about “their” production process and their current state. On the other hand, they are able to communicate with manufacturing resources. Thus, the individual workpiece is able to control itself throughout the production process. The productspecific experiences during order processing are used for continuously updating the knowledge models. The feasibility and benefit of the holistic approach was successfully shown by the implementation in a realistic production environment.

Adaptive Job Control in the Cognitive Factory

Nowadays, industrial organizations have to face a turbulent environment, which is caused by the globalization of the economy and saturated markets. Among other things, this development results in increasing product variants with specific configurations, decreasing lot sizes and short delivery lead times. Especially job-shop production systems that are characterized by a high flexibility, undirected value streams and a high proportion of manual working steps are affected by this development. In order to cope with these challenges, modern sensor technologies, such as RFID (Radio frequency identification), are indispensable elements to enhance the information management on the shop floor. Especially the lack of information about the actual location of orders and its corresponding material can be resolved by modern identification technologies. This paper identifies the potential of integrating RFID-based real-time location and product data to enhance the performance level of a typical job shop production.

Martin Ostgathe

Papers

A holistic approach for the cognitive control of production systems

Towards the Cognitive Factory

A multi-agent-supported, product-based production control

Adaptive Job Control in the Cognitive Factory

Adaptive, Location-based Shop Floor Control