One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the Internet. Cyber-physical production systems (CPPS), relying on the latest, and the foreseeable further developments of computer science, information and communication technologies on one hand, and of manufacturing science and technology, on the other, may lead to the 4th industrial revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots in general – and in particular to the CIRP community – which point towards CPPS. Expectations towards research in and implementation of CPS and CPPS are outlined and some case studies are introduced. Related new R&D challenges are highlighted.

Cyber-physical systems in manufacturing

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

Many countries around the world face three major issues associated with their aging societies: a declining population, an increasing proportion of seniors, and an increasing number of single-person households. To explore assistive technologies that can help solve the problems faced by aging societies, we have tested several information and robot technologies. This paper introduces research on a home-assistant robot, which improves the ease and productivity of home activities. For people who work hard outside the home, the assistant robot performs chores in their home environment while they are away. A case study of a life-sized robot with a humanlike functional body performing daily chores is presented. An integrated software system incorporating modeling, recognition, and manipulation skills, as well as a motion generation approach based on the software system, is explained. Moreover, because housekeepers perform chores one after another in their daily environment, we also aim to develop a system for continuously performing a series of tasks by including failure detection and recovery.

Home-Assistant Robot for an Aging Society

https://re.public.polimi.it/bitstream/11311/1049581/1/1-s2.0-S0360835218300329-main%281%29.pdf

Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems

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.

/pdf/cooperative-and-responsive-manufacturing-enterprises-ny9s2qs4yd.pdf

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

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

A holistic approach for the cognitive control of production systems

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

The order-driven single and small series batch production is characterized by a high variety and the demand for short delivery times. Therefore, a robust production planning is essential. Usually the master data, which is used for scheduling, does not represent the current conditions on the shop floor, due to its static nature. Thus the planning results are of poor quality. To counteract that, this article describes an approach that uses production-condition-dependent execution times of all throughput time components under the consideration of uncertainty. The provision of the scheduling parameters is done with the help of a knowledge-based system that uses a previously on actual data set up case and rule base. A simulation based validation showed that this approach led to an adherence to delivery dates of 93 % in comparison to the utilization of static master data with 74 %.

Knowledge-based machine scheduling under consideration of uncertainties in master data

Kurzfassung In produzierenden Unternehmen besteht heutzutage die Notwendigkeit den Energieverbrauch zu reduzieren. Einen moglichen Ansatz stellt die Erschliesung bisher ungenutzter Potenziale in der Produktionsplanung und -steuerung (PPS) dar, da diese determiniert wann welche Produkte auf welchen Maschinen gefertigt werden. Somit beeinflusst diese Tatigkeit den Gesamtenergieverbrauch in der Produktion. Allerdings wird im klassischen Zielsystem der PPS der Energieverbrauch als Planungs- und Steuerungszielgrose bisher nur unzureichend beachtet. Der vorliegende Artikel beschreibt Handlungsfelder zur Realisierung einer energieproduktiven PPS und somit zur Reduktion des Energieverbrauchs sowie der resultierenden Energiekosten.

Florian Geiger

Papers

Artificial Cognition in Production Systems

A holistic approach for the cognitive control of production systems

Adaptive Job Control in the Cognitive Factory

Knowledge-based machine scheduling under consideration of uncertainties in master data

Handlungsfelder zur Realisierung energieeffizienter Produktionsplanung und -steuerung