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Correction to: On the use of adjoint gradients for time-optimal control problems regarding a discrete control parameterization

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Multibody System Dynamics 2023年第3期59卷 335-336页

作者： Lichtenecker, Daniel Rixen, Daniel Eichmeir, Philipp Nachbagauer, Karin TUM School of Engineering and Design Department of Mechanical Engineering Chair of Applied Mechanics Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Munich Germany Institute of Mechanics and Mechatronics Vienna University of Technology Wien Austria Faculty of Engineering and Environmental Sciences University of Applied Sciences Upper Austria Wels Austria Institute for Advanced Study Technical University of Munich Garching Germany

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Low Power and Temperature-Resilient Compute-In-Memory Based on Subthreshold-FeFET

arXiv

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arXiv 2023年

作者： Zhou, Yifei Huang, Xuchu Yang, Jianyi Ni, Kai Amrouch, Hussam Zhuo, Cheng Yin, Xunzhao Zhejiang University Hangzhou China Department of Electrical Engineering University of Notre Dame Notre Dame United States AI Processor Design Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence Munich Germany Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

Compute-in-memory (CiM) is a promising solution for addressing the challenges of artificial intelligence (AI) and the Internet of Things (IoT) hardware such as"memory wall" issue. Specifically, CiM employing nonvolatile memory (NVM) devices in a crossbar structure can efficiently accelerate multiply-accumulation (MAC) computation, a crucial operator in neural networks among various AI models. Low power CiM designs are thus highly desired for further energy efficiency optimization on AI models. Ferroelectric FET (FeFET), an emerging device, is attractive for building ultra-low power CiM array due to CMOS compatibility, high ION/IOFF ratio, etc. Recent studies have explored FeFET based CiM designs that achieve low power consumption. Nevertheless, subthreshold-operated FeFETs, where the operating voltages are scaled down to the subthreshold region to reduce array power consumption, are particularly vulnerable to temperature drift, leading to accuracy degradation. To address this challenge, we propose a temperature-resilient 2T-1FeFET CiM design that performs MAC operations reliably at subthreahold region from 0°C to 85°C, while consuming ultra-low power. Benchmarked against the VGG neural network architecture running the CIFAR-10 dataset, the proposed 2T-1FeFET CiM design achieves 89.45% CIFAR-10 test accuracy. Compared to previous FeFET based CiM designs, it exhibits immunity to temperature drift at an 8-bit wordlength scale, and achieves better energy efficiency with 2866 TOPS/W. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy efficiency

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Low Power and Temperature- Resilient Compute-In-Memory Based on Subthreshold-FeFET

Low Power and Temperature- Resilient Compute-In-Memory Based...

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design, Automation and Test in Europe Conference and Exhibition

作者： Yifei Zhou Xuchu Huang Jianyi Yang Kai Ni Hussam Amrouch Cheng Zhuo Xunzhao Yin Zhejiang University Hangzhou China ZJU - Hangzhou Global Scientific and Technological Innovation Center Hangzhou China Department of Electrical Engineering University of Notre Dame Notre Dame USA Chair of AI Processor Design Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence Munich Germany Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Compute-in-memory (CiM) is a promising solution for addressing the challenges of artificial intelligence (AI) and the Internet of Things (IoT) hardware such as “memory wall” issue. Specifically, CiM employing nonvolatile memory (NVM) devices in a crossbar structure can efficiently accelerate multiply-accumulation (MAC) computation, a crucial operator in neural networks among various AI models. Low power CiM designs are thus highly desired for further energy efficiency optimization on AI models. Ferroelectric FET (FeFET), an emerging device, is attractive for building ultra-low power CiM array due to CMOS compatibility, high ION / $I$ O F F ratio, etc. Recent studies have explored FeFET based CiM designs that achieve low power consumption. Nevertheless, subthreshold-operated FeFETs, where the operating voltages are scaled down to the subthreshold region to reduce array power consumption, are particularly vulnerable to temperature drift, leading to accuracy degradation. To address this challenge, we propose a temperature-resilient 2T-1FeFET CiM design that performs MAC operations reliably at subthreahold region from 0°C to 85°C, while consuming ultra-low power. Benchmarked against the VGG neural network architecture running the CIFAR-10 dataset, the proposed 2T1FeFET CiM design achieves 89.45% CIFAR-10 test accuracy. Compared to previous FeFET based CiM designs, it exhibits immunity to temperature drift at an 8-bit wordlength scale, and achieves better energy efficiency with 2866 TOPS/W.

关键词： Semiconductor device modeling Power demand Nonvolatile memory Microprocessors Neural networks Computer architecture Energy efficiency

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DECOMPOSITION OF INDUSTRIAL SYSTEMS FOR ENERGY EFFICIENCY OPTIMIZATION WITH OPTTOPO

arXiv

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arXiv 2022年

作者： Thiele, Gregor Johanni, Theresa Sommer, David Krüger, Jörg Department for Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology IPK Germany Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany Weierstrass Institute for Applied Analysis and Stochastics Berlin Germany Institute for Machine Tools and Factory Management Technical University of Berlin Berlin Germany

The operation of industrial facilities is a broad field for optimization. Industrial plants are often a) composed of several components, b) linked using network technology, c) physically interconnected and d) complex regarding the effect of set-points and operating points in every entity. This leads to the possibility of overall optimization but also to a high complexity of the emerging optimization problems. The decomposition of complex systems allows the modeling of individual models which can be structured according to the physical topology. A method for energy performance indicators (EnPI) helps to formulate an optimization problem. The optimization algorithm OptTopo achieves efficient set-points by traversing a graph representation of the overall system. © 2022, CC BY.

关键词： Optimization

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Using anomaly detection and classification to support failure recovery of plants

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AIP Conference Proceedings 2024年第1期2989卷

作者： Niklas Grambow Lisa-Marie Fenner Oliver Heimann Jörg Krüger Department for Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology Pascalstr. 8-9 10587 Berlin Germany Institute for Machine Tools and Factory Management Technische Universität Berlin Pascalstr. 8-9 10587 Berlin Germany

Failure recovery of machines is a great challenge for the plant operator. Usually, a stopped plant is quite costly and has to be put back into operation fast. In that case, experienced personnel are essential. Only their knowledge and broad understanding of the interaction of the various components allows a reliable identification of the underlying problem and enables a successful recovery. Digitization can help to address this problem. Knowledge can be stored and shared digitally across plants, locations and companies. In addition, an ever-increasing amount of machine and process data is digitally available which can further support the problem-solving process. We present a new approach to machine maintenance that relies on machine learning to help identify the underlying technical problem that led to the machines error. In contrast to predictive maintenance, our system is employed reactively and focusses on the identification and classification of singular failures rather than a predictive monitoring of the plants state. To support the operator in fault recovery, we use anomaly detection to identify the deviations in the data of the processes prior to the fault. This allows the system to generate hints as to where to look for the underlying cause of the error and helps the technician make an educated guess. Additionally, an error classification algorithm also allows troubleshooting information to be linked directly to the data. Thereby, when an error reoccurs, the knowledge gained in the first occurrence is immediately made available to the operator through information linked to the error *** this article, we present the concept behind our anomaly detection system and the required software architecture to combine the different data sources. Furthermore, we discuss the results from an experiment that simulates an optical part inspection using a camera based system, where we introduce different errors into the process and are able to demonstrate the capability

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Implementing human-robot collaboration in highly dynamic environments: Assessment, planning and development

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AIP Conference Proceedings 2024年第1期2989卷

作者： A. Bastidas-Cruz T. Jaya G. Thiele J. Krüger Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstr. 8-9 10587 Berlin Germany Head of Industrial Automation Technology Department Institute of Machine Tools and Factory Management Technische Universität Berlin Pascalstr. 8-9 10587 Berlin Germany

Human-robot collaboration (HRC) applications have been slowly making their path in the industry. Although the required hardware and the methods for the planning and development of collaborative robotic applications are mostly already developed, some industrial branches still struggle to implement HRC. This is the case in motorcycle production, where, unlike car production, the assembly line has been optimized for manual *** on the use case described above, this paper identifies new requirements of HRC for automated screwing assembly operations in flexible production environments. In order to compensate deviations in the position of the tool relative to the workpiece, a screwing strategy based on force control is proposed. Parameter sensitivity is considered and supported experimentally with a screwing task performed by a cobot, where a method for contact detection between the nutrunner and the screw head is analyzed. This paper brings a guideline for experts from the manufacturing system engineering to implement HRC in highly dynamic assembly environments.

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Leadership approach towards Agile, Waterfall and Iterative implementation of the software development products

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IOP Conference Series: Materials Science and Engineering 2021年第1期1169卷

作者： O Popa C. Mihele C Făgărăşan A. Pîslă Design engineering & Robotics Department Machine Building Faculty Technical University of Cluj-Napoca 103-105 Muncii Avenue Cluj-Napoca Romania

The automotive industry is one of the most dynamic markets, gathering around many different sectors from material extractions to robotics and cloud computing. The current research analyses the influences and particularities of leadership and identifies the challenges and advantages of the two principal methodologies in software development projects within the automotive industry, Agile and Waterfall. Some aspects of reducing methodological disadvantages are suggested and presented. The aim is to arrive at a sustainable solution that can ensure the delivery of reliable and flexible software products. The impact of these methodologies on the quality standards and project documentation is analyzed, which is a vital part of automotive software development. By influencing the product development lifecycle, there is an opportunity to develop a structured framework that can be adopted to build software products in a more flexible and agile way.

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Automation of Life Data Analysis Processes

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IOP Conference Series: Materials Science and Engineering 2021年第1期1140卷

作者： Jonathan Krämer Gregor Thiele Theresa Johanni Jörg Krüger Department for Industrial automation at the Institute for Machine Tools and Factory Management Technical University of Berlin Department for Process automation and Robotics Fraunhofer Institute for Production Systems and Design Technology

Life data analysis is an effective statistical process to gain information on the reliability of technical facilities. The Weibull analysis is a widely-used method for modeling the probabilities of different functional failures. For its application in modern manufacturing and maintenance processes, an automation of this analysis is expedient. An exemplary process of data collection and fitting of a parametric model with continuous time scale is analyzed in this article. Its automation with different statistic software tools is described and comparatively evaluated. With the ambition of minimizing manual effort in the process, a highly automated solution was developed in this research. We describe this self-implemented solution in 'R' and justify that this procedure automatizes the process more than the examined commercial implementations. The here presented work proves to be a practical real-time assistance, right now applied in aircraft maintenance.

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On the Selection and Application of a Convenient Energy Management Software for Industrial Purposes

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IOP Conference Series: Materials Science and Engineering 2021年第1期1140卷

作者： Larissa Wurster Gregor Thiele Clemens Briese Jörg Krüger Plant Development Infrastructure / Assembly Trucks (TG/MAD) Daimler Truck AG Department for Process automation and Robotics Fraunhofer Institute for Production Systems and Design Technology Department for Machine Vision Fraunhofer Institute for Production Systems and Design Technology Department for Industrial automation at the Institute for Machine Tools and Factory Management Technical University of Berlin

The profitability of companies, especially in Germany, is affected by rising energy prices and increasingly stringent energy legislation. Certification according to ISO 50.001, an international standard for energy management systems, can help to meet legal requirements and increase energy efficiency. This article offers assistance in the form of a methodology that provides a structure for the selection process of an energy management system (EnMS). Considering properties of the individual company, it helps to identify an appropriate software solution. It is applied to a globally operating metalworking company in an example study. Furthermore, the measurement infrastructure in particular is a basic requirement that should not be overlooked in addition to the process of choosing an appropriate software solution. In this context, suitable metering points or criteria must be defined as well as sufficient attention paid to the anticipated costs for acquiring and integrating new measuring transducer and energy meters. The type and number of relevant measuring points must be considered in particular. Discussing these aspects, this article facilitates the process of planning and implementing an energy monitoring.

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Agile, waterfall and iterative approach in information technology projects

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IOP Conference Series: Materials Science and Engineering 2021年第1期1169卷

作者： C Fagarasan O Popa A Pisla C Cristea Design engineering & Robotics Department Machine Building Faculty Technical University of Cluj-Napoca 103-105 Muncii Avenue Cluj-Napoca Romania Electrical Machines and Drives Department Faculty of Electrical Engineering Technical University of Cluj-Napoca 26-28 G. Baritiu Street Cluj-Napoca Romania

The aim of this paper is to analyse the Agile methods implementation capability within software projects as a more viable alternative to the waterfall model and determine the key factors that guarantee the continuous delivery of software to market at the right and agreed quality level. Two Agile implementation methods were considered: Scrum and Kanban, which were evaluated based on factors like predictability, practicability and complexity. The conclusions show the selected methodologies advantages and disadvantages, and project key attributes can be used to choose the suitable methodology for a project. Regarding the Agile implementation methods, the most straightforward and predictable one was proven to be Scrum. This framework supports frequent delivery of software products that can address complex problems and adapt to the rapid market changes.

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