| 1. |
- Afshar, Sara Zargari, et al.
(author)
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An optimal spin-lock priority assignment algorithm for real-time multi-core systems
- 2017
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In: The 23th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications RTCSA'17.
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Conference paper (peer-reviewed)abstract
- Support for exclusive access to shared (global) resources is instrumental in the context of embedded real-time multi-core systems, and mechanisms for achieving such access must be deterministic and efficient. There exist two traditional approaches for multiprocessors when a task requests a global resource that is locked by a task on a remote core: a spin-based approach, i.e. non-preemptive busy waiting for the resource to become available, and a suspension-based approach, i.e. the task relinquishes the processor. A suspension-based approach can be viewed as a spin-based approach where the lowest priority on a core is used during spinning, similar to a non-preemptive spin-based approach where the highest priority on a core is used. By taking such a view, we previously provided a general model for spinning, where any arbitrary priority can be used for spinning, i.e. from the lowest to the highest priority on a core. Targeting partitioned fixed-priority preemptive scheduled multiprocessors and spin-based approaches that use a fixed priority for spinning per core for all tasks, we aim at increasing the schedulability of multiprocessor systems by using the spin-lock priority per core as parameter. In this paper, we present (i) a generalization of the traditional worst-case response-time analysis for non-preemptive spin-based approaches addressing an arbitrary but fixed spin-lock priority per core, (ii) an optimal spin-lock priority assignment (OSPA) algorithm per core, i.e. an algorithm that will find a fixed spin-lock priority per core that will make the system schedulable, whenever such an assignment exists and, (iii) comparative evaluations of the OSPA algorithm with the spin-based and suspension-based approaches where OSPA showed up to 38% improvement compared to both approaches.
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| 2. |
- Afshar, Sara Zargari, et al.
(author)
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Investigating Alternatives for System Architectures to Enhance Discrete Manufacturing
- 2019
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In: International Journal of Distributed Sensor Networks. - Sweden : SAGE Publications. - 1550-1329 .- 1550-1477. ; 15:8
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Journal article (peer-reviewed)abstract
- This article investigates the possibility of advancing discrete manufacturing using system architectures that are developed for Collaborative Process Automation Systems. Collaborative Process Automation System is a technology that has the potential to achieve production excellence for process industry. However, not much attention has been paid on using the architectures based on Collaborative Process Automation Systems for discrete manufacturing domains. In this article, we propose a base architecture consisting of three layers, and we discuss various alternatives to make the communications among the layers. We consider legacy components in the proposal, in contrast to most of the related works. In order to show the practicality of the proposed alternatives, we present an example that has been implemented in an ongoing project at ABB Robotics in Sweden.
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| 3. |
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| 4. |
- Balasubramanian, S.M.N, et al.
(author)
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A dual shared stack for FSLM in Erika enterprise
- 2017
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In: The 23rd IEEE International Conference on Embedded and Real-Time Computing Systems and Applications - WiP Session RTCSA'17.
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Conference paper (peer-reviewed)abstract
- Recently, the flexible spin-lock model (FSLM) has been introduced, unifying spin-based and suspension-based resource sharing protocols for real-time multi-core platforms. Unlike the multiprocessor stack resource policy (MSRP), FSLM doesn’t allow tasks on a core to share a single stack, however. In this paper, we present a hypothesis claiming that for a restricted range of spin-lock priorities, FSLM requires only two stacks. We briefly describe our implementation of a dual stack for FSLM in the Erika Enterprise RTOS as instantiated on an Altera Nios II platform using 4 soft-core processors.
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| 5. |
- Balasubramanian, S.M.N, et al.
(author)
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Incorporating implementation overheads in the analysis for the flexible spin-lock model
- 2017
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In: IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY. - 9781538611272 ; , s. 411-8418
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Conference paper (peer-reviewed)abstract
- The flexible spin-lock model (FSLM) unifies suspension-based and spin-based resource sharing protocols for partitioned fixed-priority preemptive scheduling based real-time multiprocessor platforms. Recent work has been done in defining the protocol for FSLM and providing a schedulability analysis without accounting for the implementation overheads. In this paper, we extend the analysis for FSLM with implementation overheads. Utilizing an initial implementation of FSLM in the OSEK/VDX-compliant Erika Enterprise RTOS on an Altera Nios II platform using 4 soft-core processors, we present an improved implementation. Given the design of the implementation, the overheads are characterized and incorporated in specific terms of the existing analysis. The paper also supplements the analysis with measurement results, enabling an analytical comparison of FSLM with the natively provided multiprocessor stack resource policy (MSRP), which may serve as a guideline for the choice of FSLM or MSRP for a specific application.
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| 6. |
- Hatvani, Leo, 1985-, et al.
(author)
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Optimal Priority and Threshold Assignment for Fixed-priority Preemption Threshold Scheduling
- 2018
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In: ACM SIGBED Review. - 1551-3688. ; :1, s. 43-49
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Journal article (peer-reviewed)abstract
- Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold.This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable.We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.
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| 7. |
- Leberruyer, Nicolas, et al.
(author)
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Enabling an AI-Based Defect Detection Approach to Facilitate Zero Defect Manufacturing
- 2023
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In: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. - 9783031436659 - 9783031436666 ; , s. 643-649
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Conference paper (peer-reviewed)abstract
- Artificial Intelligence (AI) has proven effective in assisting manufacturing companies to achieve Zero Defect Manufacturing. However, certain products may have quality characteristics that are challenging to verify in a manufacturing facility. This could be due to several factors, including the product’s complexity, a lack of available data or information, or the need for specialized testing or analysis. Prior research on using AI for challenging quality detection is limited. Therefore, the purpose of this article is to identify the enablers that contributed to the development of an AI-based defect detection approach in an industrial setting. A case study was conducted at a transmission axle assembly factory where an end-of-line defect detection test was being developed with the help of vibration sensors. This study demonstrates that it was possible to rapidly acquire domain expertise by experimenting, which contributed to the identification of important features to characterize defects. A regression model simulating the normal vibration behavior of transmission axles was created and could be used to detect anomalies by evaluating the deviation of new products compared to the model. The approach could be validated by creating an axle with a built-in defect. Five enablers were considered key to this development.
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| 8. |
- Leberruyer, Nicolas, et al.
(author)
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Toward Zero Defect Manufacturing with the support of Artificial Intelligence—Insights from an industrial application
- 2023
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In: Computers in industry (Print). - : Elsevier B.V.. - 0166-3615 .- 1872-6194. ; 147
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Journal article (peer-reviewed)abstract
- The Zero Defect Manufacturing (ZDM) concept combined with Artificial Intelligence (AI), a key enabling technology, opens up new opportunities for improved quality management and advanced problem-solving. However, there is a lack of applied research in industrial plants that would allow for the widespread deployment of this framework. Thus, the purpose of this article was to apply AI in an industrial application in order to develop application insights and identify the necessary prerequisites for achieving ZDM. A case study was done at a Swedish manufacturing plant to evaluate the implementation of a defect-detection strategy on products prone to misclassification and on an imbalanced data set with very few defects. A semi-supervised learning approach was used to learn which vibration properties differentiate confirmed defects from approved products. This method enabled the calculation of a defect similarity ratio that was used to predict how similar newly manufactured products are to defective products. This study identified four prerequisites and four insights critical for the development of an AI solution supporting ZDM. The key finding demonstrates how well traditional and innovative quality methods complement one another. The results highlight the importance of starting data science projects quickly to ensure data quality and allow a ZDM detection strategy to build knowledge to allow for the development of more proactive strategies, such as the prediction and prevention of defects.
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| 9. |
- Wickberg, Philip, et al.
(author)
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Adopting a Digital Twin Framework for Autonomous Machine Operation at Construction Sites
- 2023
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In: Proc. CAA Int. Conf. Veh. Control Intell., CVCI. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350340488
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Conference paper (peer-reviewed)abstract
- Autonomous machines are expected to be vastly used at construction sites as they can efficiently perform repetitive and dangerous tasks. However, ensuring the operational safety of such autonomous machines in a highly dynamic environment is challenging. Although autonomous machines usually are equipped with a perception system that permits them to navigate locally, there is a need to share a global view of the construction site to reduce the risk of accidents or errors. A digital twin of the construction site map has the potential of fusing the real-time perception from different sources at the site, such as different autonomous machines working at the construction site, analysing them and sharing the needed information to operate safely and effectively at the site. This paper proposes the adoption of the recently published standard, ISO 23247 digital twin framework for manufacturing, to implement and maintain a dynamic map of construction sites. The proposed framework will enable safe and efficient operation of autonomous machines on construction sites.
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