On the truck dispatching problem

１ Ｂａｓｉｃ ｎｅｐｈｒｏｌｏｇｙ（生理；免疫・病理；分子生物学；検査・診断） ２ Ｃｌｉｎｉｃａｌ ｎｅｐｈｒｏｌｏｇｙ（糸球体障害；尿細管・間質障害；全身性疾患と腎障害；水電解質異常；腎不全）

Annual review 腎臓

Industry 4.0 and the human factor – A systems framework and analysis methodology for successful development

Real-time generic object detection on mobile platforms is a crucial but challenging computer vision task. Prior lightweight CNN-based detectors are inclined to use one-stage pipeline. In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet. In the backbone part, we analyze the drawbacks in previous lightweight backbones and present a lightweight backbone designed for object detection. In the detection part, we exploit an extremely efficient RPN and detection head design. To generate more discriminative feature representation, we design two efficient architecture blocks, Context Enhancement Module and Spatial Attention Module. At last, we investigate the balance between the input resolution, the backbone, and the detection head. Benefit from the highly efficient backbone and detection part design, ThunderNet surpasses previous lightweight one-stage detectors with only 40% of the computational cost on PASCAL VOC and COCO benchmarks. Without bells and whistles, ThunderNet runs at 24.1 fps on an ARM-based device with 19.2 AP on COCO. To the best of our knowledge, this is the first real-time detector reported on ARM platforms. Code will be released for paper reproduction.

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ThunderNet: Towards Real-Time Generic Object Detection on Mobile Devices

Although manufacturing companies are currently situated at a transition point in what has been called Industry 40, a new revolutionary wave—Industry 50—is emerging as an ‘Age of Augmentation’ when the human and machine reconcile and work in perfect symbiosis with one another Recent years have indeed assisted in drawing attention to the human-centric design of Cyber-Physical Production Systems (CPPS) and to the genesis of the ‘Operator 40’, two novel concepts that raise significant ethical questions regarding the impact of technology on workers and society at large This paper argues that a value-oriented and ethical technology engineering in Industry 50 is an urgent and sensitive topic as demonstrated by a survey administered to industry leaders from different companies The Value Sensitive Design (VSD) approach is proposed as a principled framework to illustrate how technologies enabling human–machine symbiosis in the Factory of the Future can be designed to embody elicited human values and to illustrate actionable steps that engineers and designers can take in their design projects Use cases based on real solutions and prototypes discuss how a design-for-values approach aids in the investigation and mitigation of ethical issues emerging from the implementation of technological solutions and, hence, support the migration to a symbiotic Factory of the Future

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Value-Oriented and Ethical Technology Engineering in Industry 5.0: A Human-Centric Perspective for the Design of the Factory of the Future

Empowering and engaging industrial workers with Operator 4.0 solutions

In this paper, we propose an efficient and fast object detector which can process hundreds of frames per second. To achieve this goal we investigate three main aspects of the object detection framework: network architecture, loss function and training data (labeled and unlabeled). In order to obtain compact network architecture, we introduce various improvements, based on recent work, to develop an architecture which is computationally light-weight and achieves a reasonable performance. To further improve the performance, while keeping the complexity same, we utilize distillation loss function. Using distillation loss we transfer the knowledge of a more accurate teacher network to proposed light-weight student network. We propose various innovations to make distillation efficient for the proposed one stage detector pipeline: objectness scaled distillation loss, feature map non-maximal suppression and a single unified distillation loss function for detection. Finally, building upon the distillation loss, we explore how much can we push the performance by utilizing the unlabeled data. We train our model with unlabeled data using the soft labels of the teacher network. Our final network consists of 10x fewer parameters than the VGG based object detection network and it achieves a speed of more than 200 FPS and proposed changes improve the detection accuracy by 14 mAP over the baseline on Pascal dataset.

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Object detection at 200 Frames Per Second

Mixed model assembly line literature involves two problems: balancing and model sequencing. The general tendency in current studies is to deal with these problems in different time frames. However, in today's competitive market, the mixed model assembly line balancing problem has been turned into an operational problem. In this paper, we propose mixed integer programming (MIP) and constraint programming (CP) models which consider both balancing and model sequencing within the same formulation along with the optimal schedule of tasks at a station. Furthermore, we also compare the proposed exact models with decomposition schemes developed for solving different instances of varying sizes. This is the first paper in the literature which takes into account the network type precedence diagrams and limited buffer capacities between stations. Besides, it is the first study that CP method is applied to balancing and scheduling of mixed model assembly lines. Our empirical study shows that the CP approach outperforms the MIP approach as well as the decomposition schemes.

Balancing and scheduling of flexible mixed model assembly lines

In this paper, we study flexible mixed model assembly lines with serially connected stages where stages may have one or more parallel stations. Station parallelism in flexible mixed model assembly lines improves system reliability and enables rapid adaptability to customer demand fluctuations. However, in order to effectively manage such lines under real-world conditions, there is a need to extend traditional assembly line management methods. This study extends the current research by simultaneously considering the problems of task assignment and model scheduling on parallel stations. Furthermore, scheduling of assigned tasks on each station is considered. We formulate the problem context first as a mixed integer programming model and then develop a decomposition scheme for large scale applications. Finally, we compare the performance of the proposed model and decomposition scheme using various size test instances.

Cemalettin Ozturk

Papers

Empowering and engaging industrial workers with Operator 4.0 solutions

Object detection at 200 Frames Per Second

Balancing and scheduling of flexible mixed model assembly lines

Balancing and scheduling of flexible mixed model assembly lines with parallel stations

Cyclic scheduling of flexible mixed model assembly lines with parallel stations