Monitoring and control the Wire Arc Additive Manufacturing process using artificial intelligence techniques: a review
Wire Arc Additive Manufacturing is a Direct Energy Deposition additive technology that uses the principle of wire welding to deposit layers of material to create a finished component. This technology is finding an increasing interest in the ...
Collaborative approaches in sustainable and resilient manufacturing
In recent years, the manufacturing sector is going through a major transformation, as reflected in the concept of Industry 4.0 and digital transformation. The urge for such transformation is intensified when we consider the growing societal ...
Rule-based visualization of faulty process conditions in the die-casting manufacturing
Die-casting is a popular manufacturing process that produces precise metal parts with excellent dimensional accuracy and smooth cast surfaces. Recently die-casting process condition data can be acquired to be used as input for machine learning ...
Heterogeneous demand–capacity synchronization for smart assembly cell line based on artificial intelligence-enabled IIoT
An assembly cell line (ACL) is one type of cell production practice, derived from the Toyota Production System in the electronics industry and rapidly spread to other fields. In this mode, the conveyor line is divided into assembly cells (ACs) ...
Methodology for complexity and cost comparison between subtractive and additive manufacturing processes
This works presents a methodology, along with its software implementation called “Design 2 Cost”, for evaluating the manufacturing cost and complexity of a part built by a subtractive (e.g. milling) or additive (e.g. laser metal deposition, ...
Intelligent control system for 3D inkjet printing
- Fanbo Meng,
- Jin Huang,
- Bu Ping,
- Pengfei Yuan,
- Nan Bai,
- Xiaolai Zhang,
- Xueyou Shi,
- Jinzhu Zhou,
- Peng Li,
- Pengbing Zhao
Additive manufacturing is typically an open-loop process. Consequently, it results in poor material matching at the junctions in multimaterial printing, affecting the performance of functional components. This study investigated the surface ...
A novel hybrid framework for single and multi-robot path planning in a complex industrial environment
Optimum path planning is a fundamental necessity for the successful functioning of a mobile robot in industrial applications. This research work investigates the application of the artificial bee colony (ABC) approach, probabilistic roadmap (PRM) ...
Digital-twin based real-time resource allocation for hull parts picking and processing
The development of Industrial Internet of Things, big data, and multi-domain modeling, led to the emergence of digital twin (DT), providing a new approach to the cyber-physical production systems. In the traditional shipbuilding industry, a large ...
Global and local representation collaborative learning for few-shot learning
The objective of few-shot learning (FSL) is to learn a model that can quickly adapt to novel classes with only few examples. Recent works have shown that a powerful representation with a base learner trained in supervised and self-supervised ...
Robust-stable scheduling in dynamic flow shops based on deep reinforcement learning
This proof-of-concept study provides a novel method for robust-stable scheduling in dynamic flow shops based on deep reinforcement learning (DRL) implemented with OpenAI frameworks. In realistic manufacturing environments, dynamic events endanger ...
A novel deep learning motivated data augmentation system based on defect segmentation requirements
Deep learning methods, especially convolutional neural networks (CNNs), are widely used for industrial surface defect segmentation due to their excellent performance on visual inspection tasks. However, the problems of overfitting and low ...
A novel micro-defect classification system based on attention enhancement
A surface micro-defect is characterized by a small size and a susceptibility to noise. Micro-defect detection and classification is very challenging. This paper proposes a Micro-defect classification system based on attention enhancement (MDCS) ...
A smart system of Customer- product Interaction Life Cycle (CILC) in industrial Internet era for mass personalization from industrial practice survey: identification, definition, acquisition and parsing
In the Internet era, the industrial Internet platform has become a bridge between customers and enterprises. In addition, with the continuous improvement of customers’ living standards, customers not only meet the basic needs for the functionality ...
A novel approach of tool condition monitoring in sustainable machining of Ni alloy with transfer learning models
- Nimel Sworna Ross,
- Paul T. Sheeba,
- C. Sherin Shibi,
- Munish Kumar Gupta,
- Mehmet Erdi Korkmaz,
- Vishal S Sharma
Cutting tool condition is crucial in metal cutting. In-process tool failures significantly influences the surface roughness, power consumption, and process endurance. Industries are interested in supervisory systems that anticipate the health of ...
A domain adaptation method for bearing fault diagnosis using multiple incomplete source data
The fault diagnosis method based on domain adaptation is a hot topic in recent years. It is difficult to collect a complete data set containing all fault categories in practice under the same working condition, leading to fault categories ...
Task allocation model for human-robot collaboration with variable cobot speed
New technologies, such as collaborative robots, are an option to improve productivity and flexibility in assembly systems. Task allocation is fundamental to properly assign the available resources. However, safety is usually not considered in the ...
Predicting maintenance through an attention long short-term memory projected model
Long sequence information remains a challenging problem in deep learning nowadays for predicting remaining useful life (RUL). In this work, we propose a novel deep learning module called attention long short-term memory projected (ALSTMP) for RUL ...
Multi-layer edge resource placement optimization for factories
Introducing distributed computing paradigms to the manufacturing domain increases the difficulty of designing and planning an appropriate IT infrastructure. This paper proposes a model and solution approach addressing the conjoint application and ...
A knowledge distillation-based multi-scale relation-prototypical network for cross-domain few-shot defect classification
Surface defect classification plays a very important role in industrial production and mechanical manufacturing. However, there are currently some challenges hindering its use. The first is the similarity of different defect samples makes ...
Graph neural network comparison for 2D nesting efficiency estimation
Minimizing the level of material consumption in textile production is a major concern. The cornerstone of this optimization task is the nesting problem, whose goal is to lay a set of irregular 2D parts out onto a rectangular surface, called the ...
Experience from implementing digital twins for maintenance in industrial processes
The capability of estimating future maintenance needs in advance and in a timely manner is a prerequisite for reliable manufacturing with high availability in a production unit. Additionally, conducting planned maintenance efforts regularly and ...
Safe contextual Bayesian optimization integrated in industrial control for self-learning machines
Intelligent manufacturing applications and agent-based implementations are scientifically investigated due to the enormous potential of industrial process optimization. The most widespread data-driven approach is the use of experimental history ...
Partitioned abrasive belt condition monitoring based on a unified coefficient and image processing
Abrasive belt condition (BC) monitoring is significant for achieving profile finishing precision and quality in grinding of difficult-to-machine materials like Inconel 718. While indirect signal-based BC monitoring methods are ineffective when ...
Machine learning enabled optimization of showerhead design for semiconductor deposition process
In semiconductor fabrication, the deposition process generates layers of materials to realize insulating and conducting functionality. The uniformity of the deposited thin film layers’ thickness is crucial to create high-performance semiconductor ...
