Applying machine learning to wire arc additive manufacturing: a systematic data-driven literature review
Due to its unique benefits over standard conventional “subtractive” manufacturing, additive manufacturing is attracting growing interest in academic and industrial sectors. Here, special emphasis is given to wire arc additive manufacturing (WAAM), ...
Fault diagnosis and self-healing for smart manufacturing: a review
Manufacturing systems are becoming more sophisticated and expensive, particularly with the development of the intelligent industry. The complexity of the architecture and concept of Smart Manufacturing (SM) makes it vulnerable to several faults ...
Image deep learning in fault diagnosis of mechanical equipment
With the development of industry, more and more crucial mechanical machinery generate wildness demand of effective fault diagnosis to ensure the safe operation. Over the past few decades, researchers have explored and developed a variety of ...
Digital Twin-based manufacturing system: a survey based on a novel reference model
The development of advanced information technologies are paving the digital transformation of manufacturing systems, of which Digital Twin-based manufacturing system (DTMS) has become a prevailing topic attracted ever-increasing concerns from both ...
Tool wear prediction in milling CFRP with different fiber orientations based on multi-channel 1DCNN-LSTM
In the machining of carbon fiber reinforced polymer (CFRP) components, tool wear grows rapidly due to the highly abrasive property of carbon fibers, resulting in unfavorable part quality such as delamination and fiber pullout. The tool wear ...
Production quality prediction of cross-specification products using dynamic deep transfer learning network
In the process of industrial production, products with different specifications (i.e., the difference in geometry, process conditions, and machine conditions, etc.) have different quality data distributions, which lead to a decrease in the ...
Smart scheduling of dynamic job shop based on discrete event simulation and deep reinforcement learning
In the era of Industry 4.0, production scheduling as a critical part of manufacturing system should be smarter. Smart scheduling agent is required to be real-time autonomous and possess the ability to face unforeseen and disruptive events. However,...
An innovative integrated approach to automatic defect detection system of cell phone case manufacturing in an empirical implementation
In this study an innovative integrated approach is proposed to develop a design schema for automatic defect detection system. This system has been successfully implemented in an empirical factory setting. In addition, this novel design has been ...
Evaluation of process planning in manufacturing by a neural network based on an energy definition of hopfield nets
During the planning stages of new factories for the Body-In-White assembly, the processes used per production system need to be defined. Each production system uses a specific combination of processes, with each process belonging to a main process ...
Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysis
This article proposes two approaches for a tailored geometrical deviation compensation for Laser-Powder-Bed-Fusion production. The deviation compensation is performed by a non-rigid deformation of the manufacturing geometry in each iteration to ...
Multi-stage few-shot micro-defect detection of patterned OLED panel using defect inpainting and multi-scale Siamese neural network
Automatic micro-defect detection is crucial for promoting efficiency in the production lines of patterned OLED panels. Recently, deep learning algorithms have emerged as promising solutions for micro-defect detection. However, in real-world ...
Digitalization platform for data-driven quality management in multi-stage manufacturing systems
Digital transformation is driving the current technological trends in manufacturing. An integral constituent is a communication between machines, between machines and humans, or between machines and products. This extensive communication involves ...
A real spatial–temporal attention denoising network for nugget quality detection in resistance spot weld
Resistance spot welding is an important process in the production of body-in-white. The quality of the welded nugget affects the safety performance of the whole vehicle. Currently, the quality of the welded nugget is mainly inspected manually, ...
Rapid simplification of 3D geometry model of mechanisms in the digital twins-driven manufacturing system design
With the development of simulation technology, more and more manufacturers have begun to use the digital twin to design workshops and factories. For these design scenarios under real-time interaction requirements with an excessive amount of model ...
A novel interpretable predictive model based on ensemble learning and differential evolution algorithm for surface roughness prediction in abrasive water jet polishing
As an important indicator of the surface quality of workpieces, surface roughness has a great impact on production costs and the quality performance of the finished components. Effective surface roughness prediction can not only increase ...
Smart nesting: estimating geometrical compatibility in the nesting problem using graph neural networks
Reducing material waste and computation time are primary objectives in cutting and packing problems (C &P). A solution to the C &P problem consists of many steps, including the grouping of items to be nested and the arrangement of the grouped ...
Swarm intelligence-based framework for accelerated and optimized assembly line design in the automotive industry
This study proposes a dynamic simulation-based framework that utilizes swarm intelligence algorithms to optimize the design of hybrid assembly lines in the automotive industry. Two recent discrete versions of Whale Optimization Algorithm (named ...
Competing refurbishment in a supply chain with different selling modes
This study focuses on the optimal pricing and product refurbishing decisions of an original equipment manufacturer (OEM) and a retailer in a supply chain. The OEM sells the new product through a retailer, which serves as a reseller or selling ...
Equipment electrocardiogram (EECG): making intelligent production line more robust
The simultaneous regulation of production efficiency and equipment maintenance in intelligent production lines poses a challenging problem. Existing approaches addressing this issue often separate the regulation of equipment maintenance and load ...
An accuracy and performance-oriented accurate digital twin modeling method for precision microstructures
Digital twin, a core technology for intelligent manufacturing, has gained extensive research interest. The current research was mainly focused on digital twin based on design models representing ideal geometric features and behaviors at ...
Digital twin enhanced fault diagnosis reasoning for autoclave
Autoclave is the most important equipment in the composite curing process, and its real-time condition has a direct impact on the quality of composite materials. Therefore, rapid and precise fault diagnosis reasoning is of great significance for ...
A deep convolutional network combining layerwise images and defect parameter vectors for laser powder bed fusion process anomalies classification
Defect detection is an essential way to ensure the quality of parts made by laser powder bed fusion (LPBF) and industrial cameras are one of the commonly used tools for defect monitoring. Different lighting environments affect the visibility of ...
A hierarchical ensemble causal structure learning approach for wafer manufacturing
In manufacturing, causal relations between components have become crucial to automate assembly lines. Identifying these relations permits error tracing and correction in the absence of domain experts, in addition to advancing our knowledge about ...
