The digital models are the fundamental elements used in the virtual simulation of CNC machining for process planning, result prediction, analysis, etc. The essential work to build the digital models of machined parts is the calculation of the envelope surface generated by moving a cutter surface relative to workpieces. This calculation is usually complicated, and the requirements in different cases

Monitoring the transmission status of multi-joint industrial robots is very important for the accuracy of the robot motion. The fault diagnosis information is an indispensable basis for the collaborative maintenance of the robots in industry 4.0. In this paper, an attitude data-based intelligent fault diagnosis approach is proposed for multi-joint industrial robots. Based on the analysis of the transmission

Engineering product family design and optimization in complex environments has been a major bottleneck in today’s industrial transformation towards smart manufacturing. Digital twin (DT), as a core part of cyber-physical system (CPS), can provide decision support to enhance engineering product lifecycle management workflows via remote monitoring and control, high-fidelity simulation, and solution generation

As the resource crisis and environmental pollution become increasingly prominent, remanufacturing is currently a popular research field for addressing these issues. However, scheduling for remanufacturing is more difficult than that for traditional manufacturing because the entire remanufacturing system (RMS) involves three cooperative subsystems: disassembly, reprocessing, and reassembly. Few studies

The human–machine collaboration system is a key means of manufacturing. Its surveillance, prognostic, and health management are related to safety and manufacturing persistence. This paper begins with the mission requirements of intelligent manufacturing. The study is based on the visual question answering (VQA) technology with a digital twin to increase efficiency. The research contents are as follows:

This paper studies the problem of allocating semiconductor wafers to customer orders with the objective of minimizing the overallocation prior to assembly. It is an important problem for back-end semiconductor manufacturing as overallocation may have severe impact on operational performance due to excess inventory and unnecessarily occupied manufacturing equipment. In practice, a wafer can contain

Additive Manufacturing (AM) processes have been increasingly used to manufacture energy storage products with dedicated material preparation and post-processing stages to enhance product properties. Most researchers focus on selecting materials and improving processes, yet the system modeling and management has not been investigated so far. This paper extends the conventional single-stage AM processes

Currently, ways to approach the design of Cyber Physical Systems in Industry 4.0 are under development. Emerging concepts of Smart Factories require the development of specialized knowledge; new working methods are also needed to manage the transition from conventional industry to industry 4.0. To achieve this objective, fractal theory could provide the appropriate knowledge and tools. Fractal systems

This paper proposes a Digital Twin approach for health monitoring. In this approach, a Digital Twin model based on nonparametric Bayesian network is constructed to denote the dynamic degradation process of health state and the propagation of epistemic uncertainty. Then, a real-time model updating strategy based on improved Gaussian particle filter (GPF) and Dirichlet process mixture model (DPMM) is

Big data is one of the most important resources for the promotion of smart customisation. With access to data from multiple sources, manufacturers can provide on-demand and customised products. However, existing research of smart customisation has focused on data generated from the physical world, not virtual models. As physical data is constrained by what has already occurred, it is limited in the

Developments in the internet technology, internet of things, cloud computing, big data, and artificial intelligence in recent years have brought significant advancements in manufacturing, among which manufacturing digitalization contributes greatly to the ever-increasing productivity. A cutting tool driven by the digital twin can provide modern solution to these ever-growing needs of digitalization

Wire arc additive manufacturing technology (WAAM) has become a very promising alternative to high-value large metal components in many manufacturing industries. Due to its long process cycle time and arc-based deposition, defect monitoring, process stability and control are critical for the WAAM system to be used in the industry. Although major progress has been made in process development, path slicing

Internet of things (IoT) and artificial intelligence (AI) are popular topics of Industry 4.0. Many publications regarding these topics have been published, but they are primarily focused on larger enterprises. However, small and medium-sized enterprises (SMEs) are considered the economic backbone of many countries, which is why it is increasingly important that these kinds of companies also have easy

With the widespread application of new digital and information technologies, manufacturing patterns have been reformed in different industries. The digital twin shop-floor (DTS), based on digital twins, has gradually become an advanced data-driven manufacturing model for modern manufacturing companies. The DTS integrates physical and virtual manufacturing processes through simulation and optimisation

Multiple parts in gas exchange system of 2-stroke heavy fuel aircraft engine with poppet valves lead to complicated manufacturing and inefficient assembly. Besides, real experimental optimization wastes lots of time and cost due to the increased valve parameters. To address the above issues, the paper proposes a digital twin (DT)-driven optimization method with several DT modules for the system to

Multi-load Automated Guided Vehicle (AGV) has been proposed for a while, but the advantage of its application is still not fully understood today. In order to fill this knowledge gap, a novel integrated model of a multi-load AGV system is developed in this paper by using an advanced form of Petri Nets, namely Coloured Petri Nets (CPNs), to simulate the operation of the AGV system in various scenarios

Digital twin represents a fusion of the informational and physical domains, to bridge the material and virtual worlds. Existing methods of digital twin modeling are mainly based on modular representation, which limits guidance of the modeling process. Such methods do not consider the components or operational rules of the digital twin in detail, thereby preventing designers from applying these methods

Laser welding has been widely utilized in various industries. Effective real-time monitoring technologies are critical for improving welding efficiency and guaranteeing the quality of joint-products. In this paper, the research findings and progress in recent ten years for real-time monitoring of laser welding are critically reviewed. Firstly, different sensing techniques applied for welding quality

Predictive maintenance is one of the important technical means to guarantee and improve the normal industrial production. The existing bottlenecks for popularization and application are analyzed. In order to solve these problems, a cooperative awareness and interconnection framework across multiple organizations for total factors that affect prediction maintenance decision-making is discussed. Initially

An adaptive production control structure for failure-prone manufacturing systems under inventory and demand uncertainty is proposed. It contains estimation and forecasting modules incorporated into a control loop. The customer demand is unknown and its rate is composed of ramp-type, seasonal and random components. Information available to decision maker consists of imprecise inventory records, and

This paper addresses the problems of data management and analytics for decision-aid by proposing a new vision of Digital Shadow (DS) which would be considered as the core component of a future Digital Twin. Knowledge generated by experts and artificial intelligence, is transformed into formal business rules and integrated into the DS to enable the characterization of the real behavior of the physical

Modern manufacturing enterprises are shifting toward multi-variety and small-batch production. By optimizing scheduling, both transit and waiting times within the production process can be shortened. This study integrates the advantages of a digital twin and supernetwork to develop an intelligent scheduling method for workshops to rapidly and efficiently generate process plans. By establishing the

In a personalized and various production mode, the production line needs to be updated quickly to meet market demand. The Optimization of production line is taken as the object. To address the coupling problems, such as unreasonable production line layout, unbalanced process capability, inaccurate logistics distribution and unintelligent equipment testing, a method of flexible cellular manufacturing

The use of a modern technological system requires a good engineering approach, optimized operations, and proper maintenance in order to keep the system in an optimal state. Predictive maintenance focuses on the organization of maintenance actions according to the actual health state of the system, aiming at giving a precise indication of when a maintenance intervention will be necessary. Predictive

As a state-of-the-art computer technology, virtual reality (VR) is considered to play an important role in helping manufacturing companies stay competitive in the international market. However, despite the achievements made in the field of VR, it is still an emerging technology that lacks deeper exploration and development in industrial application scenarios, especially in the coming fourth industrial

Industrial cloud robotics (ICR) integrates cloud computing with industrial robots (IRs). The capabilities of industrial robots can be encapsulated as cloud services and used for ubiquitous manufacturing. Currently, the digital models for process simulation, path simulation, etc. are encapsulated as cloud services. The digital models in the cloud may not reflect the real state of the physical robotic

The competitive global scenario faces the corresponding impacts such as difficulties in scheduling and loading, high tooling and equipment investment, enormous scrap availability, complex to control the quality, and extensive setup time. So, a higher level of connectivity is required in between the design and manufacturing activities to raise the profitability of the firms and enrich the product support

As usher in Industry 4.0, there has been much interest in the development and research that combine artificial intelligence with automation. The control and operation of equipment in a traditional automated shoemaking production line require a preliminary subjective judgment of relevant manufacturing processes, to determine the exact procedure and corresponding control settings. However, with the manual

As the disassembly of end-of-life products is affected by several dynamic and uncertain issues, many mathematical models and solution approaches have been established. However, with more extended objectives, constraints and different methods of disassembly, inconsistent models relating to product representations and types of disassembly lines have become the main barriers for the transfer of research

Fault diagnosis, with the aim of accurately identifying the presence of various faults as early as possible so at to provide effective information for maintenance planning, has been extensively concerned in advanced manufacturing systems. With the increase of the amount of condition monitoring data, fault diagnosis methods have gradually shifted from the model-based paradigm to data-driven paradigm

In several production systems, buffer stocks are built between consecutive machines to ensure the continuity of supply during interruptions of service caused by breakdowns or planned maintenance actions. However, in previous research, maintenance planning is performed individually without considering buffer stocks. In order to balance the trade-offs between them, in this study, an integrated model

Estimating remaining useful life (RUL) of industrial machinery based on their degradation data is very critical for various industries. Machine learning models are powerful and very popular tools for predicting time to failure of such industrial machinery. However, RUL is ill-defined during healthy operation. This paper proposes to use anomaly monitoring during both RUL estimator training and deployment

This paper describes and examines thoroughly a stochastic production/inventory system that produces a single type of products. During the production process, the system is affected by several deterioration failures. It is restored to its initial and previous deterioration state by repair and maintenance activities. Both maintenance and repair duration are assumed as exponential random variables. Moreover

Centrifugal impeller (CI) manufacturing is moving toward a new paradigm, with the objective to improve efficiency and competitiveness through Industry 4.0 and smart manufacturing. Making a CI developable and ruled has become a crucial technology to obviously improve machining efficiency and save costs although it may bring negative effects on aerodynamic performance accordingly. Hence, it is extremely

Filling the gaps between virtual and physical systems will open new doors in Smart Manufacturing. This work proposes a data-driven approach to utilize digital transformation methods to automate smart manufacturing systems. This is fundamentally enabled by using a digital twin to represent manufacturing cells, simulate system behaviors, predict process faults, and adaptively control manipulated variables

This paper concentrates on a resource-constrained multi-robotic disassembly line balancing (RC-MDLB) problem. In this RC-MDLB problem, different types of end-of-life products are disassembled simultaneously on the same line under the following conditions: allocating multiple robots to a workstation to simultaneously process the disassembly tasks that have no precedence relationship with each other

This paper studies an order assorting system (OAS) composed of multiple-parallel order assorting aisles (OAAs) in a retailer’s order fulfillment center. We evaluate two worker-assignment policies for a worker-to-part OAA: a dedicated-assignment policy and a shared-assignment policy. Our analytical models evaluate the mean value and variance of worker process time including assorting time, walk time

Dynamic flexible job shop scheduling problem is studied under the events such as new order arrivals, changes in due dates, machine breakdowns, order cancellations, and appearance of urgent orders. This paper presents a constructive algorithm which can solve FJSP and DFJSP with machine capacity constraints and sequence-dependent setup times, and employs greedy randomized adaptive search procedure (GRASP)

Various kinds of engineering software and digitalized equipment are widely applied through the lifecycle of industrial products. As a result, massive data of different types are being produced. However, these data are hysteretic and isolated from each other, leading to low efficiency and low utilization of these valuable data. Simulation based on theoretical and static model has been a conventional

Welding systems are being transformed by the advent of modern information technologies such as the internet of things, big data, artificial intelligence, cloud computing, and intelligent manufacturing. Intelligent welding systems (IWS), making use of these technologies, are drawing attention from academic and industrial communities. Intelligent welding is the use of computers to mimic, strengthen,

This paper proposes a new integration method for cell formation, group scheduling, production, and preventive maintenance (PM) planning problems in a dynamic cellular manufacturing system (CMS). The cell formation sub-problem aims to form part families and machine groups, which minimizes the inter-cell material handling, under-utilization, and relocation costs. The production planning aspect is a multi-item

The prognostic study of the ball screw is critical to increase the reliability of manufacturing system, which has drawn great attention in the field of Prognostics and Health Management (PHM). The particle filters (PF) method is a powerful tool for prognostic study because of its capability of robustly predicting the future behavior. However, lack of analytical ball screw measurement model limits the

For many contemporary manufacturing processes, autonomous robotic operators have become ubiquitous. Despite this, the number of human operators within these processes remains high, and as a consequence, the number of interactions between humans and robots has increased in this context. This is a problem, as human beings introduce a source of disturbance and unpredictability into these processes in

Smart manufacturing is arriving. It promises a future of mass-producing highly personalized products via responsive autonomous manufacturing operations at a competitive cost. Of utmost importance, smart manufacturing requires end-to-end integration of intra-business and inter-business manufacturing processes and systems. Such end-to-end integration relies on standards-compliant and interoperable interfaces

Modeling complex systems as networks of interacting elements has gained increased attention in recent years. So far, network modeling in manufacturing and logistics has often focused on the description of system properties. In the data-driven world of smart manufacturing, creating material flow network models becomes a lot easier due to the ubiquitous availability of shop floor and transportation data

Pharmaceutical product customization, a prerequisite for personalized medicines, is currently a widely researched topic. Patient characteristics can be mapped and translated into parameters for designing patients’ individual treatment, i.e., the dosage form. However, current pharmaceutical manufacturing is dominated by mass production and lacks the capability and flexibility required to produce customized

To reduce waste during disassembly production and improve disassembly efficiency, this study investigates a type of partial parallel disassembly line applicable for the simultaneous disassembly of different products. A multi-objective mathematical model for a partial parallel disassembly line balancing problem is built considering four optimisation goals, namely, the minimisation of the cycle time

Every time a component’s design is changed, the corresponding manufacturing has to be changed as well. Due to several recent developments such as increasing market dynamics or ever-shorter product life cycles, the amount of component changes is rising sharply. Therefore, the number of manufacturing changes is increasing at a fast pace. Particularly for safety-critical components, the implementation

With the Internet of Things, it is now possible to sense the real-time status of manufacturing objects and processes. For complex Service Selection (SS) in Cloud Manufacturing, real-time information can be utilized to deal with uncertainties emerging during task execution. Moreover, in the face of diversified demands, multiple manufacturing clouds (MCs) can provide a much wider range of choices of

Feature extraction plays an important role in industrial process monitoring. Autoencoder and its deep framework, deep autoencoder, are used to extract latent features from complex data. However, the latent features extracted by autoencoder through unsupervised learning may not be useful for discriminative tasks. Fisher discriminant analysis (FDA) is another widely used supervised feature extraction

Cyber-physical security is a major concern in the modern environment of digital manufacturing, wherein a cyber-attack has the potential to result in the production of defective parts, theft of IP, or damage to infrastructure or the operator have become a real threat that have the potential to create bad parts. Current cyber only solutions are insufficient due to the nature of manufacturing environments

In automotive paint shops, changes of colors between consecutive production orders cause costs for cleaning the painting robots. It is a significant task to re-sequence orders and group orders with identical color as a color batch to minimize the color changeover costs. In this paper, a Color-batching Resequencing Problem (CRP) with mix bank buffer systems is considered. We propose a Color-Histogram

Computer Numerical Control Machine Tool (CNCMT) Digital Twin (DT) model is a carrier for complex, time-varying, coupled data of CNCMT, which can theoretically provide a time-varying high-fidelity model. However, there are still many difficulties in its implementation process. And the key issue is how to realize the updated DT model with performance attenuation and validate it. In order to solve this

When a mission arrives at a random time and lasts for a duration, it becomes an interesting problem to plan replacement policies according to the health condition and repair history of the operating unit, as the reliability is required at mission time and no replacement can be done preventively during the mission duration. From this viewpoint, this paper proposes that effective replacement policies

The business world is continually changing. Dynamic environments, full of uncertainties, complexities, and ambiguities, demand faster and more confident decisions. To compete in this environment, Industry 4.0 emerges as an essential alternative. In this context, the reliability of manufacturing is an essential aspect for companies to make successful decisions. In the literature, several technologies