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Abstract Superalloys, particularly nickel alloys such as Inconel 625, are increasingly used in biomedical engineering for manufacturing critical components such as implants and surgical instruments due to their exceptional mechanical properties and corrosion resistance. However, traditional machining methods often struggle with these materials due to their high strength and thermal conductivity. This study investigates the application of Wire Electrical Discharge Machining (WEDM) as an advanced method for processing Inconel 625 in biomedical contexts. The authors develop an Adaptive Neuro‐Fuzzy Inference System for forecasting WEDM parameters using grey‐based data. The model's variable inputs are analysed through analysis of variance (ANOVA) and Taguchi design, aiming to optimise process performance attributes relevant to biomedical applications. Comparative studies between predicted and experimental data demonstrate a high degree of accuracy, indicating that the proposed model effectively enhances the machining process. The results suggest that this intelligent system supports decision‐making in the production of high‐quality biomedical devices and components.

Abstract Large and complex workpieces are core components in fields, such as aerospace, shipbuilding, and other industrial applications. However, the main challenge of curved plate processing comes from the difficulty in determining the nonlinear rebound features with structural design parameters. An intelligent method framework is proposed for 3D surface manufacturing in cloud‐edge collaboration environment. With the construction of an intelligent generation method for machining parameters, a unified data model is effectively integrated with various discrete data, and an intelligent processing mechanism based on 3D point clouds is constructed. In particular, a prediction method for curved panel rebound is constructed to reduce the manual dependency of the manufacturing process. Finally, a related case study is conducted to verify the framework, and the result shows accuracy, interpretability and reusability advantages over other similar methods.

Abstract The chaotic identification and resolution, inadequate data interoperability, and inefficient management of resources in the high‐voltage coil production workshop limited the effectiveness of its management, and posed significant challenges. To address this issue, the authors establish a comprehensive interconnected digital workshop for high‐voltage coil manufacturing based on Industrial Internet Identification and Resolution as well as the 5G technology. A comprehensive framework model is developed for the high‐voltage coil workshop, along with a formal modelling and tagging approach for objects within the high‐voltage coil workshop. In addition, a management shell modelling method for the complete set of resources in the high‐voltage coil workshop is explored. An analytical identification and interoperability mechanism for the full resource of the high‐voltage coil workshop is introduced. Furthermore, a trusted shared space is developed for the complete resource data of the high‐voltage coil workshop. Finally, a field validation is conducted within a specific high‐voltage coil production workshop. The obtained results demonstrate that the proposed methods and models facilitate the unified access, mutual integration, and efficient management of the entire resources within the high‐voltage coil workshop. These achievements serve as a crucial reference for the implementation and advancement of interconnected manufacturing workshops.

Abstract Workload control (WLC) is usually employed to make order release to attain workload balance, satisfactory delivery rate and high production efficiency. However, in the real production environment of printed circuit board (PCB) industries, slight modifications in the product process shifts the bottleneck resources which leads to misjudge the effect of WLC and may ultimately increase the lateness of orders. Therefore, this research focuses on the order release problem of PCB production system considering main process flow and shifting of bottlenecks. At first, certain improvements are proposed on the classic WLC method and two order release control strategies based on process switching are designed to generate order release plan on the basis of Lancaster University Management School Corrected Order Release method. Furthermore, different scheduling rules are investigated along with the upper workload limits on the PCB system simultaneously. Finally, a simulation model is developed to analyse the impact of order release methods on the system performance through simulation experiments. Furthermore, extensive simulation experiments for different scheduling rules on bottleneck resource and different workload upper limit ratios are also carried out in the current research. Simulation results show that the process order release control strategy based on process switching has a strong adaptability in PCB manufacturing system.

Abstract OpenAI's ChatGPT (GPT‐4) ushers in a superior mode of computer interaction through natural language dialogues. Notably, it generates not only engaging dialogues but also codes aligned to queries and requirements. The potential of ChatGPT in hardware implementation via natural language is implemented and a strategy for “asking the right questions” is outlined. The versatility of ChatGPT is demonstrated through three mainstream hardware designs – systolic array, ResNet and MobileNet accelerators – comparing these with hand‐coded designs. The evaluation metrics include design quality, design efforts, and limitations of code generated by ChatGPT/GPT‐4/Cursor against prevalent High‐Level Synthesis or hand‐coded HDL designs. Consequently, a novel design workflow is proposed and the constraints of using GPT, particularly in AI accelerators, are highlighted.

Abstract The reliability of well‐performing production processes not only depends on internal but also on external factors in the upstream supply chain. Therefore, companies require fast and reliable information exchange with cooperating organisations. Since existing researches usually put focus on reviewing intra‐organisational solutions, the authors have conducted a survey to capture the current state and needs regarding the inter‐organisational information exchange between German companies. The main outcomes of the authors’ survey are outlined. In a first step, the current status of digitalisation in the companies is analysed. The authors have found that the use and implementation of modern methods correlates positively with the company size. Taking a look on the current methods for inter‐organisational information exchange in a second step, it is seen that only a few companies are completely satisfied with their current methods. Companies see the greatest potential for the improvement of information exchange in standardisation and the increase of required resources. This indicates that companies would be best supported by the development of solutions that can be implemented easily and help to form the heterogeneous landscape of data exchange strategies towards a structured, standardised way.

Abstract 3D meshes simplification plays an important role in many industrial domains. The two goals of Delaunay mesh simplification are maintaining high geometric fidelity and reducing mesh complexity. However, they are conflicting and cannot solved by gradient. Such limitation prevents existing Delaunay mesh simplification to obtain a small enough number of vertices and promising fidelity at the same time. To address these issues, this paper proposes an evolutionary multi‐objective approach for Delaunay mesh simplification. Firstly, the authors replace the previous fixed error‐bound threshold by the designed adaptive segment‐specific thresholds. Secondly, a constrained simplification is performed through a series of edge collapses that satisfy both Delaunay and error constraints. Next, the non‐dominated sorting genetic algorithm II (NSGA‐II) is employed to solve the multi‐objective problem to search for the optimal trade‐off threshold sequences. Finally, a fine‐tuning method is designed to further enhance the geometric fidelity of the simplified mesh. Experimental results demonstrate that the authors’ method consistently achieves a satisfactory balance between the approximation error and number of vertices, outperforming existing state‐of‐the‐art methods.

In the Flexible Manufacturing System (FMS), where material processing is carried out in the form of tasks from one department to another, the use of Automated Guided Vehicles (AGVs) is significant. The application of multiple-load AGVs can be understood to boost FMS throughput by multiple orders of magnitude. For the transportation of materials and items inside a warehouse or manufacturing plant, an AGV, a mobile robot, offers extraordinary industrial capabilities. The technique of allocating AGVs to tasks while taking into account the cost and time of operations is known as AGV scheduling. Most research has exclusively addressed single-objective optimization, whereas multi-objective scheduling of AGVs is a complex combinatorial process without a single solution, in contrast to single-objective scheduling. This paper presents the integrated Local Search Probability-based Memetic Water Cycle (LSPM-WC) algorithm using a spinning mill as a case study. The scheduling model’s goal is to maximize machine efficiency. The scheduling of the statistical tests demonstrated the applicability of the proposed model in lowering the makespan and fitness values. The mean AGV operating efficiency was higher than the other estimated models, and the LSPM-WC surpassed the different algorithms to produce the best result.

Manufacturing companies aim for the optimization of their processes by means of Computer Integrated Manufacturing (CIM), in order to keep-up with the competition and the evolution of clients' needs. This transformation is based on connecting the shop floor systems to the high business layer ones. Based on the limitations of the existing architectures in the literature, we proposed the BLAEM architecture (Bi-Level Architecture for Efficient Manufacturing), an ISA95-based architecture that relies on six major aspects, among which we can cite Cybersecurity. In this paper, we focus on this specific aspect, and we try to elaborate a security index to evaluate the implementation of our architecture. [ABSTRACT FROM AUTHOR]

Adder with high efficiency and accuracy is the major requirement for electronic circuit design. Here the optical logic gate based adder circuit is designed for better performance analysis of optical input signals varied with the wavelength. Efficiency of the adder can be improved by increasing the speed of operation, reducing the complexity and power consumption. To maintain the high efficiency with accuracy, a new combination of adder has been proposed and tested in this work. A new adder by combining the logics of Brent Kung, Sklansky and Kogge Stone adders by Tree Grafting Technique (BSKTGT) has been tested along with individual Brent Kung, Sklansky, Kogge Stone, Knowles, Han Carlson and Ladner Fischer adders. All the existing and proposed adders have been designed and tested for efficiency with the help of Cadence platform with 45 nm technology. Efficiency in terms of Size reduction, Power reduction, Power Delay Product (PDP) and accuracy in adding 8 bit, 16 bit and 32 bit values had been tested for all the adders and found that the 32 bit BSKTGT adder performed well in all aspects and have produced better efficiency with the power consumption of 52.512426 μW with 3.16% of power saving over Brent Kung adder, utilised an area of 631.191 with 8.55% reduction over Kogge Stone Adder, has the cell count of 132 which is 10.61% reduction over Brent Kung Adder and PDP value of 122.6695 J, which is 0.46% less than that of the Han Carlson Adder. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of collaborative robotic car-painting using a team of industrial manipulators that can be heterogeneous. Given the CAD model of the car, a collection of heterogeneous articulated robotic arms, and their corresponding fixed base positions on the factory floor/ceiling, the objective is to generate a collection of joint trajectories for each robot in a computationally efficient manner such that the car body can be painted by the nozzles attached to the arms while collisions during the painting process are avoided. Our solution to this computationally intensive collaborative coverage path planning relies on decoupling the collision avoidance from the coverage path planning by exploiting the inherent two-dimensional structure of the problem. In particular, our algorithm relies on partitioning the reachable space of the forearms of these robots, projecting the resulting volumes of intersection on the sides and the top of the car body, and performing the coverage planning on the resulting projected volumes. Simulation results on several industrial arms that are collaboratively painting a Ford Motor Company F-150 truck demonstrate the effectiveness of our proposed solution.

The combination of innovative advance and fluctuating client needs are paving the way to continuous changes in the manufacturing environments. As a result, mechanical enterprises aim for the honing of their processes by means of Computer Integrated Manufacturing (CIM). Their holy grail is connecting the shop floor systems to the high business layer systems. Based on our previous literature review on the CIM architectures available in the literature, we have identified six major aspects and detected the limitations of the existing appeals. We attempted to get the better of these fall backs and to be as exhaustive as to cover all 6 aspects through the BLAEM Architecture (Bi-Level Architecture for efficient Manufacturing). Through this paper, we will be presenting an execution of the BLAEM by means of a real case study. [ABSTRACT FROM AUTHOR]

Industry 4.0 is characterized by increased flexibility of production processes, a level of customization, a level of automation, smart manufacturing execution, and overall optimized production processes. Despite global competition, flexibility is a differentiation strategy applied by manufacturers to remain competitive. By incorporating flexibility in the manufacturing process of their products, enterprises can adapt faster to the demands. Enterprises need cost-effective, intuitive solutions to benefit from Industry 4.0 involving minimal efforts and integration costs. This study presents a new approach increasing the flexibility of manufacturing operations including robot trajectory, processing, and quality control. The results are tested in an industrial platform 4.0 installed in the laboratory. Our approach is to transform a rigid production system into an agile production system. For this, we break down the manufacturing process and reorganize it by programming core modules while maintaining the existing control structure but upgrading its programmable function to the Manufacturing Execution System Layer. Thus, the production manager can use the developed modules connected by flows to orchestrate a new production plan in a short time compared with the traditional approach. [ABSTRACT FROM AUTHOR]

Increasing the flexibility of robots needs systems more capable in perceiving and interacting with the environment. A challenge is still to easy design the robotic system around the application, especially when the objects to be manipulated are bulky, and the relative positions between the robot and the objects to be manipulated are uncertain and high precision is required to successfully complete a task. In this paper a possible guideline to design a system capable to localize itself, identify a target, bulky, object and manipulate it, is presented. A method for tuning the impedance control parameters is shown, to keep interaction forces below dangerous values. The autonomous localization, grasping and assembly of a sidewall panel of an airplane is used as test. Experiments show that the success rate of completing a task increases, combining vision perception and force control, with respect to the single use of visual localization and position control.

Programmable logic controllers (PLCs) are an established platform, widely used throughout industrial automation but poorly understood among researchers. This article gives an overview of the state of the practice, explaining why this settled technology persists throughout industry and presenting a critical analysis of the strengths and weaknesses of the dominant programming styles for today's PLC-based automation systems. We describe the software execution patterns that are standardized loosely in IEC 61131-3. We identify opportunities for improvements that would enable increasingly complex industrial automation applications while strengthening safety and reliability. Specifically, we propose deterministic, distributed programming models that embrace explicit timing, event-triggered computation, and improved security. [ABSTRACT FROM AUTHOR]

The ongoing changes in manufacturing require that new information models for industrial computer systems be developed and applied. This paper describes a concept for the material model as a “digital twin” for producing highly customised, smart electronic devices. The scope of the research is the transformation of the models that are typical for the currently used automation pyramid approach to Reference Architecture Models for Industry 4.0 (RAMI4.0). The ISA95 standard is used as the modelling tool and Open Production Connectivity Unified Architecture (OPC UA) as the communication middleware. The presented use case focuses on a rework operation that is performed during the short series production of highly customised electronic devices that are produced by the Aiut company. The paper focuses on the transformation from the static architecture of Manufacturing Execution Systems to flexible and dynamic information models.

Model-Based 3D engineering has gained wide popularity in recent times for various Computer-Aided Engineering applications, bypassing the need for 2D drawings, thereby creating an efficient digital thread, reducing development time and improving the product quality. With the use of model-based definition, most data required to design, analyze and manufacture aproduct is stored in digital format. The primary focus of the paper is to create aseamless digital thread for exchanging data from anative CAD file to astandard data format like ISO STEP AP242 and vice versa, which enables smart manufacturing by attaching product manufacturing information. Prior to STEP AP242, the only successful translation among CAD systems was for the boundary representation with very little or no manufacturing data. These standards will not be enough unless defined in amachine-readable format and are equipped with tools that can read/write from these data structures. The method presented enhances the neutral data format 'Constraint Tolerance Feature (CTF) Graph' to 'Augmented Constraint Tolerance (aCTF) Graph', which holds additional information required for manufacturing. This paper discusses the elements needed during CAD data exchange, for multiple CAE applications like Computer-Aided Tolerance Analysis, Computer-Aided Manufacturing, etc., and discusses the implementation of required translators. [ABSTRACT FROM AUTHOR]

This research considers a specific incremental sheet metal free-forming process, which allows for individualized component manufacturing. However, for a reasonable application in practice, an automation of the manual process is mandatory. Unfortunately, up to now, no general tool path generation strategies are available when free-forming processes are to be utilized. On this account, for the investigated driving process, a holistic concept for deriving tool paths for the production of sheet metal parts directly from a digital component model is presented adopting an artificial neural network architecture. Consequently, for the very first time an automated part production is possible in incremental sheet metal free-forming applications. For this, a suitable network input and output structure is designed. Balanced sample data sets are generated for appropriate training. An associated network topology is determined and undergoes a training and testing phase. The influence of different training algorithms, network configurations, as well as training sets have been studied in relation to a feedforward network structure with backpropagation. Finally, the proposed computer integrated manufacturing system is subject to validation and verification by automated sheet part production, which is followed by concluding remarks on the capabilities and limits of the concept. [ABSTRACT FROM AUTHOR]

This paper describes the results of a recent field study of computer integrated manufacturing (CIM) adoption strategies in U.S. manufacturing firms. The purpose of the study was to identify the extent to which CIM technologies are in use in U.S. firms, the impact of a facility's process characteristics on the CIM development process, and the adoption policy being followed implicitly or explicitly. The survey focused on manufacturing process characteristics, the CIM development process, the CIM architecture, and perceived value and benefits. Our results indicate that CIM implementations follow a definite temporal pattern with respect to the adoption of certain information technologies. We also find evidence of labor substitution through CIM, although the direct labor jobs that are lost are partially replaced by engineering and design tasks. While most CIM users find that their CIM projects successfully meet their initial operational goals, the technology seems to be poorly integrated in most sites. More crucially, it appears that CIM does not live up to its promise: it is not being adopted as a strategic information system for competitive missions. The initiative for CIM programs is usually generated from the bottom-up by small groups of technical experts who tend to focus on localized data-processing concerns. This gradual bottom-up approach appears to severely restrain, rather than enable, plant-wide integration for critical crossfunctional business processes such as order fulfillment or the introduction of new products. The decentralized, bottom-up, development pattern of these information systems reinforces the existence of many incompatible divisional islands of automation, thereby negatively affecting the competitive capability of the firm. [ABSTRACT FROM AUTHOR]

The paper is summarizing the research activities that had been carried out for defining an appropriate manufacturing concept and the system architecture for a manufacturing plant of pellet boilers. The concept has been validated through the implementation of a solution of computer integrated manufacturing that includes a CAD platform and a CAM facility including laser cutting machines, rolling and welding machines and advanced technologies for assembly, quality control and testing.

G-code is the language used to control computer numerical control (CNC) machines. Although most CAD/CAM software can generate G-code based on a design and machine tools needed, the ability to understand G-code is valuable, especially when a machining job does not run smoothly. Intelligent tutoring systems (ITS) have been shown to be successful in helping students to learn programming. However, G-code is different from general purpose computer programming languages. CNC programming also requires that students master many hardware-related facts and concepts, such as cutting speed and feed rate, and tools for several types of drilling. We built a web-based ITS for CNC programming called CNC-Tutor, and proposed a data-driven approach to generate proper hints and feedback during students' problem-solving process. The approach is based on finding past submissions that are most similar to a student's solution. The similarity is measured using a "behavior & machine state distance'' metric. The system was evaluated by 93 undergraduate students. Results suggest that the design is instructionally effective, and that students' subjective impressions of the system were positive. It also appears that CNC Tutor's explanations and feedback are a good fit for active, visual learners. [ABSTRACT FROM AUTHOR]

Manufacturing process monitoring systems is evolving from centralised bespoke applications to decentralised reconfigurable collectives. The resulting cyber-physical systems are made possible through the integration of high power computation, collaborative communication, and advanced analytics. This digital age of manufacturing is aimed at yielding the next generation of innovative intelligent machines. The focus of this research is to present the design and development of a cyber-physical process monitoring system; the components of which consist of an advanced signal processing chain for the semi-autonomous process characterisation of a CNC turning machine tool. The novelty of this decentralised system is its modularity, reconfigurability, openness, scalability, and unique functionality. The function of the decentralised system is to produce performance criteria via spindle vibration monitoring, which is correlated to the occurrence of sequential process events via motor current monitoring. Performance criteria enables the establishment of normal operating response of machining operations, and more importantly the identification of abnormalities or trends in the sensor data that can provide insight into the quality of the process ongoing. The function of each component in the signal processing chain is reviewed and investigated in an industrial case study. [ABSTRACT FROM AUTHOR]

Global competition and the growing need for rapid responsiveness of customers' orders necessitate the integration of planning, scheduling and control in manufacturing systems. This paper proposes an RFID event-driven integrated production planning and control (RED-IPPC) framework for such a need in a make-to-order Service-Oriented Architecture (SOA) - based production environment. Flexible Job-shop scheduling problems are used to demonstrate the applicability of the proposed framework by solving static schedules via optimisation algorithms and dynamic schedule via complex event processing (CEP) and heuristic rules if predefined operations deviate from the planned schedule under disturbances. And CEP is adopted to deal with real time RFID data. Simulation with ARENA and experiments based on the Rifidi Edge Serve are used to validate such applications. The use of RFID combined with CEP offers better context awareness and real-time responsiveness in production, and makes the proposed framework in process-linked applications in various systems from flexible manufacturing systems of high automation to those operated manually. [ABSTRACT FROM AUTHOR]

This paper proposes an extension of International Electrotechnical Commission (IEC) Common Information Model (CIM) to accomplish the interoperability requirements for the power system state estimation (SE). The proposed method utilizes a multiarea SE (MASE) approach, suitable for the power system networks, which can be divided into several independently controlled subareas. The standard IEC CIM model is extended for exchanging the SE results of the MASE from subareas to a central coordinator (CC) in the standard format, which might individually use diverse proprietary software applications and databases. The suggested schema defines the data exchange format among the subareas and the CC without modifying proprietary databases and software applications. The new MASE approach, used to demonstrate the proposed CIM extension process, requires lesser data exchange as there is no topology information exchange among the subareas and the CC, thus resulting in reduced communication bandwidth requirement. The effectiveness of the proposed approach has been demonstrated on IEEE 30 bus system and 246-bus reduced Northern Regional Power Grid Indian system. [ABSTRACT FROM PUBLISHER]

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