Browse Topic: Manufacturing equipment and machinery

Items (254)
Large-sized irregular castings are critical components extensively employed in large-scale equipment manufacturing. Due to their substantial dimensions and complex geometries, the assembly and docking processes between different components present significant challenges. To address the docking problem between large-scale irregular castings, this study proposes a casting docking method based on relative pose, along with a modeling approach for irregular castings, and accomplishes the docking process through the control of an industrial robot. Firstly, the current poses of feature points on the docking surfaces are measured. Based on these measurements, the relative pose transformation relationship between the center point of the docking surface and the robot’s Tool Center Point (TCP) is established, thereby constructing the docking model. This model calculates the relative deviation between the current pose and the theoretical pose. Subsequently, the robot motion is controlled according to this deviation to achieve precise docking. Finally, a simulation environment was built using KUKA. Sim Pro with Office Lite to simulate the docking process of large-sized irregular castings. The results demonstrate that the relative pose-based docking method effectively accomplishes the docking task. This study provides an effective solution for the docking of large-sized irregular castings.
Liu, HaoranJia, HailiWang, AiminXigang, FanPeidong, Su
Reliability evaluation aims to quantify the reliability level of equipment and to verify its compliance with reliability requirements. Existing reliability evaluation methods primarily rely on operational phase data, which means reliability evaluation may lag behind actual needs. In practice, both users and design teams are more concerned with how to estimate CNC machine tools’ reliability before they are put into operation. Moreover, current reliability evaluation methods usually ignore the design team’s influence on CNC machine tool reliability. To overcome these limitations, this study proposes a novel reliability evaluation method that accounts for the influence of the design team on the reliability of CNC machine tools. By analyzing the impact of the design team’s technical capabilities and reliability capabilities on CNC machine tool reliability, a set of quantifiable evaluation indicators was established. Then, the weight coefficients of all indicators were determined using the expert scoring method. Finally, all data were integrated using the vector projection method, which enabled a quantitative reliability evaluation of CNC machine tools from different design teams within the same category. Additionally, the proposed method was applied to conduct practical case studies on multiple CNC external cylindrical grinding machine tools designed by different design teams, thereby validating the feasibility of the proposed method. The reliability evaluation results not only determine the reliability level of each CNC machine tool but also identify the weak points in the technical capabilities and reliability competencies of each design team. This study concludes by discussing the significance of this approach for enhancing the reliability capabilities of design teams and its practical implications for end users.
Sun, DongyangZheng, WeixuChu, HongyanXu, JingjingCheng, Qiang
Precisely detecting multi-stage degradation (MD) in rolling bearings is crucial for keeping equipment in good shape. Yet, health indicator (HI) crafted with current single-method strategies often can't balance degradation sensitivity and monotonicity across different operating conditions. Also, common MD detection methods struggle to spotransitional samples between degradation stages in cross-condition settings. To tackle these challenges, this paper introduces a new cross-condition MD detection approach for bearings, which relies on a health indicator matrix (HIM) and a transition sample enhanced network with multi-branch encoding (TSEN-MBE). First, a degradation-sensitive health indicator (DSHI) is constructed by integrating the least absolute shrinkage and selection operator (LASSO) algorithm — with comprehensive fault frequency energy (CFFE) as the regression target — and the grey wolf optimizer (GWO), capturing intrinsic degradation characteristics of bearings. Meanwhile, to enhance the monotonicity of unsupervised HIs, a time-weighted Wasserstein distance (TWWD) metric is proposed by incorporating temporal degradation features into the Wasserstein distance-based HI construction. The DSHI and TWWD are subsequently combined to generate the HIM. This HIM serves as the driving force for the Gath-Geva (GG) fuzzy clustering algorithm, enabling it to adaptively allocate MD labels according to varying operating conditions. Ultimately, the TSEN-MBE model is constructed, employing multi-branch Transformer encoders integrated with multi-head attention mechanisms to encode and combine heterogeneous features. A joint loss (JL) function — comprising transition sample enhancement (TSE), local maximum mean discrepancy (LMMD), and cross-entropy (CE) losses — is designed to enhance the recognition of transitional samples and improve cross-condition MD identification accuracy. Experimental results on the XJTU-SY dataset validate the effectiveness and superiority of the proposed method, showing that DSHI achieves the highest average degradation angles, TWWD obtains optimal monotonicity, and TSEN-MBE outperforms comparative methods in cross-condition recognition tasks.
Ma, JinghuaWei, LaiHu, GuangqiaoYu, Xiaoxia
During the high-speed operation of packaging machines, if the abnormal components evolve into faults, the packaging machines often stop for inspection or even damage, causing production stagnation and huge economic losses. If key variables are predicted and faults are identified before the evolution of packaging machine failures, it is of great significance to ensure equipment safety and reduce maintenance costs and losses for enterprises. The purpose of fault prediction is to use the information modeling of equipment historical data to output the changes in key features before component failures in the future. Firstly, for the redundant data of multiple measurement points of the same variable in the packaging machine process variables, Pearson correlation analysis is used to obtain more accurate variable data. We reuse adaptive empirical mode decomposition (EEMD) for signal processing and feature extraction, reduce redundant information, use convolutional neural network (CNN) models for spatial feature learning, and then use bidirectional long short-term memory models to capture temporal dependencies of CNN information for capturing time series data. A model is established on the normal training set to fit the normal state of the packaging machine, identify different types and degrees of equipment fault characteristics through normal test set data, and send the predicted results of the equipment state to the fault classifier for judgment to determine whether to issue a fault warning. The results indicate that this article has validated the effectiveness of the model in fault feature extraction and high-precision fault classification through training on equipment status data.
Wu, AiminLiu, ShixianZhao, LihuiLiu, ZhaoWu, TaoLi, Lianbing
In order to achieve precise control of refueling volume, improve oil change efficiency, reduce oil pollution and waste, a new oil change device for the reducer of the range hood equipment is studied. We design a new oil change device that integrates oil discharge and refueling functions based on the operating characteristics of the reducer in the range hood equipment. Using the rotational speed of the power pump and the flow rate of the oil pipeline as variables, we determine the refueling flow rate using a one-dimensional quadratic formula. Based on direct control theory, we optimize the relative position parameters of each component of the device, establish a control matrix, and achieve precise control. The experimental results show that the new oil change device exhibits good performance during both one-time oil discharge and refueling processes, meeting the precise control standards for refueling volume. The design and application of a new oil change device can effectively improve the efficiency and accuracy of oil change in the reducer of the range hood equipment, and have practical application value.
He, PengtaoWei, BoLiang, ZhiyuanDeng, WeirenLiang, WenbinXing, Yuquan
To obtain additional space for industrial sorting and assembly line labeling operations, this study conducts an analysis of the four-bar mechanism. Based on this analysis and combination, the redundant parallel mechanism is introduced. That is, on the basis of the traditional parallel mechanism with central rotation, the objective of expanding the working space is achieved. The degree of freedom of the screw theory and the disparities between the working space of this mechanism and that of the traditional mechanism are analyzed. Finally, through application analysis, it is demonstrated that the working space of this mechanism is variable and that the mechanism can adapt to diverse workplaces.
Li, WenqianZhang, Xiaojie
Five-Axis CNC machines have become essential for creating the complex geometries demanded by industries such as aerospace and defense. These advanced machines offer superior part accessibility and minimize the need for repositioning, enabling shops to eliminate secondary set-ups and post-processing. However, for many machine shops, unlocking the full performance potential of five-axis equipment requires more than sophisticated motion control: it also demands higher spindle speeds. Traditional five-axis machines often top out at spindle speeds between 6,000 and 15,000 RPM. While this is sufficient for heavy roughing operations using large diameter tools, when it comes to finishing intricate features or micro-drilling, small tools require consistent spindle speeds of 40,000 to 90,000 RPM on the toolpath to function effectively. Without that capability, shops risk poor surface finishes, broken tools and unacceptably long cycle times. This is where governed high-speed air-driven spindles offer a transformative upgrade.
Friction stir welding (FSW) of Al 6063 alloy plates of 6 mm thickness was investigated in the present study for exploring the mechanical attributes of the welded joints. The tool profile significantly influences the quality of joints produced by FSW. In the current study, the influence of tool profile and FSW process parameters on the FSW weld characteristics of similar joining of Al 6063 plates has been investigated. The effect of FSW tool rotational speed (TRS) and tool travel speed on the FSW weld properties, mainly microstructure characteristics, microhardness, and ultimate tensile strength (UTS), have been studied. Comparison of two different tool profiles, namely taper and cylindrical tool, has also been examined. The effect of transient temperature distribution has also been studied for varying FSW process parameters. When increasing the tool’s rotational speed from 800 to 1200 rpm at a fixed traverse speed of 80 mm/min, a rise in peak temperature is observed. Conversely, increasing the traverse speed from 80 to 100 mm/min while keeping the rotational speed constant at 1200 rpm results in a decrease in the peak temperature. Expanding the TRS from 800 to 1200 rpm—while keeping the welding speed constant at 80 mm/min—leads to a wider FSW weld nugget zone. Under the same welding conditions, the average microhardness of the nugget zone decreases as a result of this increase in TRS. Additionally, as the TRS increases from 800 to 1000 rpm at a steady traverse speed of 80 mm/min, the UTS improves and reaches a peak of about 235 MPa, which is close to the strength of the base material. When the rotational speed is further increased to 1200 rpm, the UTS drops to approximately 150 MPa, likely due to overheating, which may cause grain coarsening or softening in the welded region.
Kumar, PramodKumar, VikashKumar, GulshanArif, AbdulPrasad, Chitturi RamZubairuddin, M.
This paper reports on a new design of semi-automatic riveting machine designed to be affordable. This work started in 2024. There are no customers yet. The machine is all electric. The machine installs interference bolts as well as squeeze rivets. Cost is a key criterion. The machine must feed a wide variety of fasteners. This machine is called Flexriveter.
Zieve, PeterReznicek, Jeffrey
The segment manipulator machine, a large custom-built apparatus, is used for assembling and disassembling heavy tooling, specifically carbon fiber forms. This complex yet slow-moving machine had been in service for nineteen years, with many control components becoming obsolete and difficult to replace. The customer engaged Electroimpact to upgrade the machine using the latest state-of-the-art controls, aiming to extend the system's operational life by at least another two decades. The program from the previous control system could not be reused, necessitating a complete overhaul.
Luker, ZacharyDonahue, Michael
The increasing reliance on lithium-ion batteries in manufacturing necessitates advanced monitoring techniques to ensure their longevity and reliability. Cloud technology offers a solution by enabling real-time data collection, analysis, and accessibility, facilitating thorough monitoring and predictive maintenance. Digital twin technology, creating a virtual replica of the physical battery system, provides a platform for simulating real-world conditions and predicting potential issues before they arise. By integrating sensor data and historical usage patterns, the digital twin model can accurately predict battery degradation, aiding in timely maintenance strategies. This proactive approach enhances battery operational efficiency and extends lifespan, leading to cost savings and improved safety. The paper explores using cloud-based monitoring systems to enhance the health estimation and management of lithium-ion batteries. A comprehensive feasibility study on adopting battery digital twin technology for electric two-wheeler and three-wheeler manufacturers examines creating a digital twin model for batteries and validating corresponding tests. Furthermore, the research discusses the technical challenges and solutions associated with implementing digital twin technology in manufacturing. Key metrics such as state of charge (SoC) and state of health (SoH) are analyzed to showcase the effectiveness of the digital twin model in real-world applications.
Zeeshan, MohammadAkre, Vineet
This article addresses the machines and automated guided vehicles (AGVs) concurrent scheduling with alternative machines in a multi-machine flexible manufacturing system (FMS) in order to provide the best optimum sequences for the minimization of makespan (MKSN).The assignment of AGVs and related trips, such as the dead headed trip and loaded trip times of AGVs to jb-ons, as well as the decision to select machines for job-operations (jb-ons) and the sequencing of jb-ons on the machines, make this problem extremely difficult to solve. This paper offers a mixed integer nonlinear programming (MINLP) formulation for modeling the problem, as well as the crow search algorithm (CSA) to solve the problem. For verification, a manufacturing company's industrial problem is employed. The findings indicate that CSA performs better than the existing techniques, and that the utilization of alternative machines for the operations can bring the MKSN and cost down.
Mareddy, Padma LalithaReddy K, AjayaKatta, Lakshmi NarasimhamuSiva Rami Reddy, Narapureddy
In automotive applications, most of the engineering components come across the material removal process in manufacturing. Face milling is one of the prominent material removal processes wherein a multi-point cutter is used to machine the flat workpiece to bring it to its required dimension. In the material removal process, the cost of the cutting tool occupies the major part of the total manufacturing cost of a product. Also, the continuous usage of the cutting tool results in tool wear. The usage of the cutting tool after the threshold value of the tool wear deteriorates the surface finish of the workpiece which leads to product rejection. Hence, optimal tool usage is inevitable. The continuous monitoring of the cutting tool condition will ensure optimal tool usage. In the present work, four real-time tool conditions are considered, namely, fresh tool (G), tool flank wear (FW), tool flaking on rake surface (FL) and tool with broken tip (B). Vibration signals are acquired while milling mild steel workpiece with cutting tools of considered conditions. From the vibration signal, Discrete Wavelet Transform (DWT) features are extracted and the top-ranked wavelet member in terms of classification accuracy of the tool condition is selected using the Decision Tree (DT) algorithm. The Mean Squared Energy (MSE) of the detailed coefficients of the selected wavelet member is computed and that forms the features set. Then the classifying ability of Machine Learning (ML) algorithms such as Support Vector Machine (SVM), and Naïve Bayes (NB) are analysed using the feature set. The results show that the NB outperformed the SVM with the MSE of selected wavelet members derived from DWT.
D, Pradeep KumarSyed, ShaulV, MuralidharanS, Ravikumar
To avoid equipment failures in automotive manufacturing activities, particular attention is paid to the design of an effective preventive maintenance strategy model for automotive component processing equipment. The selection of appropriate maintenance intervals as well as the equilibrium between the benefits and costs should be the primary challenges in high-quality maintenance process. In this study, a reliable preventive maintenance strategy model is proposed and the aim is to suggest an appropriated approach for the selection of maintenance intervals from a comprehensive view of importance, hazard, and maintenance cost. First and foremost, a new Fermatean fuzzy entropy (FFE) measure method on the basis of analytic hierarchy process (AHP) is innovatively employed to access more objective weights of each indicator. Moreover, a more objective scoring of importance and hazard indicator is executed to aggregate the expert group judgments. Furthermore, this study emphasizes the introduction of a stable equipment reliability distribution, which is obtained using scientific regression on the basis of failure data. Thus, the maintenance cost of the equipment could be derived based on the equipment’s reliability. As a consequence, the prediction of the probability of failure occurring and preventive maintenance cycle are well validated. In conclusion, the preventive maintenance strategy established in the study not only reduces the inherent subjectivity in multi-criteria decision analysis, but also improves the accuracy of equipment failure probability prediction. Hence, it offers novel perspectives on optimized maintenance intervals and the balance between benefits and costs.
Ma, ZexinPan, ZheshengWang, ChengxiangWei, MingxinYu, WenbinLi, GuoxiangZhao, FeiyangZhu, Sipeng
In the 1990s and early 2000s, the field of parallel kinematics was viewed as being potentially transformational in manufacturing, having multiple potential advantages over conventional serial machine tools and robots. Many prototypes were developed, and some reached commercial production and implementation in areas such as hard material machining and particularly in aerospace manufacturing and assembly. There is some activity limited to niche and specialist applications; however, the technology never quite achieved the market penetration and success envisaged. Yet, many of the inherent advantages still exist in terms of stiffness, force capability, and flexibility when compared to more conventional machine structures. This chapter will attempt to identify why parallel kinematic machines (PKMs) have not lived up to the original excitement and market interest and what needs to be done to rekindle that interest. In support of this, a number of key questions and issues have been identified which need to be explored to advance the technology further. In this chapter, we establish the history and current state of the art of PKMs and identify key issues that unlock the technology’s potential. We have sought the views of recognized thought leaders to understand the practical limitations that have hindered deployment and what, if anything, can be done to move the technology forward given the prospective advantages.
Muelaner, JodyWebb, Philip
Vacuum suction cups are used as transforming handles in stamping lines, which are essential in developing automation and mechanization. However, the vacuum suction cup will crack due to fatigue or long-term operation or installation angle, which directly affects production productivity and safety. The better design will help increase the cups' service life. If the location of stress concentration can be predicted, this can prevent the occurrence of cracks in advance and effectively increase the service life. However, the traditional strain measurement technology cannot meet the requirements of tracking large-field stains and precise point tracking simultaneously in the same area, especially for stacking or narrow parts of the suction cups. The application must allow multiple measurements of hidden component strain information in different fields of view, which would add cost. In this study, a unique multi-camera three-dimensional digital image correlation (3D-DIC) system was designed and applied to measure the strain concentration of the suction cups while the cups were running the pulling progress. In this technique, a multiplexed quad-cameras DIC system which contains two sets of 3D-DIC system (4 cameras) with different field of view or different measurement directions enables simultaneous measurement of full-filed and hidden parts under the same calibration progress. The first two cameras built a sub-group of the 3D-DIC system, which was used to measure the local strain of the narrow or stacked prats. The other system was used to acquire the strain fields of the entire suction cup. In addition to the experimental test, the fatigue test to see the cracks appeared location. The results of DIC were compared to the fatigue data, and the DIC experimental data validated the crack location. This project aims to help designers and operators thoroughly understand the performance of vacuum cups by investigating the strain concentration and crack location.
Guo, BichengZheng, XiaowanFang, SiyuanYang, Lianxiang
One of the imaging technologies that many robotics companies are integrating into their sensor packages is Light Detection and Ranging (LiDAR). Now Duke engineers have developed a new LiDAR system that can potentially improve the vision of autonomous systems such as driverless cars and robotic manufacturing plants.
This standard has notes/guidance narratives interspersed throughout. These notes/guidance narratives are identified by a header and by text in italics. This standard defines a series of requirements that results in a specific AM machine qualified to produce material (see GN1) in compliance to an aerospace materials specification. The machine control and/or configuration types are discussed in the next sections. The industry (including AIA and ASTM) generally acknowledges that there are three qualification milestones for AM machines; nevertheless, this document will focus only on the initial two stages, namely: Installation Qualification (IQ): Producing objective evidence to show that all key aspects of the process equipment and ancillary system installation adhere to the AM Part Producer’s specification and that the recommendations of the supplier of the equipment are suitably considered; this is tied to a specific machine serial number. Operational Qualification (OQ): Establishing sufficient process control to maintain stable material performance and demonstrating that the material specification requirements can be met; this is also tied to a specific machine serial number (see GN2).
AMS AM Additive Manufacturing Metals
Contrary to popular opinion, Henry Ford didn’t invent the automotive assembly line. That was Ransom Olds of Oldsmobile fame, who reportedly patented his novel manufacturing approach in 1901. Twelve years later, Ford simply took Olds’ good idea and made it better. Much better, it seems. Rather than using a stationary line like Oldsmobile, the Ford Motor Company founder added a moving conveyor, thereby reducing worker fatigue while drastically increasing production throughput. The concept stuck, and more than a century later, the moving assembly line remains an integral piece of most automobile manufacturing.
Any manufacturing facility that uses hydraulics powered by conventional fixed-speed hydraulic power units (HPUs) has engineers and personnel who know all too well how large, noisy, and inefficient older HPUs can be. In the past, such features were simply an accepted part of the manufacturing environment. But now, advances in engineering and design have led to new variable-speed power units that are smaller, quieter, and more efficient, intended for use in a wide variety of applications, and can directly replace traditional hydraulic systems.
Researchers have developed a robot that uses radio waves, which can pass through walls, to sense occluded objects. The robot, called RF-Grasp, combines this powerful sensing with more traditional computer vision to locate and grasp items that might otherwise be blocked from view. The advance could one day streamline warehouse operations or help a machine pluck a screwdriver from a jumbled toolkit.
As Industry 4.0 evolves, the use of more sophisticated robots, as well as advanced automation and control systems within industrial applications has become more common as companies continue their pursuit to increase efficiency and profitability.
The field of parallel kinematics was viewed as being potentially transformational in manufacturing, having multiple potential advantages over conventional serial machine tools and robots. However, the technology never quite achieved market penetration or broad success envisaged. Yet, many of the inherent advantages still exist in terms of stiffness, force capability, and flexibility when compared to more conventional machine structures. Deployment of Parallel Kinematic Machines in Manufacturing examines why parallel kinematic machines have not lived up to original excitement and market interest and what needs to be done to rekindle that interest. A number of key questions and issues need to be explored to advance the technology further. Click here to access the full SAE EDGETM Research Report portfolio.
Webb, Philip
This SAE Standard establishes the minimum performance requirements for pelvic restraint systems (seat belts, anchorages, and the fastening elements of seat belts) necessary to restrain an operator or rider within a roll-over protective structure (ROPS) in the event of a machine roll-over, as defined in ISO 3471, ISO 8082-1, ISO 8082-2, ISO 12117-2, and ISO 13459, or tip-over protection structure (TOPS), in the event of a machine tip over as defined in ISO 12117. This standard provides guidance and recommendations for information included in the machine operator manual.
HFTC4, Operator Seating and Ride
Manufacturing workpieces with unique material characteristics can provide machining challenges. The metal beryllium is an excellent example. Beryllium is two-thirds the weight of aluminum and six times as stiff as steel. It has a high melting point and a very low range of thermal expansion. Those attributes deliver performance that is crucial in precision applications such as aircraft components, spacecraft, communication satellites and optics. However, beryllium is also hard and brittle and produces powder instead of chips when machined, therefore requiring special machining techniques to avoid cracking. It is also expensive, about $1,500 a pound. And finally, it is toxic and causes severe allergic reactions in those sensitive to it. As such, only a few shops in the United States are the lone providers of parts made from this tricky material. One of those is a California shop that combines a deliberate, highly structured production process; data-driven manufacturing analytics; precise and reliable machine tools; and longtime familiarity with processing beryllium to manufacture parts profitably and safely. Founded in 1954, L.A. Gauge Company in Sun Valley, California, is an ultra-precision machining and optic shop focusing on specialty metal fabrication for the aerospace and defense Industry. The shop regularly holds machining tolerances to within 40 millionths of an inch (1 micron), and polishing tolerances to within billionths of an inch (1 Angstrom).
There’s no doubt that Industrial Ethernet (IE) is paving the way for the automated factory of the future. IE is the backbone of modern industrial communications between devices on the plant floor, the enterprise information network, and the cloud services that companies increasingly rely upon to build and grow their business. At the macro level, IE is as essential to automation control as the internet is to e-commerce.
This specification prescribes process requirements for batch processing of used, metal powder originating from an existing additive manufacturing process workflow for reuse in subsequent additive manufacturing of aerospace parts in non-closed loop additive manufacturing machines. Such powders may be pre-alloyed or commercially pure. This specification is not limited to a specific additive manufacturing process workflow as the originating source of material to be reused. It is intended to define those procedures and requirements necessary to achieve required cleanliness and performance of metal powder feedstock to be reintroduced into the same additive manufacturing process from which such powder originated. This specification is intended to be used in conjunction with relevant AMS powder specifications and AMS process specifications for additive manufacturing. Unless otherwise specified, powder prepared for reuse following this specification is intended to be conforming in physical and chemical attributes as defined by the originating virgin powder specification for the purposes of producing aerospace parts, providing equivalent characteristics and properties as specified by the corresponding AMS material specification.
AMS AM Additive Manufacturing Metals
Industries are currently going through “The Fourth Industrial Revolution,” as professionals have called it “Industry 4.0” (I4.0). Integration of physical and digital systems for the product life cycle mainly concerns Industry 4.0. With the appearance of I4.0, the concept of prediction management has become an unavoidable tendency in the framework of big data and smart manufacturing. At the same time, it offers a reliable solution for handling test fatigue failures. AI and its key technologies play an essential role - 1 to make industrial systems autonomous like predicting test failures 2 to make possible the automatized data collection from industrial machines/components. Based on these collected data types, machine learning algorithms can be applied for automated failure detection and diagnosis. However, it is a bit difficult to select appropriate machine learning (ML) techniques, type of data, data size, and equipment to apply ML in industrial systems. Selection of inappropriate technique, dataset, and data size may cause time loss and infeasible result prediction. Therefore, this study aims to present a comprehensive case study of predicting the testing failure using ML techniques. This work presents a novel approach for different parameter- based fatigue failure (rig testing failure) characterization using artificial intelligence (AI). The deep learning algorithm is trained on carefully collected physical testing data (historical data), which helps in predicting the new product development testing failure cycles based on basic design parameters available at the start of the program such as loading, component dimensions, distances, and inclination angle, etc. Rig testing reveals the testing cycles which indicate either failure or non-failure of the component (depending upon the passing criteria). Thus, every driveline component subjected to this research work generates at least one data set (testing values from AI). Based on this study, a conservative failure prediction accuracy of 88% is achieved. So, this methodology is pioneering to predict fatigue failure without - 1 comprehensive expensive physical testing. 2 the need for extensive, error-prone, use of complex assessment methodologies With expert knowledge of evaluation procedures, the developed AI approach enables quick and reliable prediction of fatigue failure of components based on elementary key design parameters which can reduce the overall design cycle time.
A robotic system called RFusion is a robotic arm with a camera and radio frequency (RF) antenna attached to its gripper. It fuses signals from the antenna with visual input from the camera to locate and retrieve an item, even if the item is buried under a pile and completely out of view. The RFusion prototype relies on RFID tags, which are cheap, battery-less tags that can be stuck to an item and reflect signals sent by an antenna. Because RF signals can travel through most surfaces, RFusion is able to locate a tagged item within a pile.
Industrial programmable logic controllers (PLCs) and their associated operations technology (OT) software and communication protocols have traditionally been best suited for localized installations. They lacked the computing performance, connectivity options, and security needed to easily integrate them with higher-level information technology (IT) resources.
In 1901, a patent was issued to Ransom E. Olds for the idea of a continuously moving assembly line, which he used to build the first Oldsmobile vehicles. In 1913, Henry Ford improved the concept by adding moving conveyor belts and with these two innovations, the time needed to assemble a car went from 1½ days to 1½ hours. The modern assembly factory was born.
There are some tasks that traditional robots — the rigid and metallic kind — cannot perform. Soft-bodied robots may be able to interact with people more safely or slip into tight spaces with ease. But for robots to reliably complete their programmed duties, they need to know the whereabouts of all their body parts. That’s a difficult task for a soft robot that can deform in an infinite number of ways.
This SAE Recommended Practice establishes minimum performance and test requirements for combination pelvic and upper torso occupant restraint systems provided for off-road self-propelled work machines.
HFTC4, Operator Seating and Ride
A new algorithm significantly speeds up the planning process required for a robot to adjust its grasp on an object by pushing that object against a stationary surface. Whereas traditional algorithms would require tens of minutes for planning out a sequence of motions, the new approach shaves this preplanning process down to less than a second. This faster planning process will enable robots, particularly in industrial settings, to quickly figure out how to push against, slide along, or otherwise use features in their environments to reposition objects in their grasp. Such nimble manipulation is useful for any tasks that involve picking and sorting, and even intricate tool use.
Capacity planning is one of the major factors in saving capital and avoiding unnecessary costs in any manufacturing system particularly large original equipment manufacturers (OEMs). However, many manufacturing systems still suffer from huge costs incurred due to a lack of applying a robust capacity planning optimization model. Most of the developed models in literature do not consider real-life situations in manufacturing systems and, hence, are not easy to implement. In this paper, a novel capacity planning optimization model considers various important features of a manufacturing system. The objective function of the model is to minimize the weighted sum of the total number of assets and changeovers. A unique feature of the developed model is the capability of providing the number of additional required assets of each type in case the existing assets are not capable of covering the entire demand. The other unique feature is providing the utilization percentage of each asset and, hence, identifying underutilized and overutilized assets. This will give great insight to planners about the possibility of saving even more assets by increasing the capability of some machines through adding tooling and/or reprograming them. The developed model, as a capacity planning tool, has been deployed in some of Ford Motor Company’s plants, and it has shown potential to save millions of dollars for the studied programs. The model can easily be used in different manufacturing systems, plants, and OEMs. A real case study is provided for illustration.
Navaei, JavadMaxwell, BryanHassan, NazmulKalamdani, RajeevAustin, Rosaleen
You may not be able to see them but power anomalies that originate within your automated control system are costing you expensive downtime. Your automated production equipment has a low tolerance for poor power quality, especially if it is controlled by a PLC(s).
Lithium-metal batteries, capable of doubling the capacity of today’s standard lithium-ion cells, can be built utilizing much of the current Li-ion battery manufacturing process, according to researchers at the University of Michigan. Their findings, part of a project supported by the U.S. Department of Energy, remove a major hurdle for automakers looking to embrace the next major evolution in energy storage technology for electric vehicles (EVs).
Linear motion components such as bearings, shafts, actuators, and slides are heavily utilized in many types of industrial machines, so the more that engineers can streamline component design, configuration, and ordering, the more they can lower their production costs.
As vacuum suction cups are widely used in stamping plants, it becomes urgent and important to understand their performance and failure mode. Vacuum suction cups are employed to lift, move, and place sheet metal instead of human hands. Occasionally the vacuum cups would fail and drop parts, even it would cause expensive delays in the production line. In this research, several types of vacuum cups have been studies and compared experimentally. A new tensile device and test method was developed to measure the pulling force and deformation of vacuum cups. The digital image correlation technique has been adopted to capture and analyze the contour, deformation and strain of the cups under different working conditions. The experimental results revealed that the relevant influential parameters include cup type, pulling force angles, vacuum levels, sheet metal curvatures, etc. Also, the deformation distribution and history of the cups denote the weak part and failure mechanism during operation. Moreover, this work could help designers and operators thoroughly understanding the performance of vacuum suction cups and greatly improved in further work.
Xu, WanZhang, BoyangWang, RongMa, WenGuo, BichengYang, Lianxiang
A novel Spatially Optimized Diffusion Alloy (SODA) material has been developed and applied to exhaust systems, which are an aggressive environment subject to high temperatures and loads, as well as excessive corrosion. Traditional stainless steels disperse chromium homogeneously throughout the material, with varying amounts ranging from 10% to 20% dependent upon its grade (e.g. 409, 436, 439, 441, and 304). SODA steels, however, offer layered concentrations of chromium, enabling an increased amount along the outer surface for much needed corrosion resistance and aesthetics. This outer layer, typically about 70μm thick, exceeds 20% of chromium concentration locally, but is less than 3% in bulk, offering selective placement of the chromium to minimize its overall usage. Since this layer is metallurgically bonded, it cannot delaminate or separate from its core, enabling durable protection throughout manufacturing processes and full useful life. The core material may be comprised of various grades, however, this study employs interstitial free steel (low carbon), which eases manufacturing operations, as it is more formable than stainless steel grades. The material and its manufacturing process are described, including characterization measurements comparing its forming and corrosion resistance response to baseline exhaust materials. Rolled mufflers are manufactured with high-volume manufacturing equipment and processes without incident, demonstrating the ease of material substitution versus aluminized 409 stainless steel (409AL). Each application is exposed to various test conditions, including fatigue, corrosion, and thermal cycling and compared against baseline materials. Results overall demonstrate favorable performance, even along exposed and welded edges, which may be further protected locally with cold spray. SODA offers unique value in performance versus baseline materials, enabling a competitive alternative with much less chromium.
Kotrba, AdamQuan, TonyWei, WinstonDetweiler, ZacharyKeifer, DavidBullard, Daniel
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