Browse Topic: Computer integrated manufacturing

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AI-Driven Predictive Methodology for Bolt Integrity in Vehicle Durability Testing2026-26-0648To be published on 01/16/2026
The application of AI/ML techniques to predict truck tailgate bolt loosening represents a major innovation for the automotive industry, aligning with the principles of Industry 4.0. Traditional physical testing methods are both expensive and time-consuming, often identifying issues late in the development process and necessitating costly design changes and prototype builds. By harnessing AI/ML, manufacturers can now analyze tailgate slam and bolt preload data to accurately forecast potential bolt loosening issues. This predictive capability not only enhances quality and safety standards but also significantly reduces the costs associated with tooling and builds. The AI/ML tool described in this paper can simulate a variety of load conditions and predict bolt loosening with over 90% accuracy, considering factors such as changes in loads, bolt diameters, washer sizes, and unexpected masses added to the tailgate. It provides valuable design insights, such as recommending optimal bolt
Sivakrishna, Masani, Das, Mahat, Singh, Abhinav, karra, Manasa, Shienh, Gurpreet, Luebke, Amy
Transforming Gear Manufacturing_ A Deep Learning Approach to Quality Prediction2026-26-0646To be published on 01/16/2026
The automotive industry is rapidly transitioning towards Industry 4.0, transforming vehicle manufacturing. To achieve a lower carbon footprint, it is crucial to minimize raw material wastage and energy consumption. Reducing component wastage, lead time, and automating gear manufacturing are key areas. Gear micro-geometry inspection is vital, as variations affect service life and NVH (Noise, Vibration, Harshness). Despite standards for permissible errors, manual evaluation is often needed.This subjective evaluation approach will have a possibility that a gear with undesired variations gets assembled into the product. These issues can be detected during NVH testing, leading to replacement of part and re-assembly thus increasing lead time. This generates a need for an automated system which could reduce the human intervention and perform the activity. This paper discusses methodologies to meet these requirements and achieve desired results. The research aims to develop a deep learning
Ramakrishnan, Gowtham Raj, Baheti, Palash, PR, Vaidyanathan, Durgude, Ranjit, Bathla, Archana, R, Greeshmita, V, Rangarajan
Transforming Manufacturing: Increasing Throughput and Reducing production Complexity with Digital Twins2026-26-0449To be published on 01/16/2026
In traditional manufacturing, increasing production line capacity often involves physical trials, leading to downtime, high costs, and operational risks. This paper presents a bidirectional digital twin developed for the Fischertechnik Smart Factory Kit, enabling real-time simulation and validation of production line modifications before actual deployment. The digital twin integrates with a Siemens PLC to mirror real-world operations, capturing live production data and visualizing key parameters like cycle time and machine utilization in a 3D environment. Engineers can test various optimization scenarios adjusting conveyor speeds, optimizing robot paths, and modifying buffer sizes to enhance efficiency. The best-performing configurations are identified based on throughput, cycle time, and resource utilization, and validated changes are automatically deployed to the PLC, ensuring seamless implementation. Beyond capacity optimization, this solution improves overall production efficiency
Kumar, Rahul, Singh, Randhir
Nexifi11D: A Comprehensive Multidimensional Framework for Futuristic Manufacturing Ecosystems2026-26-0282To be published on 01/16/2026
The manufacturing sector is undergoing a paradigm shift driven by hyper-connectivity, sustainability imperatives, and accelerated digital transformation. Conventional systems, however, remain constrained by their focus on isolated optimizations—such as predictive analytics, IoT-enabled sensing, or workforce scheduling—without providing an integrated operational perspective. To address this fragmentation, Nexifi11D is introduced as a comprehensive, multidimensional framework that consolidates 11 critical dimensions of manufacturing into a unified ecosystem. Nexifi11D advances beyond traditional Industry 4.0 architectures by seamlessly integrating intelligent algorithms, immersive simulation technologies, IoT infrastructure, and predictive systems within a scalable, interoperable mesh. The framework breaks down silos across key manufacturing domains—such as sustainability, cost, operations, and workforce—enabling holistic, data-driven, and proactive decision-making. Each integrated
Kumar, Rahul, Singh, Randhir
Virtual Reality in Assembly Simulations: Outpacing Tecnomatix Process Simulate for Faster Time-to-Market2026-26-0398To be published on 01/16/2026
Virtual Reality (VR) technology is emerging as a transformative solution in manufacturing industry. It offers significant advantages over traditional tools like Tecnomatix Process Simulate (PS) in assembly and ergonomic simulations. Analysis using PS is time consuming and lacks real time human interaction as it relies on detailed modelling and sequential workflows, which will delay the identification of assembly no-build conditions and ergonomic issues. This paper evaluates the time and cost saving potential of VR in assembly processes and explores its role in minimizing the need for physical prototypes across various stages of vehicle development. VR provides interactive environments, enabling interaction with 3D models and real-time collaboration with various teams across the globe. This leads to faster identification of assembly process flaws, quicker iteration cycles, and a reduced need for physical prototypes in the station development process for the lines. VR allows individuals
Nagendran, Rakesh Kumar
A unified Framework for Industry 4.0 based Automotive Homologation in India2024-26-036001/16/2024
The term Industry 4.0 is well known in contemporary automotive landscape. It encompasses a smart integrated framework of IoT (Internet of Things) and industrial automation with machine learning, artificial intelligence and big data analytics to arrive at optimal solutions to running the processes in a streamlined, efficient and effective manner. Industry 4.0 has assumed critical significance in the contemporary era of people working from remote locations to operate processes in order to build products, thus ensuring business continuity. Consequently, it follows that if industry 4.0 is applied to automotive homologation activity, it will lead to better evaluation, better fidelity of testing and accurate judgement of the product under test with regards to its certification. The author hereby elucidates a unified Industry 4.0 Framework for Automotive homologation in India which is the need of the hour. This framework consists of five elements. The first is use of IoT to ensure optimal use
S Thipse, Yogesh
Blockchain Enabled Sustainability in Industry 4.0 for Aerospace domain2022-26-116205/26/2022
Industry 4.0 is a fusion of the innovative production practices that enable manufacturers to accomplish their business objectives in a lot more agile manner. Investigation has been performed on various Industry 4.0 technologies like Artificial Intelligence, Big data, Internet of Things (IoT), Blockchain and Sustainability and how they could create significant interruptions in recent years. These technologies provide various opportunities in the world of manufacturing and supply chain. Blockchain is a next-generation advancement of information technology for achieving sustainability in businesses and industries. The Impact of block chain is beyond economic parameter, it is transforming social interaction, public relations and affect options for sustainable development. The fundamental expertise of Blockchain is data privacy, transparency, value transfer & process effectiveness and automation, which could be leveraged to handle the efficient adjustments necessary to produce sustainable
Veeramalla, Shashi Kanth, Kumar, Vivek
Blockchain based Aircraft Maintenance Records2022-26-114005/26/2022
Currently, Aircraft records and many other archives are in paper format. Paper records like maintenance records included in logbook are cumbersome, inefficient, and insecure compared to the capabilities of modern technology. Blockchain technology is the next step in creating process efficiencies, security, and integrity of maintenance data over the lifetime of an aircraft/engine. Changing paper records to digital records using blockchain is the foundation for a better future towards digital twin and analytics. Blockchain based maintenance can connect a world of data between various groups for extended periods of time by creating a secure digital thread. As regulatory requirements grow and cyber threats loom, blockchain technology can assist in the integrity and security of the captured data. The objective of this paper is to describe the advantages of migrating to digital applications using blockchain and how it can secure the future of the industry.
Jayarajan, Keerthi
SMART Manufacturing with Augmented Reality2022-26-124005/26/2022
Aircraft Manufacturing procedures are very critical and always required skillful engineer who need to follow different process and procedure during daily work. The challenge is not only to identify right tools and manuals but also to keep track of operator usage data and behavior. With Augmented reality, intelligent tools, and analytics we can provide a new lease of life to first-line assembly engineers. The objective is how AR can help us to reduce rework or scrap with the concept of Industry 4.0 were integrating with cutting edge technologies like machine learning, and the Internet of things to meet the fundamental requirements during manufacturing. Smart Manufacturing consists of four major components Cyber-physical systems, IoT, Cloud computing, and Cognitive computing. Integrating AR with IoT our objective is to achieve Cyber-physical systems connectivity and fill the gap between the smallest physical assets to be connected with digital infrastructure. It can help us to Increase
Sahu, Parimal
Aerospace Digital Design and Manufacturing Services- DDMS2022-26-114805/26/2022
Digital Design, Manufacturing & Services (DDMS) is a digital approach to the way aerospace products are designed, manufactured, operated & serviced. The DDMS process focuses on digital methods & tools for end to end digital connectivity of data to meet the business process objectives like cost reduction and time to market, meeting our customers' expectations for quality, safety, functional and environmental performance. The paper covers DDMS technology where unique tools and technologies are developed to meet individual organization requirement which includes study of current available infrastructures in terms design, manufacturing, existing tools etc. Digital serves the long-term perspective, which is the next generation of planes, the new development of the new systems. Digital manufacturing is the use of an integrated, computer-based system comprised of simulation, 3D visualization, analytics and collaboration tools to create product and manufacturing process definitions
R, Suresh M.
Digital Manufacturing Execution System for Special Processes 2022-26-116805/26/2022
Processes like Chrome Conversion Coating, Painting, Temper ETCH are categorized as Special Process in Aerospace. They have many variables in the process which need to be monitored, recorded and inter relationship studied using ML & AI. Study of Process Parameters using IIoT, their impact on Quality and the impact on life cycle (Industry 4.0) due to the process parameters maintained at that time of manufacture needs specialized, customized software for each and every process. The said software needs to have checks and alerts for maintenance of Process parameters. It should, on a daily basis do a few lab measurements to cross check whether the automated measuring accuracy is correct or not. Regular empirical calculations for the concentration of baths should be done and an 'alarm' needs to be raised if any mismatch with actual measurement is found. This way regular checking of measuring instruments should be carried out. This also ensures that the issue is found out before it translates
Damodaran, Ramamurthy
The role of Additive Manufacturing in the era of Industry 4.0 2022-26-116905/26/2022
Progressive innovations enable businesses to stay ahead of competition while also increasing profits. These contributing dynamics have allowed the development of a number of advanced innovations, but no other paradigm has had a larger effect in recent decades than Industry 4.0. The unification of intelligent technological advances and manufacturing systems is promoted by Industry 4.0. Amongst which, additive Manufacturing(AM) plays a critical role in solving some of the 4th industrial revolution's key pressing concerns. Manufacturing was never more versatile, effective, or mechanized than in the Internet of Things(IOT) epoch. One can now develop ever-more complicated innovations which merge tangible items and data management. Automated machineries are capable of communicating with one another, exchanging and processing data, evaluating their operational situation in order to be self-adaptable and sometimes even making selections. All of which happens on its own with very little human
N, Harikeerthana, Kumar PhD, Sachin
Application of AI for Predicting Test Cycles of Drivetrain Component2022-32-001401/09/2022
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
Connections for Control: Communications Interfaces for Position and Motion SensorsTBMG-3958608/01/2021
Curing the Porosity Problem in Additive Manufacturing21AERP08_0208/01/2021
Additive manufacturing, also known as 3D printing, allows the fast and cost-effective production of complex high-quality components in a range of materials. The rise of this technology has been fast, and it is rapidly altering the manufacturing landscape. In 2019, the global additive manufacturing market size was valued at $11.58 billion and is predicted to grow at a CAGR (compound annual growth rate) exceeding 14% from 2020 to 2027 (GVR). Additionally, research from Deloitte shows that additive manufacturing is empowering industry 4.0.
Innovative IoT Sensor Applications Pave the Way to the FutureTBMG-3924406/01/2021
If you tell people that exterminators use temperature sensors to eliminate bedbugs, it prompts questions, and people want to know more. You can get the same reaction when you mention that landfill, entomology labs, and banana-ripening managers use sensor data to automate and optimize their operations.
A Hybrid Method for Automotive Entity Recognition2021-01-017904/06/2021
Over the past decades, automotive industry has made substantial investments in automation solutions, electric and autonomous vehicles and advanced product technologies for enhancing vehicular communication and so on. The rise of industry 4.0 brings out a revolutionary transformation in the automotive industry with low-cost computing, high-speed connectivity, and machine learning that have enabled the digitization of the physical world, transforming insights into optimized actions. These technologies have an important role in the growth and future of automotive domain. Hence it is relevant and important to get insight of different automotive entities like OEMs (Original Equipment Manufacturer), geographical locations and their focusing technologies adapted currently and in the nearby future. In this paper, we are implementing a hybrid method for entity recognition, which is a combination of both rule-based and machine learning based entity recognition techniques. Rule based entity
Sivaraman, Navya K, Koduri, Rajesh, Manalikandy, Mithun
Digital Thread and the Impact on Weapon System Acquisition Cost Growth2021-01-002603/02/2021
The traditional acquisition and development cycles of a weapon system by government agencies goes through multiple stages throughout the life cycle of the product. Over the last few decades, many of the United States military equipment had experienced acquisition cost growth. Many studies by the Department of Defense indicates that the cost growth is a result of multiple factors including the development and manufacturing stages of the product. Organizations with multiple operation sites that goes across multiple states or even countries and continents are finding it increasingly difficult to share informational databases to ensure the corporate synergy between multiple sites or divisions. For such organizations, there exist the need to synchronize the operations and have standard and common database where everything is stored and equally accessed by different sites. Digital transformation sounds real exotic and futuristic and promise to reduce operation costs of big organizations
Hamada, Mohamed Yousef
Quality 4.0: How Wireless IoT Sensor Networks are Reshaping ManufacturingTBMG-3863703/01/2021
Quality control is fundamental in every industry, but in manufacturing it’s hyper-critical. Volatile market demand, high material and production costs, alongside the mission-critical nature of end products, impel manufacturers to pursue nothing but first-rate quality and a minimal rejection rate. With the Internet of Things (IoT) gradually hitting its stride across the manufacturing industry, quality management is an area with transformational opportunities.
Innovation on a Larger Scale: Robotic Fiber Placement and 3D PrintingTBMG-3850602/01/2021
Washington, DC
Modern HMI Software Propels Industry 4.0TBMG-3851402/01/2021
Human-machine interface (HMI) software is continually improving, now providing IT and operations technology (OT) capabilities. Once confined to the role of machine and process visualization and control, modern unified HMI software now delivers better user interfaces, containerization, and remote device management — all wrapped up in a cybersecure package.
Technology Leaders: Industry Renaissance Transforms Invention, Learning, Production, and TradeTBMG-3819612/01/2020
A profound societal transformation is underway on a scale not seen since the great European Renaissance. Then, Gutenberg’s printing press made books — and the knowledge they contained — available to all. Today, the new book is the experience. Digital technology, which enables virtual experiences, is enabling an Industry Renaissance that is shaking all sectors of society with new ways, both real and virtual, of inventing, learning, producing, and trading.
Printable Light Sensors Can See ColorsTBMG-3797511/01/2020
Cameras, light barriers, and movement sensors all work with light sensors that are already found in many applications. In the future, these sensors might also play an important role in telecommunications, as they enable data transmission via light. Printable light sensors have been developed that can see colors.
Taking Benchtop Fluid Dispensing to a New Level of Process ControlTBMG-3807611/01/2020
Pneumatic benchtop fluid dispensers encompass a range of models that can accommodate specific fluid application processes with a wide scope of functionality. The latest benchtop dispensers provide a high degree of process control, capable of dispensing adhesives, solder pastes, and all other assembly fluids with high consistency. Handling fluid dispensing of dots, beads, and fills under a broad range of conditions, these units are equipped with multiple capabilities to refine the dispensing process. Features such as 0–100 psi air pressure regulation, timed-shots, vacuum control to keep thin fluids from dripping, digital time/pressure displays, and electric foot pedals help operators maintain process control.
AI Software Enables Real-Time 3D Printing Quality AssessmentTBMG-3781710/01/2020
Researchers have developed artificial intelligence (AI) software for powder bed 3D printers that assesses the quality of parts in real time without the need for expensive characterization equipment. The software, named Peregrine, supports the advanced manufacturing “digital thread” that collects and analyzes data through every step of the manufacturing process, from design and feedstock selection, to print build and material testing.
Laser Inversion Enables Multi-Material 3D PrintingTBMG-3780610/01/2020
Additive manufacturing, or 3D printing, uses digital manufacturing processes to fabricate components that are light, strong, and require no special tooling to produce. One of the most widely used manufacturing processes, selective laser sintering (SLS), prints parts out of micron-scale material powders using a laser — the laser heats the particles to the point where they fuse together to form a solid mass.
Unsettled Technology Domains in Industrial Smart Assembly Tools Supporting Industry 4.0EPR202001809/29/2020
“Smart” refers to tools that are “specific, measurable, achievable, reasonable/realistic, and time bound.” Smart assembly tools are used in many industries, including automotive, aerospace, and space for measuring, inspecting, gauging, drilling, and installing all existing fastening systems. Inside the Industry 4.0 environment, these tools have a huge influence on Information and Communication Technology (ICT), assembly cost reduction, process control, and even the product and process quality.These four domains—and their undefined nature—are the focus of this SAE EDGE™ Research Report. The technical issues identified here need to be discussed, the goals clarifying the scope of the industry-wide need to be aligned, and the issues requiring standardization need prioritized.NOTE: SAE EDGE Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE Research Reports is to
Roye, Thorsten
USB and GigE Connectivity for Modern Machine VisionTBMG-3766909/01/2020
Over the decades, machine vision has adopted a number of industry standards from the more traditional Camera Link standard that involves the use of frame grabbers to the more mainstream USB 3.0 standard. To keep up with changing camera, processing, and integration technologies, the machine vision standards are consistently evolving, with each protocol serving various industrial niches. This article will discuss in detail the merits of the USB3 and GigE vision standards, how they keep pace with imaging technologies, and how augmenting the cabling is critical for optimal performance.
Advanced Sensing Solutions for Cost-Effective Machine BuildingTBMG-3700606/01/2020
Sensing technology has a major presence in manufacturing machinery. It provides the foundation for maintaining consistent quality and detecting any lapses in machine performance. If subtle changes in the physical properties of a machine can cause it to fail, then the sensors responsible for detecting those changes can save manufacturers lengthy downtime and repair costs.
Improving Robotic Accuracy through Iterative Teaching2020-01-001403/10/2020
Industrial robots have been around since the 1960s and their introduction into the manufacturing industry has helped in automating otherwise repetitive and unsafe tasks, while also increasing the performance and productivity for the companies that adopted the technology. As the majority of industrial robotic arms are deployed in repetitive tasks, the pose accuracy is much less of a key driver for the majority of consumers (e.g. the automotive industry) than speed, payload, energy efficiency and unit cost. Consequently, manufacturers of industrial robots often quote repeatability as an indication of performance whilst the pose accuracy remains comparatively poor. Due to their lack in accuracy, robotic arms have seen slower adoption in the aerospace industry where high accuracy is of utmost importance. However if their accuracy could be improved, robots offer significant advantages, being comparatively inexpensive and more flexible than bespoke automation. Extensive research has been
Sawyer, Daniela, Tinkler, Lloyd, Roberts, Nathan, Diver, Ryan
Item Level Serialization and Traceability of Aerospace Fasteners Based on Individual Inherent Surface Patterns2020-01-001203/10/2020
Item level serialization traceability, defined as the ability to track and trace products, items or components through the supply chain from product manufacturing all the way to the end of life service, has significant value in the aerospace industry. Many items become susceptible to counterfeiting when their origin and authenticity cannot be verified and Item level serialization and traceability fosters supply chain integrity. Data Matrix and radio-frequency identification (RFID) are two common methods that enable detailed information about the manufacturer. However, these methods are not generally compatible with fasteners due to the small size of the fasteners and the cost of these methods. Fasteners are the most commonly used parts on an aircraft and rely on lot level traceability associated with packaging to provide a level of supply chain risk management. However, the association of individual fasteners to parental lots is often lost once the fasteners are removed from packaging
Haylock, Luke Leonard, Schmid-Schirling, Tobias, Saum lng, Norbert, Carl, Daniel, Harde, Jens, Rösing, Jürgen, Murray, Nils, Timpe, Torsten
Digital DHRs: Automating the Last Mile of the Production ProcessTBMG-3627403/01/2020
The smart factory has been a top manufacturing initiative for years as shop floors continue to become digital, automated, and intelligent. Today, companies are investing heavily in smart manufacturing, intelligent automation, and advanced robotics. A 2019 report from PricewaterhouseCoopers and the Manufacturing Institute found that 73 percent of manufacturers planned to increase their investment in smart factory technology over the next year.1
Leading Women in Engineering & Science: Mahsa Nakhjiri, Senior Director of Technical Product Management, FlexTBMG-3624703/01/2020
Collaboration: A Powerful, Effective Strategy for Medtech Companies Moving to Embrace Industry 4.0 and Drive Digital TransformationTBMG-3627603/01/2020
The digital revolution under way in medtech manufacturing will continue to transform the industry into a more connected, efficient, and agile ecosystem. However, the challenge for many companies is to plot the best way to embrace various existing and new technologies and move toward smarter manufacturing — their version of the “factory of the future.” Every company is at a different stage of digital transformation. Some companies are wholeheartedly piloting, integrating, and scaling disruptive technologies within their operations in a bid to realize greater supply chain and internal operational benefits. Others are at a different place in their digital journey, identifying incremental opportunity areas where they can demonstrate initial impact and justify further investment.
Going Beyond the Basics: Innovative Step Motor Designs Give Machine Designers More Options for Motion ControlTBMG-3600202/01/2020
Machine and system designers now have greater options in choosing a motor to meet motion control requirements. While basic step motors with open-loop control schemes abound in the marketplace, different motor and drive designs offer interesting solutions for smarter, faster, quieter operations with more torque. Some incorporate smart drives for higher-level streaming commands or onboard motion control, while others add encoders for greater torque and accuracy. These options can offer better solutions as applications become more sophisticated and demanding, while companies address initiatives for greener operations. This article outlines different step motor options available on the market and considerations for their use.
5G in Manufacturing: What’s Here and What’s to ComeTBMG-3596702/01/2020
Industry 4.0 — the term that originated in Germany to describe the fourth industrial revolution of cyber-physical systems — is being closely connected today with 5G, which is often referred to as the fifth-generation mobile network. This connection allows manufacturers to further improve factory automation, human/machine interfaces, and mobility in their processes.
Precision 3D BioprinterTBMG-3605702/01/2020
nScrypt Inc. Orlando, FL 407-275-4720
Implementing an Aerospace Factory of the FutureTBMG-3605602/01/2020
Companies across a wide range of segments are introducing Industry 4.0 (i4.0) technology at a rapid pace, turning the next-generation vision of manufacturing — the Factory of the Future — into reality. Many of the advances in this transformation have been in highly automated industries such as vehicle manufacturing. Conversely, the aerospace industry, with its staged approach to assembling aircraft, satellites and other products, has only begun to investigate how i4.0 technologies can improve operations, throughput, quality control and cost challenges.
Smart Manufacturing ControlTBMG-3599702/01/2020
The manufacturing process of today involves many challenges, from mass production down to a lot size of one. The CNC controls in factories have to master this market trend without an adequate amount of skilled labor in the US manufacturing world. In essence, manufacturing is facing a renaissance in the CNC control technology shift.
Implementing an Aerospace Factory OF THE FUTURE20AERP02_0402/01/2020
Companies across a wide range of segments are introducing Industry 4.0 (i4.0) technology at a rapid pace, turning the next-generation vision of manufacturing - the Factory of the Future - into reality. Many of the advances in this transformation have been in highly automated industries such as vehicle manufacturing. Conversely, the aerospace industry, with its staged approach to assembling aircraft, satellites and other products, has only begun to investigate how i4.0 technologies can improve operations, throughput, quality control and cost challenges.
In-House PCB Prototyping with Additive ManufacturingTBMG-3581301/01/2020
If you're interested in pursuing in-house PCB prototyping and testing, there are several routes you can take to create functional prototypes for new products. The best one depends on a number of factors, with product complexity being the primary consideration. For highly complex, low-volume products, using an additive manufacturing system is often the best choice for rapid prototyping thanks to its high throughput and fixed cost structure.
NASA's Thirst for Water on Mars Quenched by Student InnovatorsTBMG-3579401/01/2020
Protolabs Maple Plain, MN
The Role of Sensors in the Evolution of RoboticsTBMG-3560912/01/2019
At one time, robotics was considered more science fiction than reality. That's changing. Today, robots are increasingly playing a role in our everyday lives. They're zooming around our homes to pick up dust, helping surgeons perform operations with even more precision, sniffing out suspicious packages for law enforcement, and on the factory floor, they're performing all kinds of tasks for automotive, electronics, and industrial manufacturing companies.
Streamlining Post-Processing in Additive ManufacturingTBMG-3566612/01/2019
Undoubtedly there are many benefits associated with the use of additive manufacturing (AM) as a production technology. On a pan-industrial basis, manufacturers exploit the fact that through the use of AM they can not only build complex parts, in one piece, which were previously impossible, but they can also build stronger, lighter-weight parts, reduce material consumption, and benefit from assembly component consolidation across a range of applications. These advantages have all been well documented during the last 10-20 years as AM has emerged as a truly disruptive technology for prototyping and production, and are invariably seen as being enabled by the additive hardware that builds the parts. In reality, however, this is a partial picture, particularly for serial production applications of AM. AM hardware systems are actually just one part – albeit a vital part – of an extensive ecosystem of technologies that enable AM, both pre- and post-build.
Streamlining Post-Processing in Additive Manufacturing19AERP12_0412/01/2019
Undoubtedly there are many benefits associated with the use of additive manufacturing (AM) as a production technology. On a pan-industrial basis, manufacturers exploit the fact that through the use of AM they can not only build complex parts, in one piece, which were previously impossible, but they can also build stronger, lighter-weight parts, reduce material consumption, and benefit from assembly component consolidation across a range of applications. These advantages have all been well documented during the last 10-20 years as AM has emerged as a truly disruptive technology for prototyping and production, and are invariably seen as being enabled by the additive hardware that builds the parts. In reality, however, this is a partial picture, particularly for serial production applications of AM. AM hardware systems are actually just one part - albeit a vital part - of an extensive ecosystem of technologies that enable AM, both pre- and post-build. By focusing just on the AM build
Vision Based Surface Roughness Characterization of Flat Surfaces Machined with EDM2019-28-014810/11/2019
Surface roughness measurement is an important one in any manufacturing next to dimensions. In this investigation, a vision system and image processing tools were used to develop reliable surface roughness characterization technique for Electrical Discharge Machined surfaces. A CMOS camera with red LED light source were used for capturing images of EDMed surfaces. A separate signal vector generated for all the images from its image pixel intensity matrices. The mean, skewness and kurtosis were obtained from the signal vector. The mean, skewness and kurtosis of the images signal vector correlates very well with the stylus measured hybrid roughness parameters Rda and Rdq. Hence the technique may be preferred for online surface roughness characterization of Electrical Discharge Machined (EDMed) surfaces.
Ali, Mahashar, Jailani, Siddhi, Mariappan, Murugan, Anandan, Mangalnath, Pavithran, Vignesh
Automation: The Future of Medical ManufacturingTBMG-3536710/01/2019
Manufacturers in the medical industry face unique challenges in terms of product mix, throughput requirements, quality standards, and regulatory guidelines. Whether a company is developing imaging equipment, orthopedic implants, or diagnostics, the manufacturing process must be absolutely error free while delivering high throughput. Device companies are looking more and more to factory automation to ensure that they are addressing these disparate requirements.
Step & Repeat: Reduce Derivative Aircraft Development Risk with Design Reuse2019-01-187109/16/2019
The complex and risky process of designing derivative aircraft, especially when it comes to electrical systems, can be a daunting task at best. There are a number of design strategies that can be employed to mitigate risk and increase the overall efficiency. Quite simply, the current methods of manual processes, design and integration approaches that were optimized from mechanical approaches, are no match for today’s complexities. One method gaining significant traction is to employ a central database serving global interface definitions for the entire design process. Automation through generative design minimizes manual intervention and repetitive work. Furthermore, detecting changes through design rule checks allows system engineers to verify their designs, capturing both inadvertent and planned changes. The ability to instantly update the design content from the new definition streamlines the change management process. Employing these technologies in a digital, connected thread
Askar, Muhammad
Build IIoT Networks with Smart Control and HMI SoftwareTBMG-3487908/01/2019
Programmable automation controllers (PACs) play the primary role in IIoT systems. Also referred to as machine controllers, PACs provide a centralized architecture; they act as the central programmable logic controller (PLC) as well as motion, vision, pneumatic, hydraulic controller, and even embedded human-machine interface (HMI) or visualization (Figure 1). The benefit of the PAC approach is that the program does not need to share tags between devices due to components being part of the same device and using the same logic. This facilitates IIoT capabilities and reduces programming time. This is critical to IIoT as it allows the flow of accurate, actionable data to easily transfer within the machine and out to the user or server to make critical decisions with that data.
Introduction to Advanced ManufacturingR-46307/24/2019
Introduction to Advanced Manufacturing was written by two experienced and passionate engineers whose mission is to make the subject of advanced manufacturing easy to understand and a practical solution to everyday problems. Harik, Ph.D. and Wuest, Ph.D., professors who have taught the subject for decades, combined their expertise to develop both an applied manual and a theoretical reference that addresses many different needs. Introduction to Advanced Manufacturing covers the following topics in detail: • Composites Manufacturing • Smart Manufacturing • Additive Manufacturing • Computer Aided Manufacturing • Polymers Manufacturing • Assembly Processes • Manufacturing Quality Control and Productivity • Subtractive Manufacturing • Deformative Manufacturing Introduction to Advanced Manufacturing offers a new, refreshing way of studying how things are made in the digital age. With academics and industry professionals in mind, Introduction to Advanced Manufacturing paves the ground for
Harik, Ramy, Wuest, Thorsten
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