Browse Topic: Productivity

Items (1,147)
To optimize the preparation protocol and tribological performance of glycerol-based Fe^3O^4 magnetic fluids, three hybrid agitation systems—(i) chemical co-precipitation coupled with magnetic stirring (H+C), (ii) chemical co-precipitation coupled with mechanical stirring (H+J), and (iii) chemical co-precipitation integrated with mechanical plus ultrasonic agitation (H+J+C)—were systematically investigated with respect to their influence on the physicochemical characteristics and lubricating behaviour of the resulting magnetic nanoparticles. Relative to the H+C and H+J protocols, the H+J+C protocol effectively suppressed intermediate agglomeration, yielding a 15 % increase in Fe^3O^4 productivity and a 15 % reduction in the full-width at half-maximum of the particle-size distribution. A binary surfactant system composed of oleic acid and citric acid achieved complete surface passivation, producing nanoparticles with a saturation magnetization of 59.2 emu g^–1. Under a magnetic flux density of 0.0341 T, tribometric evaluation revealed that the friction coefficient of the fluid prepared via the H+J+C route decreased to 0.041, corresponding to reductions of 7.1 % and 22 % relative to the H+J and H+C counterparts, respectively, thereby demonstrating superior tribological performance. The present work furnishes an experimental foundation for the rational design of high-performance magnetically responsive lubricants and the optimization of magnetic-fluid synthesis protocols.
Hu, RuiZhong, ShihaoXu, ChunxiaChen, BinhuaLiu, Yang
Manual operations in traditional tea packaging lines often suffer from low productivity, safety risks, and inconsistent labeling quality. To overcome these limitations, this study develops a fully automated tea packaging system guided by an improved genetic algorithm. The system integrates five functional modules—bag feeding, bag opening, material filling, sealing, and labeling—into a seamless workflow. By applying the optimization capability of the improved genetic algorithm, the system achieves better coordination among modules, higher adaptability to different bag shapes and sizes, and improved operational efficiency. Experimental validation demonstrates that the proposed design not only simplifies the packaging procedure but also enhances precision, reliability, and production speed. The system provides a flexible and intelligent solution applicable to a wide range of tea packaging requirements.
Guo, HuiZhao, ZhikaiYuan, WeilongLin, LinYu, YunchangGao, Jiashun
Precision agriculture, also known as smart farming, was once reserved for early adopters or large-scale operations, but is now an expectation within the farming industry. Across various regions and farm sizes, smart farming techniques are changing the way crops are planted as well as how they are monitored and harvested. However, farmers today are under increasing pressure to reduce labor, decrease chemical inputs, conserve water and operate in tighter windows. Couple this with factors such as narrow seasonal windows, productivity demands and safety considerations, and the need for smarter decisions becomes imperative. Going one step further, global food demands and environmental pressures are further increasing demand for precise, accurate and intelligent farming solutions.
Love, Jennifer
Moog Inc. introduced its new adaptive electrification management system (AEMS) at a press conference during CONEXPO 2026 in Las Vegas. Moog states that this system offers a path to electrify, automate and digitalize construction machinery more efficiently and cost-effectively. “End users in the off-highway market are demanding that their machines have higher productivity and a lower total cost of ownership,” said Dr. Nate Keller, Moog strategic business manager. “OEMs are working to solve this problem, and one of the particular ways is through electrification.”
Wolfe, Matt
The advanced construction equipment packing the convention center halls and surrounding lots will understandably be the stars of the triennial CONEXPO trade show, taking place March 3-7 in Las Vegas. But the latest technologies in fluid power and motion control that help those machines operate efficiently will also command attention from showgoers. The Bosch Rexroth mobile hydraulics team will be on-site in a joint booth with partner HydraForce (Booth S80245), showcasing their current product portfolio. Rafael Cardoso, Bosch Rexroth engineering manager, mobile systems and software, expects to have conversations about advanced control and automation, “focused on the demand for smarter, software-driven control strategies that enhance precision, productivity, downtime reduction and operator assistance features.”
Gehm, Ryan
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 of gear microgeometry inspection 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 gear inspection. The research aims to develop a deep learning-based model to eliminate the ambiguity of manual evaluation of microgeometry errors and qualify gears using trained data. In this research we have identified three best possible models used in image classification tasks – Random Forest algorithm, XGBoost algorithm, and Convolutional Neural Network. The dataset is used to train these models, perform hyperparameter tuning, and obtain optimal results based on the confusion matrix, precision, recall, F1 score, and validation accuracy.
Ramakrishnan, Gowtham RajBaheti, PalashPR, VaidyanathanDurgude, RanjitBathla, ArchanaR, GreeshmitaV, Rangarajan
In the area of structural durability testing using servo hydraulic actuators, developing drive files for the actuators is a major step. Testing outcomes depend on ensuring the simulation accuracy of each drive file. These drive files are developed in an iterative process for different test track surfaces at different road and load combinations till the time we achieved better correlation. Evaluation of simulation accuracy of the drive files is an extensive manual review process making it time-consuming and resource-intensive. To address this challenge, an application has been develop to automate the comparison of actuator signals with predefined target signal files. This tool enables quick and accurate analysis of each drive file in a test run facilitating a comprehensive review of signal deviations. Each test run is having thousands of drive files based on road-load mix and actuator settings. This application helped us in significantly optimizing the simulation workflow by reducing the manual effort in reviewing thousands of files and statistical evaluation. The developed solution improves productivity and enhances quality in structural durability assessments using servo hydraulic actuators.
Soni, YashKatake, VrishaliMullapudi, DattatreyuduChaskar, Mithun
This paper presents a novel Plunger-Integrated Hybrid System aimed at enhancing the efficiency and performance of deep drawing operations in metal forming processes. The proposed hybrid system strategically combines the mechanical strength of metals with the elastic flexibility of polymers, specifically polyurethane rubber, to improve formability and reduce spring-back, two critical challenges in conventional sheet metal forming. A novel two-stage forming technique is employed, an initial drawing operation using a larger radius with polyurethane rubber, followed by final radius formation using the same rubber in conjunction with a pneumatic cylinder. This integrated approach ensures uniform force distribution via the embedded plunger, significantly minimizing forming defects and enhancing the dimensional accuracy of the final components. The solution has been validated using Finite Element (FE) simulation methods, confirming its capability to produce high-quality parts suitable for both complex structural geometries and outer body panels in automotive and aerospace applications. Key benefits include: ~17% reduction in manufacturing costs through fewer tool trials, simplified tool design and reduced simulation iterations. Enhanced production rate and process repeatability. Lowered CO₂ emissions footprint by improving material usage efficiency
Chava, Seshadri ReddySingh, PrakharDhanajkar, NarendraRoy, AmlanRaju, Gokul
Additive manufacturing is one of the pillars of technologies of the industry 4.0 and enables rapid prototyping, testing of new materials, and customized manufacturing of parts with personalized design. Poly(lactic acid) (PLA) is a bio-based and biodegradable polymer that is used in packaging, medical applications, and consumer goods. However, it presents low mechanical strength and thermal stability, which limits its use in automotive parts. The use of reinforcement materials such as cellulose nanofibers (CNF) aim to increase the mechanical strength and thermal stability of PLA without reducing its ecological appeal. However, the addition of nanofibers in the 3D printing process can lead to reproducibility problems and constant clogging of the extruder nozzle due to the material’s lower printability. These difficulties may restrict its application to industrial processes due to reduced productivity. To address the challenges in the production of automotive parts with PLA/CNF composites, this paper explored the implementation of a quality management tool to improve the additive manufacturing process using nanocomposite-based filaments. The Ishikawa diagram was used to understand the difficulties observed during production and based on the potential root causes an action plan was developed using 5W2H (five whys and two hows) technique. Through the implementation of the Ishikawa diagram, it was possible to identify critical areas of improvement. Through the 5W2H, specific actions were defined in the whole process, from the nanocomposite and filament manufacturing process to 3D printing parameters. Additionally, standard operating procedures (SOPs) with special routines for the maintenance of the equipment and also for continuously monitoring all the actions that were implemented along the processing stages. For future work, new quality management tools such as checklists and operation flowcharts will be implemented to guarantee better performance of nanocomposites in 3D printing manufacturing processes.
Oliveira, ViníciusHoriuchi, Lucas NaoGonçalves, Ana PaulaSouza, MarianaPolkowski, Rodrigo
Process mining emerges as a very important tool in the automotive industry to improve processes and increase efficiency. Its use allows the identification of bottlenecks and opportunities for improvement in production processes, contributing to increased productivity and cost reduction. This article aimed to evaluate the benefits of applying the Process Mining tool by conducting a Three-way match analysis in the Procure-to-pay (PTP) process of a company in the auto parts sector, seeking to identify opportunities for improvement. Analysis using process mining in PTP of the organization allowed us to identify significant number of cases of price discrepancies were observed in relation to orders related to services, being 2.5 times higher than orders related to materials. Additionally, quantity discrepancies represented 24% of the cases analyzed, compared to only 1.5% of price discrepancies. Of the materials involved in these price discrepancies, approximately 63% were not registered in the system. Most cases of price discrepancies among material suppliers were related to transportation services. Furthermore, 22% of the processes analyzed involved price changes, possibly due to how tax calculation was configured in the SAP system. It is recommended that the company continue to seek solutions to reduce price discrepancies, especially concerning service orders, and increase the level of automation in purchasing and payment processes. In light of the presented results, the process mining tool emerges as a strategic ally, offering competitive advantage by identifying bottlenecks, reducing costs, and automating processes.
Rosa da Silva, Petterson MaxwellCampos, Renato deFranco, Bruno Chaves
Agrícola Cana Caiana and Grunner have developed an innovative vehicle for sugarcane harvesting, focused on reducing fuel consumption. This optimization is vital and relevant for similar operations in the largest global producers: Brazil (724 mi t - 37%), India (439 mi t - 22%), China (103 mi t - 5.3%), Thailand (92 mi t - 4.7%), Pakistan (88 mi t - 4.5%), Mexico (55 mi t - 2.8%), Colombia (35 mi t - 1.8%), Indonesia (32 mi t - 1.6%), USA (31 mi t - 1.6%), and Australia (28 mi t - 1.4%). In Brazil, São Paulo leads with 383.4 mi t (54.1% of the 23/24 harvest), followed by Minas Gerais (81.3 mi t). This innovative agricultural machinery, a result of the owners' experience, has already sold over a thousand units, proving its impact on the efficiency of the sugar-alcohol sector. The Belei family's expertise generated this solution that optimizes resources and increases harvesting productivity, with the potential to advance sustainability and profitability globally, driving agricultural innovation. High market acceptance reinforces this machine's relevance to cost and efficiency challenges, representing a promising example for a more efficient and sustainable agribusiness, with advanced technology for harvesting practices [1].
Ferreira, Antonio Eustáquio Sirolli
This study presents the results of applying a Lean Six Sigma-based analytical approach to optimize the manufacturing of automotive coatings, specifically in a PU primer filling process. Through production flow mapping and the Define, Measure, Analyze, Improve, and Control (DMAIC) methodology, unplanned stoppages in the filling line were significantly reduced, addressing critical inefficiencies in automotive coating production. The research was driven by the need to enhance manufacturing productivity and ensure process reliability in the production of coatings used in the automotive sector. To achieve this, Quality Management tools, such as Pareto Analysis and the Cause-and-Effect Diagram, along with Lean Manufacturing techniques, including Kaizen Blitz, were applied. These methods facilitated the identification and mitigation of key causes of unplanned downtime, improving process efficiency and reliability. The results demonstrated a significant reduction in downtime, enhanced operational efficiency, and an increase in Overall Equipment Effectiveness (OEE). Furthermore, the implementation of Reliability-Centered Maintenance (RCM) practices contributed to process stability and improved failure prediction, ensuring higher consistency in automotive coating production. This study highlights that integrating lean methodologies with data-driven analysis is a highly effective strategy for improving manufacturing performance in the automotive industry, reducing operational costs, and strengthening supply chain resilience for automotive coating manufacturers.
Filho, William Manjud MalufRodrigues, Mateus FerreiraCarriero, Emily AmaralYoshimura, Sofia LucasMarini, Vinicius KasterSiqueira, GonçaloAlves, Marcelo Augusto Leal
Finland-based Metos Oy, a manufacturer of professional stainless steel kitchen equipment, needed a welding solution that could deliver flawless, pressure-rated welds for small batches of high-spec products, which feature tubular structures and circular shafts that required continuous, precision welding.
Imagine a user opening a technical manual, eager to troubleshoot an issue, only to find a mix of stark black-and-white illustrations alongside a few color images. This inconsistency not only detracts from the user experience but also complicates understanding. For technicians relying on these documents, grayscale graphics hinder quick interpretation of diagrams, extending diagnostics time and impacting overall productivity. Producing high-quality color graphics typically requires significant investment in time and resources, often necessitating a dedicated graphics team. Our innovative pipeline addresses this challenge by automating the colorization and classification of colored graphics. This approach delivers consistent, visually engaging content without the extensive investment in specialized teams, enhancing the visual appeal of materials and streamlining the diagnostic process for technicians. With clearer, more vibrant graphics, technicians can complete tasks more efficiently, ultimately saving time and money. Our project utilizes advanced deep learning techniques and a transformer-based architecture known as DDColor [2], focusing on: AUTOCOLORIZATION: Automating the colorization of grayscale graphics using a pixel decoder and a transformer-based color decoder that learns semantic-aware color representations. CLASSIFICATION: A classification model categorizes output images into "perfect" and "imperfect" buckets for rigorous quality control, ensuring only the best visuals are presented. AWS services are utilized to serve quick colorization requests, allowing for efficient processing and timely delivery of results. By implementing these technologies, we achieve consistent visuals while significantly reducing the time and resources required for graphic content development.
Khalid, MaazAkarte, AnuragKale, AniketRajmane, GayatriNalawade, Komal
The development of 3D game ready models is a critical component of the asset creation workflow in industries. However, traditional modeling techniques often demand extensive manual input, particularly in the areas of modeling, retopology, and texturing. To address challenges, we propose the integration of generative AI technologies into the 3D modeling workflow, aiming to enhance efficiency and streamline processes. This paper presents a comprehensive methodology that leverages advanced algorithms, machine learning techniques, and specialized software to automate repetitive tasks associated with 3D asset creation. By harnessing the power of generative AI, we aim to significantly reduce the manual effort required to produce high-quality 3D models, thereby accelerating the overall development timeline. The aim is to enter a prompt/Image as input to get a fully developed Model. Through a series of experimental implementations, we are aiming to demonstrate the effectiveness of our proposed framework in reducing development time without compromising quality. By automating the more tedious aspects of 3D modeling, professionals can focus on higher-level design decisions, fostering innovation and creativity. Moreover, we discuss the broader implications of adopting generative AI in the asset development workflow. The ability to streamline processes and improve productivity can transform how companies approach 3D asset creation, facilitating a more agile response to market demands and enhancing flexibility in project execution. As the industry continues to evolve, integrating these technologies could redefine standards in 3D modeling practices, paving the way for new opportunities and advancements in digital asset production. In conclusion, our research presents a pioneering approach to integrating generative AI into the 3D modeling workflow, with promising results that highlight its potential to revolutionize asset development processes. As the industry continues to evolve, embracing these technologies will be essential for maintaining a competitive edge and driving future advancements in the field of 3D design and production.
Arunachalam, HaripriyaGumaste, AmeyKumar, Pravin
Off-highway vehicles (OHVs) are vital for India’s construction, mining, agriculture, and infrastructure sectors. With growing demand for productivity and sustainability, the need for efficient customer support and precise diagnostic techniques has become paramount. This paper presents a comprehensive study of challenges faced in India, current and emerging diagnostic technologies, troubleshooting techniques, and strategies for effective customer support. Case studies, tables, and diagrams illustrate practical solutions.
Mulla, TosifThakur, AnilTripathi, Ashish
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical models and dynamic torque monitoring techniques to estimate the weight of bales immediately after the bale wrap process, before the bale is dropped onto the field. With the capability to function effectively in off-road conditions and diverse terrains, this system represents a substantial technological advancement that addresses the evolving challenges of modern agriculture. By demonstrating the potential of this design, the paper illustrates how advanced engineering solutions can enhance resource allocation, optimize feed management and distribution, support long-term planning, and contribute to the sustainability of agricultural practices without incurring additional costs. The weight of each bale can be used by farmers to analyze the current harvest based on bale weight variability and to make improvements before the next harvest. It also aids in key decision-making processes such as bale handling, transportation, sales and storage for future seasons. This advancement has significant advantages for scalability and profitability, allowing for optimized decision-making processes in agricultural operations.
Kadam, Pankaj
This paper presents a novel approach to automated robot programming and robot integration in manufacturing domain and minimizing the dependency on manual online/offline programming. Traditional industrial robots programming is typically done by online programing via teach pendants or by offline programming tools. This presents a major challenge as it requires skilled professionals and is a time-consuming process. In today’s competitive market, factories need to harness their full potential through smart and adaptive thinking to keep pace with evolving technology, customer demand, and manufacturing processes. This requires ability to manufacture multiple products on the same production line, minimum time for changeovers and implement robotic automation for efficiency enhancement. But each custom automation piece also demands significant human efforts for development and maintenance. By integrating the Robot Operating System (ROS) with vision-based 3D model generation systems, we address these challenges effectively. A ROS-based framework has been developed to automate the manual offline robot programming and enable real-time task optimization for performing manufacturing operations such as painting, welding, and torquing. The proposed framework—Capture → Connect → Compile → Create—using RGBD camera systems to record 3D point cloud data and part details. It then connects the complete points, annotate features, interprets edges and tasks to be performed and then convert into executable robotic programs. This method significantly reduces manual programming efforts and enables rapid deployment of robotic systems across diverse tasks. The paper outlines the system architecture, implementation methodology, and integration strategy within existing manufacturing lines. Through autonomous robotic programming, this approach enhances mass customization and boosts overall manufacturing efficiency. The proposed system offers a scalable solution for smart factories aiming to achieve high productivity, flexibility, and reduced operational costs.
Hepat, Abhijeet
In the agricultural industry, the logistics of transporting and storing bales, used as cattle feed, pose significant challenges for large scale farms. Traditional storage of bales in barns is labor-intensive, high in capital expenditure and requires multiple trips of transport vehicle on and off the field. Improper handling during this transition can lead to substantial losses in time, resources and loss of hay. This development aims to eliminate the last-mile transportation step, by enabling year-round storage of bales directly in the field. A patented wrapping material, along with strategic orientation of wrapped bales, enhances their resistance to weather conditions. Field experiments demonstrated that this innovative material not only protects the bales from adverse environmental factors but also effectively retains their nutrient and moisture content. A critical aspect of this solution is ensuring the correct orientation of the wrap seams, as the bales are continuously rotated within the baler machine. Correct orientation of the wrapped bale is achieved through implementation of position-tracking algorithm, which provides real-time feedback to the operator via audio-visual alerts, facilitating timely adjustments for optimal bale placement. By integrating a single sensor hardware modification, with software algorithms changes, this solution allows for backward compatibility with existing machinery, significantly enhancing deployment efficiency. This advancement ultimately reduces operator workload and increases overall operational productivity. This paper leverages principles of systems engineering to present a forward-looking solution that addresses multiple industry challenges, thereby contributing to enhanced efficiency and sustainability in agricultural operations. The outcomes of this project are expected to yield significant improvements in productivity and resource management, marking a notable advancement in agricultural technology.
Kadam, Pankaj
Weight and cost are pivotal factors in new product development, significantly impacting areas such as regulatory compliance and overall efficiency. Traditionally, monitoring these parameters across various stages involves manual processes that are often time-intensive and prone to delays, thereby affecting the productivity of design teams. In current workflows, designers must manually extract weight and center of gravity (CG) data for each component from disparate sources such as CAD models or supplier documents. This data is then consolidated into reports typically using spreadsheets before being analyzed at the module level. The process requires careful organization, unit consistency, and manual calculations to assess the impact of each component on overall system performance. These steps are not only laborious but also susceptible to human error, limiting agility in design iterations. To address these challenges, there is a conceptual opportunity to develop a system that could automate the extraction and analysis of weight data. Such a system might include features for identifying anomalies, estimating module-level impacts, and forecasting future changes. Additionally, it could incorporate simulation capabilities to model the effects of design modifications on weight distribution and center of gravity. By enabling real-time data integration and predictive insights, this approach could support more informed decision-making, reduce manual effort, and enhance the accuracy of design data. Notably, by streamlining these processes, the proposed system has the potential to reduce the overall product development timeline by approximately one month, offering a significant advantage in time-to-market. This paper explores the potential of such a system, outlining its envisioned functionalities and the anticipated benefits in terms of efficiency, cost control, and design optimization.
Patil, VivekSahoo, AbhilashBallewar, SachinChidanandappa, BasavarajChundru, Satyanarayana
Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks. The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN. This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on business needs. The paper also discusses integration of IT and OT through protocols such as MQTT and Apache Kafka to enable real-time connectivity and explores how sensor data acquisition can support predictive analytics, including calibration compliance and maintenance forecasting. The proposed multi-layered framework combining sensing, communication, and predictive intelligence demonstrates how digital tool tracking enhances efficiency, reduces downtime, and supports Lean manufacturing principles such as just-in-time readiness, continuous improvement, and overall equipment effectiveness (OEE).
Patel, Shravani Prashant
In the fast-paced world of construction, the demand for machine uptime is paramount. Various construction machines play crucial roles in applications such as digging, loading, landscaping, and demolition. One critical component that significantly enhances machine uptime for these operations is the quick coupler. This attachment facilitates rapid tool changes, enabling operators to switch between attachments seamlessly. It also boosts operator ease and reduces fatigue by eliminating frequent interaction between the operator and the attachments. Additionally, the ease of replacing attachments ensures that operators can easily use the correct attachment for specific tasks optimizing overall attachment usage. This paper aims to study the trade-off between breakout force and productivity when using quick couplers. This research assists customers in determining whether to utilize quick couplers based on their specific application requirements. The findings of this study are designed to help customers make informed decisions about whether to add quick couplers or not.
Bhosale, Dhanaji HaridasPARAMESWARAN, SANKARANNarayanan, Arun
Operating tractors on inclined & uneven terrains for prolonged operations presents safety and ergonomic challenges. Applications such as shuttle operations, loader use, or long-duration implement usage prove to be highly critical based on field observations across Mahindra tractor platforms and it requires skill & experience for maneuvering at ease across usage. We identified the need to offload these repeatable tasks from the operator to improve control & offer comfort. This paper explains the role of Advanced drive assistance features developed for Mahindra tractors suited for all prime mover types – ICE, Alternate Fuels including electric. These features include Hill Hold, Electronic parking brake, Cruise control & Creep mode. Each feature is designed to offload frequent manual tasks from the operator and ensure smoother, safer operation. Hill hold and electronic parking brake work in tandem to offer unparalleled safety by eliminating the fear of tractor roll back in uneven terrain and surfaces both in launch and normal operational scenarios. Cruise and Creep control in a combination have been designed to reduce operator fatigue and increase productivity.
M, RojerSundaram, PavithraNatarajan, SaravananDevakumar, KiranMuniappan, Balakrishnan
Komatsu has announced a new swing machine designed to move large quantities of timber in log loader and millyard environments. The TimberPro TN785D is Komatsu's most powerful and highest capacity machine to date. According to Komatsu, it was built with proven components and new features to meet the demand of high productivity swing applications. “TimberPro has designed this machine to excel in high demand millyard applications where lift capacity, reach combined with stability and hydraulic response are key to maximizing productivity,” said Nathan Repp, product manager for Forest Products at Komatsu. “We understand the real-world demands our customers face in these environments, and the TN785D was designed to meet those needs.”
Wolfe, Matt
In this paper, we describe an innovative V&V approach using the SCADE product, enabling significant reduction of effort while preserving compliance with DO-178C/DO-331. This new approach relies on a unique capability: automatic generation of Low-Level Tests. Details about savings will be provided to show how we can reduce costs, speed up certifications, and bring products to the market faster. We will conclude by summarizing the actual benefits and describing ongoing work to bring other savings in the future.
Xavier Dormoy, FrancoisDion, Bernard
Civil and military rotorcraft operators desire enhanced capabilities from their vehicles in terms of mission efficiency, effectiveness, productivity, and availability. A critical element of this challenge is associated with providing cold weather availability. Currently, cold weather operations are enabled by regulatory actions leading to Limited Approvals, Qualifications, Clearances, and Restrictions. Cold weather certification (clearance of a new aircraft) and continuing airworthiness (maintaining effectiveness of fielded aircraft) are data driven processes. This work provides guidance on an Icing Encounters Survey (IES) based data gathering method supporting continuing airworthiness organizations in improving fleet safety and capabilities during cold weather operations.
Alexander, Marc
SAE TOMORROW TODAY - How Autonomy is Breathing New Life into Farming135155/19/2025
Labor shortages are pushing many family farms to the brink. The solution? Autonomous technology which is emerging as a game-changer--boosting productivity, cutting risk, and giving family farms a fighting chance to thrive for generations to come. At the forefront of this transformation is Blue River Technology, a John Deere subsidiary leading the charge in precision agriculture. From AI-driven tools to autonomous machinery, the company is helping to build the future of farming the John Deere way, meeting farmers in the field and designing solutions grounded in real-world challenges. With safety and scalability built in, farmers can start small with retrofit kits that upgrade existing tractors, making automation more accessible than ever. To learn more, we caught up with Aaron Wells, Director of Engineering at Blue River, to explore how automation is transforming agriculture and giving farmers the tools they need to stay ahead--despite labor challenges. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube. Follow host Grayson Brulte on LinkedIn, Twitter, and Instagram.
Hineman, Marcie
On one hand population is increasing while on the other area under cultivation has been decreasing resulting in increased stress on the productivity to meet the needs. India in particular has been witnessing lot many challenges in terms of mechanization, availability of skilled manpower, urban shift and increased revenue to Agri households from non-Agri streams, lesser participation of women in mechanization. Likeability of younger generations to choose agriculture has declined due to need of strenuous manual works. This paper discusses about the system developed for automating monotonous agricultural tractor operations that offers increased operator comfort and productivity while minimizing operator fatigue. The system uses Electronic Depth & Draft Control (EDDC) system combined with Wheel angle sensors to offer key functions such as auto side braking, implement lift, lower and PTO disengagement during headland turns and automatic reengagement of the above controls. Field tests have shown up to 9% fuel savings and up to 11% higher productivity. This technology significantly has decreased consumption of Fuel, Pesticide besides reducing service costs and has increased productivity of operators and agricultural land.
M, Rojer DennyNatarajan, SaravananBaskar, Augustin
Today’s agriculture demands increased productivity due to the higher cropping intensities. Agricultural field readiness for cultivation requires various operation in field resulting in delay in cultivation which lower down productivity. Therefore, field operation needs to be more efficient in terms of both input cost and time consumption. One way to achieve this is by performing multiple operations in a single tractor pass, utilizing the increased power available in modern Tractors. In some agricultural operations, implements need to be mounted on the front of the tractor. Therefore, designing a front three-point hitching system for the tractor is essential to meet various farming needs, allowing customers to perform multiple operations simultaneously. The use of a front three-point linkage better utilizes the potential of four-wheel drive, higher horsepower tractors. This paper focuses on the comprehensive design process for developing and validating a front hitch system for both future and existing tractor designs. It describes the study of the Real-World Usage Pattern (RWUP) for the front hitch and the creation of a load block program for component validation. Multiple design iterations were conducted to meet CAE acceptance criteria and ensure design robustness. A new lab test was established and performed to assess the hitch’s lifting performance, durability, endurance, and track performance. The recommended design successfully passed physical validation and was implemented in the tractor. The front three-point linkage design achieved 20.25%-time savings and 15.15% fuel savings compared to traditional designs, with a cultivator at the front and a harrow at the rear during field operations, as per ISO-8759(4) and ISO 730 standards.
Kumar, YuvarajV, Ashok KumarPerumal, SolairajGaba, RahulRamdebhai, KaravadaraSubbaiyan, Prasanna BalajiM, Kalaiselvan
Competitive companies constantly seek continuous increases in productivity, quality and services level. Lean Thinking (LT) is an efficient management model recognized in organizations and academia, with an effective management approach, well consolidated theoretically and empirically proven Within Industry 4.0 (I4.0) development concept, manufacturers are confident in the advantages of new technologies and system integration. The combination of Lean and I4.0 practices emerges from the existence of a positive interaction for the evolutionary step to achieve a higher operational performance level (exploitation of finances, workload, materials, machines/devices). In this scenario where Lean Thinking is an excellent starting point to implement such changes with a method and focus on results; that I4.0 offers powerful technologies to increase productivity and flexibility in production processes; but people need to be more considered in processes, in a context aligned with the Industry 5.0 (I5.0) concept created by the European Commission (2021), which represents a differentiated and broader focus, which includes: human-centric, sustainability and resilience, going beyond the production of goods and services solely for profit. Thus, an opportunity arises to discuss how the automotive industry can meet the Agenda 2030 and the Sustainable Development Goals (SDGs) by employing I5.0. This article aims to discuss the Agenda 2030 evolution in an automotive industry through the alignment and application of Lean and I4.0 technologies, to boost operational results, and thus correlate the 169 A3 project results through the A3 methodology application with the SDGs. Thus creating the opportunity to discuss the SDGs in the automotive industry, approach reflected that the mains SDG’s classified in the A3 projects are 8 - Decent Work and Economic Growth (44%), 9 - Industry, Innovation, and Infrastructure (36%) and 12 - Responsible Consumption and Production (11%), those three present a result of 91% of mentions, because it is possible to classify the A3 project with more than one SDG’s. This article contributes to reinforcing the links between Lean Thinking, industrial digital transformation, and the SDGs, pointing out human implications.
Braggio, LuisMarinho, OsmarSoares, LuisLino, AlanRabelo, FábioMuniz, Jorge
LM (Lean manufacturing) is the manufacturing strategy focused on continuous improvement of manufacturing operations. This study has been carried out in manufacturing industry of northern India to assess important success factors, LM strategies applied, and important benefits of both LM strategies and approach. Questionnaire survey has been performed to achieve the desired objectives. Results indicated that manufacturing organizations have great affinity for LM strategies viz. small incremental improvements (kaizen) for strategic success. Production rates are highly improved after implementing LM approach. Mediating role of every success factor have been measured using regression analysis and structural equation modeling. Moreover, correlation shows the highly significant relations between LM strategies and benefits of the LM approach.
Kumar, RajeshKumar, AshwiniKumar, Rajender
Crawler Dozers play a critical role in global construction, mining and industrial sectors, performing essential tasks like pushing the material, grading, leveling and scraping. In the highly competitive dozer market, meeting the growing demand for increased productivity requires strategies to enhance blade capacity and width. Dozer operations involve pushing the material and dozing, where blade capacity significantly influences performance. Factors such as mold board profile, blade height, and width impact the blade capacity which are crucial for productivity in light weight applications such as snow removal and dirt pushing. Blade width is also pivotal for grading and leveling tasks. Traditional blade designs, like straight or fixed U-type blades, constrain operator flexibility, limiting overall productivity. The integration of hydraulic-operated foldable wings on both sides of the blade offers the adaptability to adjust blade capacity which also helps to reduce material spillage. This study investigates the impact of hydraulic folding wings on blade capacity, especially analyzing the correlation between fold angle and blade capacity. In this study, an empirical formula is derived to calculate the blade capacity of a folding blade for different wing folding angles. The optimal fold angle for maximizing capacity is determined for a standard material through analytical methods. Furthermore, a comparative analysis is carried out to assess the blade capacity of a foldable blade at the optimal folding angle in contrast to a straight blade. The study aims to evaluate the consequent influence of the blade capacity on the overall productivity. It is found from the study that the blade curvature included volume accounts for 16% of the total blade capacity and at optimum wing folding angle, the blade capacity is 26% more compared to the straight configuration.
Sahoo, Jyoti PrakashSarma, Neelam Kumar
The EN24 and EN42 materials were machined by the electric discharge machine (EDM). The study aimed to optimize the input variables for the multiple outputs, such as metal removal rate (MRR), tool wear rate (TWR), and surface roughness. The machining of the metal is essential to analyze the surface quality and the production rate. The MRR is a prediction of the production rate and surface roughness resembling the quality of the surface. The input variables were current (A), pulse on time (ton), and pulse duty factor (T). The three levels of current were 3A, 6A, and 9A. The ton time was selected as 30 μs, 50 μs, and 70 μs. The pulse duty factors were selected as 4, 5, and 6. The Taguchi optimization techniques are used to optimize process parameters. The L9 orthogonal array was selected for the process. ANOVA analysis was employed to check the rank of the input parameters relative to the output. The maximum MRR were at 9A, 70 μs, and 4 duty factor for the EN24. The best MRR were at 9A, 70 μs, and 5 duty factor for the EN42. The contribution of ton was maximum compared in the tool wear analysis. The optimum value of tool wear was at 6A, 70 μs, and 4 duty factors for the machining of EN42 and EN24. The surface analysis for EN24 was yielding at 9A, 70 μs, and 4 duty factor, and 9A, 70 μs, and 5 duty factors for the EN42. The maximum contribution of pulse on time for surface finish for machining both the materials. The scanning electron microscopy (SEM) analysis also analyzed the surface quality.
Sahu, Kapil DevSingh, RajnishChauhan, Akhilesh Kumar
High productivity, low manufacturing costs, and high workpiece quality: these are the key factors that deliver sustainability, profitability, and competitive edge for industrial manufacturers. Reliable machine monitoring yields valuable real-time insights into ongoing processes; it is the basis for dependable, productive, and reproducible manufacturing and it helps machine operators to reach well-founded decisions on both short- and long-term improvements. This technology can even capture anomalies in highly dynamic machining processes, so users can respond instantly to ensure high productivity, decrease scrap rates, and prolong tool lifetimes. Thanks to all these advantages, continuous machine and process monitoring based on suitable sensor technology is a critical success factor in today’s manufacturing industry.
Today, advancements in industrial laser cleaning automation show great promise in boosting productivity and safety when rust and contaminant removal or surface preparation is required for higher volumes of components and equipment.
The use of aluminum to manufacture injection molds aims to maximize the productivity of plastic parts, as its alloys present higher heat conductivity than tool steel alloys. However, it is essential to accurately control the injection molding parameters to assure that the design tolerances are achieved in the final molded plastic part. The purpose of this research is to evaluate the use of aluminum alloys in high-volume production processes. It delves into the correlation between the type of material used for mold production (steel or aluminum) and the thickness of the injected part, and how these variables affect the efficiency of the process in terms of the quantity and quality of the produced parts. The findings suggest that replacing steel molds with aluminum alloys significantly reduces injection molding cycle time, the difference ranging from 57.1% to 72.5%. Additionally, the dimensional accuracy and less distortion provided by aluminum have improved product quality. In case of thinner geometries, the results indicated that higher pressures were needed to completely fill the cavity. In addition, an increase in the warping of the parts was observed due to the solidification of the flow front, resulting in more pronounced pressure gradients along the part. Therefore, due to their lower stiffness and high thermal conductivity, aluminum molds would not be recommended for this type of geometry in high-production processes. For the cases associated with lower pressures (greater thicknesses), aluminum molds showed better dimensional quality compared to steel. This result indicates that these tools could be an interesting alternative for manufacturing large volumes of parts in aluminum molds.
Marconi, PedroAmarante, EvandroFerreira, CristianoBeal, ValterRibeiro Júnior, Armando
The integration of collaborative robots, or cobots, into manufacturing has revolutionized traditional processes, offering an unprecedented blend of precision, productivity, and safety. Known for their effectiveness in activities from palletizing to welding, cobots are emerging as invaluable assets for activities involving material removal like sanding, grinding and polishing, relieving human workers from arduous and risky tasks.
The concept of the vehicle has changed in accordance with the technological innovations on last decade. Today we can call these changes basically as "CASE" (Connected, Autonomous/Automated, Shared, and Electric). The ease of product access on the user side and the mass production related works have increased worldwide production volumes. This issue has resulted in a greater demand for manpower in the sector. In addition, management, productivity, and profitability related difficulties have occurred. In this project, improvements were made mainly around the productivity through the automation of "vehicle transfer operations in plant operations", which is one of a major problem and a manpower/hour consuming task. This system named as Remote-Control Auto Driving System (RCD). The advance technology used system enabling unmanned, secured operations, were implemented in mass production environment earlier than the rest of the world.
Iwahori, KentoSawano, TakuroIwazaki, NoritsuguKanou, TakeshiInoue, GoOkamoto, YukiHatano, YasuyoshiYasuyama, ShogoKato, JunyaOka, YuheiKakuma, DaisukeYajima, AmaneChiba, Hiroya
Rotary Bell Atomizers are well established in the automotive industry for top coating applications. This type of atomizer allows to create a uniform coating and is characterized by high productivity. Meanwhile, the effectiveness of the process depends on many complex factors. For instance, the transfer efficiency of the paint material, which is the percentage of the paint reaching the structure surface, ranges from 60-95% depending on the application conditions. Any increase in the transfer efficiency can not only reduce energy and material costs, but also reduce the emission of harmful non-deposited paint particles and the effort to handle them. The use of accurate numerical methods in this process helps to optimize the application process, reduce the number of expensive field experiments, and shortens the development cycle of new vehicles, which ensures predictability of production costs. This paper describes a multidisciplinary framework that allows to simulate the industrial processes of coating paint quickly with high accuracy on complex car geometries. Film deposition of paint droplets on the target, the movement of paint particles between the target and the atomizer and the effect of a swirling air jet on the droplet trajectory are all considered. The complex atomization around the bell cup is replaced by a statistical droplet generator. Furthermore, to speed up the simulation, a simplified version of the complex shaping air system is proposed in the work. To model the process, a coupled multi-physics solver is developed, which combines lattice Boltzmann method for air flow, Lagrangian particle method for paint droplets, and the thin film solver for coating thickness calculation. The paper presents the physical and mathematical model of the process, brief introduction on the numerical methodology, validation results based on experimental data, and the results of modelling practical coating scenarios. Results show that the proposed approach has high reliability and can be applied to accurate top coating simulation and the related process/design optimization.
Panov, DmitriiMenon, MuraleekrishnanZhu, HuaxiangStadik, AlexanderZhang, LingranKotian, AkhileshPeng, ChongMonaco, ErnestoBorra, Ravi KanthBoraey, Mohammed
As the automotive industry focuses on fuel-efficient and eco-friendly vehicles along with reducing the carbon footprint, weight reduction becomes essential. Composite materials offer several advantages over metals, including lighter weight, corrosion resistance, low maintenance, longer lifespan, and the ability to customize their strength and stiffness according to specific loading requirements. This paper describes the design and development of the Rear Under Run Protection Device (RUPD) using composite materials. RUPD is designed to prevent rear under-running of passenger vehicles by heavy-duty trucks in the event of a crash. The structural strength and integrity of RUPD assembly are evaluated by applying loads and constraints in accordance with IS 14812:2005. The design objective was to reduce weight while maintaining a balance between strength, stiffness, weight, manufacturability, and cost. The process involved detailed laminate design, finite element analysis, and optimization using Altair Radioss and OptiStruct solvers. The layup configuration was designed to apply the pultrusion manufacturing process to it, which is well-suited for applications requiring a constant cross-section and high production rates. This technique offers a more efficient and cost-effective solution. Pultruded laminates are created by aligning rovings along the major axis of the component, while different continuous strand mats and fabrics are used to provide strength in the cross or transverse direction. The coupon tests were performed on various layup configurations to characterize the material in different directions for failure analysis material models. The design undergoes validation and optimization through quasi-static analysis, considering all load cases according to the standard. After finalizing the design through simulation, a final prototype was made based on the final laminate thickness, and the component was manufactured using the pultrusion manufacturing process. As a result, the weight of the newly designed RUPD was reduced by 25% compared to the previous metal component.
Srivastava, SanjaySonkusare, Shailesh
A crucial component utilized in the trunk space is the luggage board. Positioned at the bottom of the trunk, the trunk board separates the vehicle body from the interior and supports for luggage. The luggage board serves multiple functions, including load-bearing stiffness for luggage, partition structure functionality, noise insulation, and thermal insulation. There is a need for a competitive new luggage board manufacturing method to meet the increasing demand for luggage boards in response to the changing market environment. To address this, the "integrated sandwich molding method" is required. The integrated sandwich molding method utilizes three key methodologies: grouping processes to integrate similar functions, analyzing materials to replace them with suitable alternatives, and overcoming any lacking functionality through integrated design structures. This paper presents a methodology for developing the integrated sandwich molding method. It aims to validate the key performance aspects (stiffness, NVH, insulation) of trunk boards manufactured using this method, demonstrating productivity improvement and lightweight capabilities.
Park, Hee SangYoon, Yeon SimLee Sr, Seung KunKim Sr, Seok CheolLee, Dong Han
As manufacturers push for increased productivity, low-value tasks such as material transport have become clear targets for improvement. In efforts to reduce material transport in large facilities, companies have explored the use of intermediate warehouse areas throughout the production floor. However, this takes up valuable space, requires additional material processing and handling, and creates opportunities for errors and lost or misplaced materials.
Diversity in the workforce contributes to creativity, productivity, and innovation. More women today are studying and excelling in science, technology, engineering, and mathematics (STEM). In the U.S., women make up 14 percent of the engineering workforce. The number of female engineers across the globe is on the rise but compared to male engineers it is still much lower.
Efficient transportation for carrying heavy loads is a common challenge across various applications, from supermarkets to industrial purposes. Conventional trolleys often fall short when loaded with heavy cargo, resulting in increased exertion and diminished productivity. Moreover, these challenges can adversely affect posture and lumbar spine health, especially for elder people and persons with cervical problems. There is a need for more user-friendly, ergonomic, and space-efficient solutions. This project addresses these challenges through an innovative design that encompasses various aspects of trolley functionality, including the study of comfort, wheel selection, and material considerations, drawing from ergonomic research. Multiple methods are employed to optimize the trolley’s dimensions to improve its overall performance. The trolley’s design features a collapsible basket for the transport of smaller-sized items and a base frame for larger goods and luggage. The project underscores the trolley’s potential to reduce musculoskeletal discomfort and reduce fatigue among users, showcasing the positive impact of ergonomic interventions. This adaptable folding cart represents a promising solution for the efficient and comfortable transportation of heavy loads, benefiting a diverse range of users in various applications.
Krishnaraj, S.Senthil Kumar, R.Sedhumadhavan, P.Mahmoodu Murshid Abdullah, I.Abdul Rahman, N.
Being an engineer-to-order (ETO) operating industry, the control cabinet industry faces difficulties in process and workplace optimizations due to changing requirements and lot size one combined with volatile orders. To optimize workplaces for employees, current literature is focusing on ergonomic designs, providing frameworks to analyze workplaces, leaving out the optimal design for productivity. This work thus utilizes a Kano analysis, collecting empirical data to identify essential design requirements for assembly workplaces, incorporating input from switchgear manufacturing employees. The results emphasize the need for a balance between ergonomics and efficiency in workplace design. Surprisingly, few participants agree on the correlation between improved processes and workspaces having a positive impact on their well-being and product quality. Ultimately, the study offers a list of requirements that are needed at ETO assembly stations to satisfy employees and improve efficiency of the production processes.
Stoidner, MichaBründl, PatrickMatthes, TinaNguyen, Huong GiangAbrass, AhmaddFranke, Jörg
Items per page:
1 – 50 of 1147