Altair Case Studies Sharda Motors: Leveraging Altair CAE Solution for Durability Analysis in Automobile Manufacturing
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Sharda Motors: Leveraging Altair CAE Solution for Durability Analysis in Automobile Manufacturing

Altair
Analytics & Modeling - Digital Twin / Simulation
Functional Applications - Manufacturing Execution Systems (MES)
Automotive
Buildings
Facility Management
Product Research & Development
Manufacturing Process Simulation
Time Sensitive Networking
Hardware Design & Engineering Services
System Integration
Sharda Motor Industries Limited (SMIL), a market leader in the manufacturing of exhaust systems and other automobile components, was faced with the challenge of reducing product design and development cycle time, effort, and cost. The company aimed to provide innovative products to clients by using simulation, automation, and optimization technologies in the development of exhaust components and systems. The challenge was to evaluate the durability of exhaust system components within a given time frame with high accuracy. They were expected to carry out finite element analysis and explain the results for typical exhaust system components. They also had to consider durability loads such as engine vibration loading and proving ground road-loads. Other durability issues associated with exhaust system components such as the muffler-pipe system, brackets, and hanger designs were required to be analyzed.
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Sharda Motor Industries Limited (SMIL) is a leading manufacturer in the country of exhaust systems, catalytic converters, independent suspension systems, seat frames, seat covers, soft top canopies, and stamped part for white goods products. They believe in maintaining the highest quality standards in the entire product development life cycle. Their state-of-the-art manufacturing facilities help them to continuously focus on new products, innovation, technology upgradation, and research & development. SMIL supplies exhaust systems to major automobile companies like Mahindra, TATA, Hyundai, Force Motors, and SML ISUZU in the country. They support all their clients through cutting-edge research and enable them to produce world-class engineering products.
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To meet their simulation software needs for concept and product design and development, SMIL decided to use the Altair Suite. The SMIL team evaluated the durability of exhaust system components by CAE simulation using Altair HyperWorks. They carried out finite element analysis and explained the results for typical exhaust system components considering various types of durability loads. They also examined durability issues related to other exhaust system components. The team carried out Finite element modeling for passenger car exhaust systems using Altair’s pre-processing tool HyperMesh and performed Static Analysis by using OptiStruct FEA for exhaust components to determine high-stress regions. They followed this up by using the S-N approach for calculating the fatigue life of exhaust system components with the help of HyperWorks and Fatigue Process Manager (FPM) in OptiStruct FEA. The results were viewed through Altair’s post-processing tool HyperView.
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The use of Altair HyperWorks by SMIL resulted in better and accurate results, enabling them to achieve the desired project objectives. The Altair Suite along with their approach produced comparable results with simplified pre and post processing and also resulted in impressive reduction in solving time. This not only improved their productivity but also allowed them to provide innovative solutions to their clients. The team was able to explain in detail their analysis of various exhaust components, thereby improving their product accuracy and achieving client targets vis-à-vis product development time and respective end-customer satisfaction.
Reduced product development cycle time
Improved productivity
Modified the rear pipe thickness from 1.6 mm to 1.2 mm and obtained the Max. Von Misses stress value (1.6 mm = 143.2 Mpa and 1.2 mm =158.003 Mpa) from the Static 4G Analysis for the full system by using OptiStruct FEA.
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