Advanced Manufacturing Solutions (AMS) Pte Ltd has been established by expert Professor after gaining 34 years of outside India experience @ ASTAR Singapore Institute of Manufacturing Technology, Okamoto Machine Tools and University of Cape Town in the field of Advanced Manufacturing. The WZL-AMS offer technology training along with the industry proven instructions to enhance the competitiveness and abilities of the Industrial workforce particularly on the material processing technologies. The training programs was nurtured, in close partnership with the WZL, Germany and built on the foundations of our extensive in-house expertise in cutting-edge manufacturing knowledge, gained through years of industry collaborations, hands-on experience, and research. The training would power up the practicing engineers to apply the manufacturing-sciences based approach for resolving the manufacturing challenges and promote a significant cost savings. The trainer is a NRF rated researchers at Singapore and South Africa and archived with a Research Gate Score 34.5, Citations 1200 and Multiple award winner & a specialist in advanced Manufacturing.
AI in manufacturing aims to optimize the production processes through better utilizing the manufacturing resources with the real time information. The real time digital process information in milliseconds is correlated to manufacturing science to evolve a customized input that maximize the process efficiency with a minimum use of resources. The AI model connects the tool-work interface behavior and makes a through iteration on fracture mechanics, materials sciences, tribology and contact mechanics. As a result, the AI model significantly upgrade the production and quality features of the component and hence the life cycle of the component is significantly improved. Presently in the Industry 4.0 domain, the AI is configured using a service-oriented architecture through a real time collaborative arrangement with the think tanks and hence the speed of decision to maximize the process efficiency is beyond the imaginations. Furthermore, the human machine interface establishes to implement the various AI centered manufacturing elements and facilitate organizational, managerial and technological milestones.
Additive manufacturing (AM) can be described as a technique of blending materials by either fusion, binding, or solidifying materials such as liquid resin and powders. Although AM offer numerous benefits, like design flexibility, ability to print complex structures, ease of use, and product customization, the AM technology needs several customized inputs to employ in the real world applications. The limit on the part size, anisotropic mechanical properties, building of overhang surfaces, high costs, low manufacturing efficiency, poor accuracy, warping, pillowing, stringing, gaps in the top layers, under-extrusion, layer misalignment, over-extrusion, elephant foot, mass production and limitation in the use materials are the challenges that need investigations and customization. In the metal power-based AM, void formation between layers of AM parts is one of the major drawbacks. This kind of problem occurs due to reduced bonding between layers, thus causing inferior mechanical performance. Therefore, Advancements in manufacturing industry depend on leading edge research associated with manufacturing processes, materials, and product design. AMS is committed to unveil the science of fusions between the metal powders and opens up opportunities to replace the present-day components with the metal powder-based AM components.
Engineering features in hard and brittle materials, are commonly. machined using the abrasive assisted processes. The continuing trend in miniaturization of component features, demands further miniaturization of the tools and abrasive processes themselves. Therefore, a need for a deeper understanding of the mechanisms of abrasive small scale material removal processes is required. Past research suggest that knowledge from common scale abrasive machining is not fully scalable to the micro scale as demonstrated by the size effects of the brittle-ductile transition area. Modelling of such small-scale material removal processes appears to be a promising technique to gain a deeper understanding of the underlying mechanisms. AMS is committed to establish the science of abrasive-work interactions and opens up new opportunities for evolving micro/nano manufacturing techniques through manufacturing simulation, analytical study and customized experimental studies.
