With rapid technology advancements and impacts of digital transformation technologies, there have been a lot of efforts in recent years at the global and national scope to develop technology eco-systems moving toward Industry 4.0. There has also been a growing number of studies about optimization of process parameters based on AI, IoT and Bigdata analytics, including CNC machining, additive manufacturing, as well as industrial welding with robots, for development of Smart Manufacturing (SM), which is one of the key elements of Industry 4.0. However, there are challenges to fully develop and apply in industrial practices the ideal SM models in the next 5 to 10 years. It is necessary to develop the cost-effective SM models that are easy to understand with a high level of applicability in practice and adoptability for SMEs. In this paper , a conceptual digital twin is proposed, with the focus on cost-effective design and development of a welding robotic system for smart manufacturing.

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The civil infrastructure systems play a critical role in the world; however, their average age is becoming higher and higher. Most of these structures need inspection, maintenance or replacement in order to ensure safety requirement of structures as well as users. Structural health monitoring systems has drawn attention from many organizations to manage crucial structures. Applied programming and Internet of Things (IoT) has received a great attention in the last decades due to its potential and capacity to be integrated into any complex system. This paper presents the use LabVIEW, IoT platform and hardwares to build an automated measurement system. The proposed solutions are demonstrated in this paper will help building robust and reliable measurement systems for crucial applications. The measurement system is used to evaluate the health of structures through the changes of natural frequencies.

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