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How Smart Industry is Changing Our Way of Developing

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DQINDIA Online
New Update
NIET

By Philipp Wallner, Industry Manager at MathWorks

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The industrial world is rapidly changing with the emergence of smart industry also known as Industry 4.0. It is the next phase of manufacturing where production machines and handling equipment will become highly integrated mechatronic systems with a significant portion of embedded software. This requires engineers of all three mechatronic domains, ie. mechanical, electrical and software engineering to work together simultaneously and evolve the ways of designing, testing, and verifying machine software and reach advanced level of functionality and quality of manufacturing.

Experts now believe that smart industry will transform the nature of production by optimising the process and changing it into a fully integrated and automated entity. To be part of this revolution, India has to go beyond the large scale industrial parks and the labour-intensive plants from the 20th century. This shift will not be easy and will take time to incorporate itself. Internet of Things (IoT) is largely enabling the Industrial revolution in India due to its dynamic ability to gather, analyse and distribute data into information and knowledge. Experts also say that IoT would not only help the companies in reducing costs, but also help in preventing downtime of machines, improve efficiency, reduce energy consumption and also improve customer service.

The growing amount of data is a major driver of smart industry. Vision sensors, electric and hydraulic drives, production machines, and power plants all collect a growing amount of measured data during production operation. This data contains information that can be transformed into business value through the development of predictive models and algorithms. For instance, machine learning techniques may be used to train a model to historical sensor data, so that the model can be used to predict future equipment failures and prevent production downtimes.

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The analytical and statistical algorithms for condition monitoring and predictive maintenance can be used to derive actionable insights from the data that has been collected and stored. This concept is taken one step further with model-based predictive maintenance, when an observer model is installed within the system. Providing sophisticated sensor networks presents one of the essential prerequisites for realizing the efficiency, cost and, therefore, competitive advantages that smart industry promises. To become innovative leaders in the market, equipment manufacturers need to rapidly develop skills and expertise in these new design approaches and technologies.

Engineers can increase their productivity and system reliability by using Model-Based Design tools. These tools facilitate modular development of automation components, hardware independent testing, and automatic code generation, which can implement algorithms for specific hardware platforms at the touch of a button. Models enable the intuitive and clear construction from predefined building blocks and continuous verification. With this approach, design flaws are corrected early on, which considerably shortens design cycles.

The algorithms need to be implemented, which can be considerably challenging using traditional methods. These traditional practices are not only time consuming but are also prone to errors with the ever-increasing complexity of the algorithms used in machinery. In contrast, real-time functionality is directly generated from simulation models using automatic code generation; this avoids the aforementioned sources of errors. Doing so not only saves time but also enables the creation of innovative solutions in small development teams. Model-Based Design with automatic code generation enables engineers to fully leverage their expertise in construction to build a machine or plant without worrying about programming language details.

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Smart Industry Realization
Keeping up with and being a leader in the worldwide smart industry requires companies in India to offer increasingly efficient and cost effective products, as well as keep an open mind to the new business opportunities that smart industry and the IIoT present. Being able to design and test new software separately from the machine will enable companies to offer revenue-generating upgrades to their customers in order to expand the capabilities of the machine. Innovative machine builders have already started to offer predictive maintenance service contracts to their customers to reduce production line standstills.

Smart industry encompasses the growing complexity of software and an ever-increasing amount of data. In the long term, the evolving trend will challenge engineers to become proficient in using new methods and tools in order to embrace this complexity. The industrial companies who manage to shift their focus towards interdisciplinary design thinking will emerge from the transformation as leaders in their areas and with new business models for their market.

analytics software-testing smart-industry
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